〔論文〕個人主義・集団主義が高圧的説得への抵抗の理由に及ぼす効果：抵抗の動機としてのリアクタンスと調和維持

　The purpose of this paper is to examine the difference between individualists and collectivists in their reasons for resistance to high-pressure communication. Reactance is assumed to be related to individualism. So, individualists would perceive high-pressure persuasion as a threat to freedom, and would resist it for this reason. In contrast, collectivists would perceive that coercive persuasion would disturb the harmony of group. It was hypothesized that horizontal individualism is positively associated with resistance due to freedom-infringement and that horizontal collectivism is positively associated with resistance due to harmony-disturbance, in response to coercive persuasion. Undergraduates （N=121） participated in a study to test these hypotheses. They were asked to read 5 short coercive communications and to rate these communications from two standpoints, that is, freedom-infringement and harmony-disturbance. A path analysis showed that horizontal individualism was positively associated with freedom-infringement, and that horizontal collectivism was positively associated with harmony-disturbance, as expected. Theoretical and practical implications of these findings are discussed

Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling

Deep hedging is a deep-learning-based framework for derivative hedging in incomplete markets. The advantage of deep hedging lies in its ability to handle various realistic market conditions, such as market frictions, which are challenging to address within the traditional mathematical finance framework. Since deep hedging relies on market simulation, the underlying asset price process model is crucial. However, existing literature on deep hedging often relies on traditional mathematical finance models, e.g., Brownian motion and stochastic volatility models, and discovering effective underlying asset models for deep hedging learning has been a challenge. In this study, we propose a new framework called adversarial deep hedging, inspired by adversarial learning. In this framework, a hedger and a generator, which respectively model the underlying asset process and the underlying asset process, are trained in an adversarial manner. The proposed method enables to learn a robust hedger without explicitly modeling the underlying asset process. Through numerical experiments, we demonstrate that our proposed method achieves competitive performance to models that assume explicit underlying asset processes across various real market data.Comment: 8 pages, 7 figure

Gain Tuning Model of Human Expert for Looper Height Control in Hot Strip Rolling

In hot strip rolling mills, the looper control system is automated. However, the looper's behavior tends to be unstable in threading. Therefore, human expert always intervenes and stabilizes the looper's behavior by tuning PID gains and interposing manipulation variable of looper control system. In this paper, we propose a method based on the recurrent neural network to express PID gains tuning action by human. Furthermore, we propose two methods to update the model by learning. To check the effectiveness of the proposed learning methods, numerical simulation applied to the looper height control is carried out

Pulsed UCN production using a Doppler shifter at J-PARC

We have constructed a Doppler-shifter-type pulsed ultra-cold neutron (UCN) source at the Materials and Life Science Experiment Facility (MLF) of the Japan Proton Accelerator Research Complex (J-PARC). Very-cold neutrons (VCNs) with 136-$\mathrm{m/s}$ velocity in a neutron beam supplied by a pulsed neutron source are decelerated by reflection on a m=10 wide-band multilayer mirror, yielding pulsed UCN. The mirror is fixed to the tip of a 2,000-rpm rotating arm moving with 68-$\mathrm{m/s}$ velocity in the same direction as the VCN. The repetition frequency of the pulsed UCN is $8.33~\mathrm{Hz}$ and the time width of the pulse at production is $4.4~\mathrm{ms}$. In order to increase the UCN flux, a supermirror guide, wide-band monochromatic mirrors, focus guides, and a UCN extraction guide have been newly installed or improved. The $1~\mathrm{MW}$-equivalent count rate of the output neutrons with longitudinal wavelengths longer than $58~\mathrm{nm}$ is $1.6 \times 10^{2}~\mathrm{cps}$, while that of the true UCNs is $80~\mathrm{cps}$. The spatial density at production is $1.4~\mathrm{UCN/cm^{3}}$. This new UCN source enables us to research and develop apparatuses necessary for the investigation of the neutron electric dipole moment (nEDM).Comment: 32 pages, 15 fugures. A grammatical error was fixe

Correlation-driven organic 3D topological insulator with relativistic fermions

Exploring new topological phenomena and functionalities induced by strong electron correlation has been a central issue in modern condensed-matter physics. One example is a topological insulator (TI) state and its functionality driven by the Coulomb repulsion rather than a spin-orbit coupling. Here, we report a "correlation-driven" TI state realized in an organic zero-gap system $\alpha$-(BETS)$_2$I$_3$. The surface metallic state that emerges at low temperatures exhibits characteristic transport properties of a gapless Dirac semimetal, evidencing the presence of a topological surface state in this compound. Moreover, we observe a topological phase switching between the TI state and non-equilibrium Dirac semimetal state by a dc current, which is a unique functionality of a correlation-driven TI state. Our findings demonstrate that correlation-driven TIs are promising candidates not only for practical electronic devices but also as a field for discovering new topological phenomena and phases.Comment: 36 pages including 10 figure

Objective evaluation method using multiple image analyses for panoramic radiography improvement

Introduction: In the standardization of panoramic radiography quality, the education and training of beginners on panoramic radiographic imaging are important. We evaluated the relationship between positioning error factors and multiple image analysis results for reproducible panoramic radiography. Material and methods: Using a panoramic radiography system and a dental phantom, reference images were acquired on the Frankfurt plane along the horizontal direction, midsagittal plane along the left-right direction, and for the canine on the forward-backward plane. Images with positioning errors were acquired with 1-5 mm shifts along the forward-backward direction and 2-10 degrees rotations along the horizontal (chin tipped high/low) and vertical (left-right side tilt) directions on the Frankfurt plane. The cross-correlation coefficient and angle difference of the occlusion congruent plane profile between the reference and positioning error images, peak signal-to-noise ratio (PSNR), and deformation vector value by deformable image registration were compared and evaluated. Results: The cross-correlation coefficients of the occlusal plane profiles showed the greatest change in the chin tipped high images and became negatively correlated from 6 degrees image rotation (r = -0.29). The angle difference tended to shift substantially with increasing positioning error, with an angle difference of 8.9 degrees for the 10 degrees chin tipped low image. The PSNR was above 30 dB only for images with a 1-mm backward shift. The positioning error owing to the vertical rotation was the largest for the deformation vector value. Conclusions: Multiple image analyses allow to determine factors contributing to positioning errors in panoramic radiography and may enable error correction. This study based on phantom imaging can support the education of beginners regarding panoramic radiography