日本古代の郡司と天皇

学位の種別:課程博士University of Tokyo(東京大学

ユーザの特性情報付きチャットボットとの雑談対話コーパスの概要

Doshisha UniversityTokyo University of TechnologyShibaura Institute of TechnologyTokyo University of TechnologyDoshisha University会議名: 言語資源ワークショップ2022, 開催地: オンライン, 会期: 2022年8月30日-31日, 主催: 国立国語研究所 言語資源開発センター本発表では、構築中のチャットボットとの雑談対話コーパスについて紹介する。本コーパスは、参加者がチャットアプリを通してチャットボットと雑談したデータに対して「対話行為」のタグ、チャットボットの発言に対して「対話破綻」のタグを付与したものである。また、各雑談データに参加者の対話に関する印象・満足度、性格特性・社会的スキルの数値を付与している点で特色のあるコーパスとなっている。雑談データの概要を説明したのち、付与された2種類のタグと参加者の性別、性格特性、社会的スキルとの関連について予備的分析を行った結果を報告する

Ecrg4 peptide is the ligand of multiple scavenger receptors

Esophageal cancer-related gene 4 (Ecrg4) encodes a hormone-like peptide that is believed to be involved in a variety of physiological phenomena, including tumour suppression. Recent progress in the study of Ecrg4 has shown that Ecrg4 is a proinflammatory factor and induces the expression of several cytokines and chemokines in macrophages/microglia. However, the detailed molecular mechanisms of Ecrg4 signalling, especially the Ecrg4 receptors, remain poorly understood. Here, using retrovirus-mediated expression cloning, we identified lectin-like oxidised low-density lipoprotein receptor-1 (LOX-1) as a membrane protein that binds amino acid residues 71-132 of Ecrg4 (Ecrg4(71-132)). Moreover, in addition to LOX-1, several scavenger receptors, such as Scarf1, Cd36 and Stabilin-1, facilitated the efficient internalisation of Ecrg4(71-132) into cells. A broad competitive inhibitor of scavenger receptors, polyinosinic acid, reduced both the binding of Ecrg4(71-132) and the activation of NF-kappa B in microglia. This activation was dependent on MyD88, an adaptor protein that recruits signalling proteins to Toll-like receptors (TLRs), with the consequent induction of various immune responses. These data suggest that multiple scavenger receptors recognise Ecrg4(71-132) and transduce its signals, together with TLRs, in microglia

Script Generation using Rhetorical Information in a Task Specification Text ∗

Abstract – In order to extend the application domain of natural language interfaces to more realistic tasks without the decrease of user’s performance, it is desirable for users to be able to specify their requests as coherent texts consisting of more than one sentence. This paper presents a processing model of a natural language interface that accepts such an input text. Rhetorical information in an input text is used to generate a control structure of an output script program. Detection of loop structures, paraphrasing and dialogue are also incorporated. The algorithms explained in this paper have been implemented and evaluated in a personal email management domain