Magnetic properties of epitaxial Fe3_3O4_4 films with various crystal orientations and TMR effect in room temperature

Fe$_3$O$_4$ is a ferrimagnetic spinel ferrite that exhibits electric conductivity at room temperature (RT). Although the material has been predicted to be a half metal according to ab-initio calculations, magnetic tunnel junctions (MTJs) with Fe$_3$O$_4$ electrodes have demonstrated a small tunnel magnetoresistance effect. Not even the sign of the TMR ratio has been experimentally established. Here, we report on the magnetic properties of epitaxial Fe$_3$O$_4$ films with various crystal orientations. The films exhibited apparent crystal orientation dependence on hysteresis curves. In particular, Fe$_3$O$_4$(110) films exhibited in-plane uniaxial magnetic anisotropy. With respect to the squareness of hysteresis, Fe$_3$O$_4$ (111) demonstrated the largest squareness. Furthermore, we fabricated MTJs with Fe$_3$O$_4$(110) electrodes, and obtained an TMR effect of -12\% at RT. The negative TMR ratio corresponded to the negative spin polarization of Fe$_3$O$_4$ predicted from band calculations

Testing Higgs models via the H±W∓ZH^\pm W^\mp Z vertex by a recoil method at the International Linear Collider

In general, charged Higgs bosons $H^\pm$ appear in non-minimal Higgs models. The $H^\pm W^\mp Z$ vertex is known to be related to the violation of the global symmetry (custodial symmetry) in the Higgs sector. Its magnitude strongly depends on the structure of the exotic Higgs models which contain higher isospin $SU(2)_L$ representations such as triplet Higgs bosons. We study the possibility of measuring the $H^\pm W^\mp Z$ vertex via single charged Higgs boson production associated with the $W^\pm$ boson at the International Linear Collider (ILC) by using the recoil method. The feasibility of the signal $e^+e^-\to H^\pm W^\mp \to \ell \nu jj$ is analyzed assuming the polarized electron and positron beams and the expected detector performance for the resolution of the two-jet system at the ILC. The background events can be reduced to a considerable extent by imposing the kinematic cuts even if we take into account the initial state radiation. For a relatively light charged Higgs boson whose mass $m_{H^\pm}$ is in the region of 120-130 GeV $< m_{H^\pm} < m_W+m_Z$, the $H^\pm W^\mp Z$ vertex would be precisely testable especially when the decay of $H^\pm$ is lepton specific. The exoticness of the extended Higgs sector can be explored by using combined information for this vertex and the rho parameter.Comment: 22 pages, 23 figure

看護教育に携帯電話を活用した参画支援ソフトウェア”ECILS”によるeラーニングの試案

看護教育において、株式会社エネックスが開発した携帯電話を利用した参画支援ソフトウェア“ECILS”を活用するシステムを試案した。 “ECILS”の機能は①リアルタイムアンケート集計、②メッセージコミュニケーション、③出席管理、④簡易理解度測定（小テスト）、⑤課題提出、⑥連絡網、⑦メッセージ検索である。“ECILS"をうまく活用することで、学生の学習意欲の向上が期待でき、参画力が身に付くことが推察される。携帯電話による利便性から情報管理や情報活用の広がりがあり、教員の授業支援と教育力向上に寄与するシステムでもある

Unconscious Other’s Impression Changer: A Method to Manipulate Cognitive Biases That Subtly Change Others’ Impressions Positively/Negatively by Making AI Bias in Emotion Estimation AI

Artificial Intelligence (AI) for human emotion estimation, such as facial emotion estimation, has been actively studied. On the other hand, there has been little research on unconscious phenomena in cognition and psychology (i.e., cognitive biases) caused by viewing AI emotion estimation information. Therefore, this study verifies RQ “Do people have a cognitive bias in which impressions of others (i.e., how to see and feel about others) are changed by viewing biased AI’s emotion estimation information? If it exists, can impression manipulation methods that intentionally use this cognitive bias be realized?” The proposed method for verification makes the emotion estimation system biased so as to estimate emotion more positively/negatively than AI without bias. A prototype system was implemented. Evaluation using video showed that the presentation of biased emotion estimation information causes a phenomenon that quickly and unconsciously changes the way people see and feel others’ impressions, which supported the RQ. Specifically, viewing information that estimated others’ emotions more positively/negatively caused the phenomenon in which the user’s self-judgment was overridden and others’ impressions of emotions, words, and actions were perceived more positively/negatively. The existence of this phenomenon and method indicates that biased emotion estimation AI has the potential to both cause adverse effects on people and support people for good purposes through the manipulation of their impressions. This study provides helpful insights for the design and use of emotion estimation AI considering cognitive biases