316 research outputs found

    Structural Stability of Lexical Semantic Spaces: Nouns in Chinese and French

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    Many studies in the neurosciences have dealt with the semantic processing of words or categories, but few have looked into the semantic organization of the lexicon thought as a system. The present study was designed to try to move towards this goal, using both electrophysiological and corpus-based data, and to compare two languages from different families: French and Mandarin Chinese. We conducted an EEG-based semantic-decision experiment using 240 words from eight categories (clothing, parts of a house, tools, vehicles, fruits/vegetables, animals, body parts, and people) as the material. A data-analysis method (correspondence analysis) commonly used in computational linguistics was applied to the electrophysiological signals. The present cross-language comparison indicated stability for the following aspects of the languages' lexical semantic organizations: (1) the living/nonliving distinction, which showed up as a main factor for both languages; (2) greater dispersion of the living categories as compared to the nonliving ones; (3) prototypicality of the \emph{animals} category within the living categories, and with respect to the living/nonliving distinction; and (4) the existence of a person-centered reference gradient. Our electrophysiological analysis indicated stability of the networks at play in each of these processes. Stability was also observed in the data taken from word usage in the languages (synonyms and associated words obtained from textual corpora).Comment: 17 pages, 4 figure

    Exact Asymptotic Stability Analysis and Region-of-Attraction Estimation for Nonlinear Systems

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    We address the problem of asymptotic stability and region-of-attraction analysis of nonlinear dynamical systems. A hybrid symbolic-numeric method is presented to compute exact Lyapunov functions and exact estimates of regions of attraction of nonlinear systems efficiently. A numerical Lyapunov function and an estimate of region of attraction can be obtained by solving an (bilinear) SOS programming via BMI solver, then the modified Newton refinement and rational vector recovery techniques are applied to obtain exact Lyapunov functions and verified estimates of regions of attraction with rational coefficients. Experiments on some benchmarks are given to illustrate the efficiency of our algorithm

    Bridging multiscale interfaces for developing ionically conductive high-voltage iron sulfate-containing sodium-based battery positive electrodes

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    Non-aqueous sodium-ion batteries (SiBs) are a viable electrochemical energy storage system for grid storage. However, the practical development of SiBs is hindered mainly by the sluggish kinetics and interfacial instability of positive-electrode active materials, such as polyanion-type iron-based sulfates, at high voltage. Here, to circumvent these issues, we proposed the multiscale interface engineering of Na2.26_{2.26}Fe1.87_{1.87}(SO4_4)3_3, where bulk heterostructure and exposed crystal plane were tuned to improve the Na-ion storage performance. Physicochemical characterizations and theoretical calculations suggested that the heterostructure of Na6_6Fe(SO4_4)4_4 phase facilitated ionic kinetics by densifying Na-ion migration channels and lowering energy barriers. The (11-2) plane of Na2.26_{2.26}Fe1.87_{1.87}(SO4_4)3_3 promoted the adsorption of the electrolyte solution ClO4− anions and fluoroethylene carbonate molecules, which formed an inorganic-rich Na-ion conductive interphase at the positive electrode. When tested in combination with a presodiated FeS/carbon-based negative electrode in laboratory- scale single-layer pouch cell configuration, the Na2.26_{2.26}Fe1.87_{1.87}(SO4_4)3_3-based positive electrode enables an initial discharge capacity of about 83.9 mAh g−1^{−1}, an average cell discharge voltage of 2.35 V and a specific capacity retention of around 97% after 40 cycles at 24 mA g−1^{−1} and 25 °C
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