http://hdl.handle.net/10061/4714 Sun, 19 May 2013 23:38:42 GMT 2013-05-19T23:38:42Z http://hdl.handle.net/10061/8622 Title: Synthesis of Very-Long-Chain Fatty Acids in the Epidermis Controls Plant Organ Growth by Restricting Cell Proliferation Authors: Takashi Nobusawa; Yoko Okushima; Noriko Nagata; Mikiko Kojima; Hitoshi Sakakibara; Masaaki Umeda Abstract: Plant organ growth is controlled by inter-cell-layer communication, which thus determines the overall size of the organism. The epidermal layer interfaces with the environment and participates in both driving and restricting growth via inter-cell-layer communication. However, it remains unknown whether the epidermis can send signals to internal tissue to limit cell proliferation in determinate growth. Very-long-chain fatty acids (VLCFAs) are synthesized in the epidermis and used in the formation of cuticular wax. Here we found that VLCFA synthesis in the epidermis is essential for proper development of Arabidopsis thaliana. Wild-type plants treated with a VLCFA synthesis inhibitor and pasticcino mutants with defects in VLCFA synthesis exhibited overproliferation of cells in the vasculature or in the rib zone of shoot apices. The decrease of VLCFA content increased the expression of IPT3, a key determinant of cytokinin biosynthesis in the vasculature, and, indeed, elevated cytokinin levels. These phenotypes were suppressed in ipt3;5;7 triple mutants, and also by vasculature-specific expression of cytokinin oxidase, which degrades active forms of cytokinin. Our results imply that VLCFA synthesis in the epidermis is required to suppress cytokinin biosynthesis in the vasculature, thus fine-tuning cell division activity in internal tissue, and therefore that shoot growth is controlled by the interaction between the surface (epidermis) and the axis (vasculature) of the plant body. Wed, 10 Apr 2013 00:00:00 GMT http://hdl.handle.net/10061/8622 2013-04-10T00:00:00Z http://hdl.handle.net/10061/8621 Title: Conversion of a Signal into Forces for Axon Outgrowth through Pak1-Mediated Shootin1 Phosphorylation Authors: Michinori Toriyama; Satoshi Kozawa; Yuichi Sakumura; Naoyuki Inagaki Abstract: Soluble guidance cues can direct cellular protrusion and migration by modulating adhesion and cytoskeletal dynamics. Actin filaments (F-actins) polymerize at the leading edge of motile cells and depolymerize proximally [1 and 2]; this, together with myosin II activity, induces retrograde flow of F-actins [3, 4 and 5]. It has been proposed that the traction forces underlying cellular motility may be regulated by the modulation of coupling efficiency between F-actin flow and the extracellular substrate via “clutch” molecules [6, 7, 8, 9 and 10]. However, how cell signaling controls the coupling efficiency remains unknown. Shootin1 functions as a linker molecule that couples F-actin retrograde flow and the substrate at neuronal growth cones to promote axon outgrowth [11]. Here we show that shootin1 is located at a critical interface, transducing a chemical signal into traction forces for axon outgrowth. We found that a chemoattractant, netrin-1, positively regulates traction forces at axonal growth cones via Pak1-mediated shootin1 phosphorylation. This phosphorylation enhanced the interaction between shootin1 and F-actin retrograde flow, thereby promoting F-actin-substrate coupling, force generation, and concomitant filopodium extension and axon outgrowth. These results suggest that dynamic actin-substrate coupling can transduce chemical signals into mechanical forces to control cellular motility and provide a molecular-level description of how this transduction may occur. Thu, 28 Feb 2013 00:00:00 GMT http://hdl.handle.net/10061/8621 2013-02-28T00:00:00Z http://hdl.handle.net/10061/8613 Title: Acoustic Model Training Using Pseudo-Speaker Features Generated by MLLR Transformations for Robust Speaker-Independent Speech Recognition Authors: Arata Itoh; Sunao Hara; Norihide Kitaoka; Kazuya Takeda Abstract: A novel speech feature generation-based acoustic model training method for robust speaker-independent speech recognition is proposed. For decades, speaker adaptation methods have been widely used. All of these adaptation methods need adaptation data. However, our proposed method aims to create speaker-independent acoustic models that cover not only known but also unknown speakers. We achieve this by adopting inverse maximum likelihood linear regression (MLLR) transformation-based feature generation, and then we train our models using these features. First we obtain MLLR transformation matrices from a limited number of existing speakers. Then we extract the bases of the MLLR transformation matrices using PCA. The distribution of the weight parameters to express the transformation matrices for the existing speakers are estimated. Next, we construct pseudo-speaker transformations by sampling the weight parameters from the distribution, and apply the transformation to the normalized features of the existing speaker to generate the features of the pseudo-speakers. Finally, using these features, we train the acoustic models. Evaluation results show that the acoustic models trained using our proposed method are robust for unknown speakers. Mon, 01 Oct 2012 00:00:00 GMT http://hdl.handle.net/10061/8613 2012-10-01T00:00:00Z http://hdl.handle.net/10061/8614 Title: 音声対話システムの発話・動作タグN-gramを用いた課題未達成のオンライン検出 Authors: 原 直; 北岡 教英; 武田 一哉 Abstract: 本論文ではN-gram特徴を用いた音声対話システム利用時の課題未達成対話の検出手法を提案する．実験にはユーザが自分のPC上で利用するという，実環境下で収録された楽曲検索のための音声対話システムとの対話データを利用する．楽曲検索課題を行っている全ての対話データはユーザとシステムの発話を抽象化した発話・動作タグにより記述し，そのタグ系列をN-gramとしてモデル化を行う．本研究では，タグ系列中のタグN-gramの出現回数を素性として，Support Vector MachineやC4.5決定木などの識別的手法による課題未達成対話の検出実験を行った．更に対話長や反応時間などの対話の特徴を表す対話変数を導入することで検出性能の向上を行った．その結果，ユーザの4回目の発話までを用いることで，約76%の識別率となった． Tue, 01 Jan 2013 00:00:00 GMT http://hdl.handle.net/10061/8614 2013-01-01T00:00:00Z