Selective Sampling for Example-based Word Sense Disambiguation

This paper proposes an efficient example sampling method for example-based word sense disambiguation systems. To construct a database of practical size, a considerable overhead for manual sense disambiguation (overhead for supervision) is required. In addition, the time complexity of searching a large-sized database poses a considerable problem (overhead for search). To counter these problems, our method selectively samples a smaller-sized effective subset from a given example set for use in word sense disambiguation. Our method is characterized by the reliance on the notion of training utility: the degree to which each example is informative for future example sampling when used for the training of the system. The system progressively collects examples by selecting those with greatest utility. The paper reports the effectiveness of our method through experiments on about one thousand sentences. Compared to experiments with other example sampling methods, our method reduced both the overhead for supervision and the overhead for search, without the degeneration of the performance of the system.Comment: 25 pages, 14 Postscript figure

Syndecan- and integrin-binding peptides synergistically accelerate cell adhesion

AbstractIntegrins and syndecans mediate cell adhesion to extracellular matrix and their synergistic cooperation is implicated in cell adhesion processes. We previously identified two active peptides, AG73 and EF1, from the laminin α1 chain LG4 module, that promote cell attachment through syndecan- and α2β1 integrin-binding, respectively. Here, we examined time-dependent cell attachment on the mixed peptides AG73/EF1. The AG73/EF1 promoted stronger and more rapid cell attachment, spreading, FAK phosphorylation that reached a maximum at 20min than that on AG73 (40min) or EF1 (90min) supplied singly. Thus, the syndecan- and α2β1 integrin-binding peptides synergistically affect cells and accelerate cell adhesion

Mechanistic target of rapamycin complex 1 signaling regulates cell proliferation, cell survival, and differentiation in regenerating zebrafish fins

[Background]:The mechanistic target of rapamycin complex1 (mTORC1) signaling pathway has been implicated in functions of multicellular processes, including cell growth and metabolism. Although recent reports showed that many signaling pathways, including Activin, Bmp, Fgf, sonic hedgehog, Insulin-like growth factor (IGF), Notch, retinoic acid, and Wnt, are implicated in non-mammalian vertebrate regeneration, also known as epimorphic regeneration, mTORC1 function remains unknown. [Results]:To investigate the role of mTORC1 signaling pathway in zebrafish caudal fin, we examined the activation and function of mTORC1 signaling using an antibody against phosphorylated S6 kinase and a specific inhibitor, rapamycin. mTORC1 signaling is activated in proliferative cells of intra-ray and wound epidermal cells before blastema formation, as well as in proliferative blastema cells, wound epidermal cells, and osteoblasts during regenerative outgrowth. Before blastema formation, proliferation of intra-ray and wound epidermal cells is suppressed, but cell death is not affected by mTORC1 signaling inhibition with rapamycin. Moreover, rapamycin treatment inhibits blastema and wound epidermal cell proliferation and survival during blastema formation and regenerative outgrowth, as well as osteoblast proliferation and differentiation during regenerative outgrowth. We further determined that mTORC1 signaling is regulated through IGF-1 receptor/phosphatidylinositol-3 kinase and Wnt pathways during fin regeneration. [Conclusion]:Taken together, our findings reveal that mTORC1 signaling regulates proliferation, survival, and differentiation of intra-ray cells, wound epidermis, blastema cells, and/or osteoblasts in various fin regeneration stages downstream of IGF and Wnt signaling pathways.This study was supported by grants from Grant-in-Aid for Scientific Research from the JSPS (KAKENHI 23616002) to Y.K., and from Hiroshima University Alumni Association Research Grant & Hiroshima University Support Foundation Research and Grant-in-Aid for Scientific Research from the JSPS (KAKENHI 26 · 6771) to K.H

Design and synthesis of amidine-type peptide bond isosteres: application of nitrile oxide derivatives as active ester equivalents in peptide and peptidomimetics synthesis.

Amidine-type peptide bond isosteres were designed based on the substitution of the peptide bond carbonyl (C=O) group with an imino (C=NH) group. The positively-charged property of the isosteric part resembles a reduced amide-type peptidomimetic. The peptidyl amidine units were synthesized by the reduction of a key amidoxime (N-hydroxyamidine) precursor, which was prepared from nitrile oxide components as an aminoacyl or peptidyl equivalent. This nitrile oxide-mediated C-N bond formation was also used for peptide macrocyclization, in which the amidoxime group was converted to peptide bonds under mild acidic conditions. Syntheses of the cyclic RGD peptide and a peptidomimetic using both approaches, and their inhibitory activity against integrin-mediated cell attachment, are presented

Dependency-directed Control of Text Generation Using Functional Unification Grammar

In text generation, various kinds of choices need to be decided. In conventional frameworks, which we call one-path generation frameworks , those decisions are made in an order carefully designed in advance. In general, however, since choices depend on one another, it is difficult to make optimal decisions in such frameworks. Our approach to this issue is to introduce the revision process into the overall generation process. In our framework, revision of output texts is realized as dependency-directed backtracking (DDB). As well as Justification-based Truth Maintenance System (JTMS), we maintain dependencies among choices in a dependency network. In this paper, we propose an efficient implementation of DDB for text generation using functional unication grammar (FUG). We use bindings of logical variables in Prolog and destructive argument substitutions to decrease the overhead of handling a dependency network. This paper describes the algorithm in detail and shows the results of preliminary..

Text Revision: A Model and Its Implementation

To generate good text, many kinds of decisions should be made. Many researchers have spent much time searching for the architecture that would determine a proper order for these decisions. However, even if such an architecture is found, there are still certain kinds of problems that are difficult to consider during the generation process. Those problems can be more easily detected and solved by introducing a revision process after generation. In this paper, we argue the importance of text revision with respect to natural language generation, and propose a computational model of text revision. We also discuss its implementation issues and describe an experimental Japanese text generation system, weiveR. 1 Introduction During the course of text generation, many kinds of decisions should be made. These decisions are generally classified into two categories: decisions on what-to-say, that is, topic selection and topic organization, and decisions on how-to-say, that is, decisions on gramma..

Selective sampling of effective example sentence sets for word sense disambiguation

This paper proposes an efficient example selection method for example-based word sense disambiguation systems. To construct a practical size database, a considerable overhead for manual sense disambiguation is required. Our method is characterized by the reliance on the notion of the training utility: the degree to which each example is informative for future example selection when used for the training of the system. The system progressively collects examples by selecting those with greatest utility. The paper reports the effectivity of our method through experiments on about one thousand sentences. Compared to ex-periments with random example selection, our method reduced the overhead without the degeneration of the performance of the system.