52 research outputs found

    Affective Affordance of Message Balloon Animations: An Early Exploration of AniBalloons

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    We introduce the preliminary exploration of AniBalloons, a novel form of chat balloon animations aimed at enriching nonverbal affective expression in text-based communications. AniBalloons were designed using extracted motion patterns from affective animations and mapped to six commonly communicated emotions. An evaluation study with 40 participants assessed their effectiveness in conveying intended emotions and their perceived emotional properties. The results showed that 80% of the animations effectively conveyed the intended emotions. AniBalloons covered a broad range of emotional parameters, comparable to frequently used emojis, offering potential for a wide array of affective expressions in daily communication. The findings suggest AniBalloons' promise for enhancing emotional expressiveness in text-based communication and provide early insights for future affective design.Comment: Accepted by CSCW 2023 poste

    Time-delay stability switching boundary determination for DC microgrid clusters with the distributed control framework

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    In a DC microgrid cluster, distributed DC microgrids are integrated to manage diverse and distributed energy resources. Without the reliance on a management center, the distributed control framework is capable of the cluster deployment by only adjacent collaborations. However, the communication among microgrids and the formation of dispatch signals inevitably lead to time delays, which might cause the system disorder and multiple-delay couplings. Considering these unstable effects, the lack of time-delay study challenges the cluster stability and burdens the energy application. The key contributions of this paper are the definition and detection of the time-delay stability switching boundary for the DC microgrid cluster with the distributed control framework, which reveals time delays switching the system stability and proves the delay-induced oscillation. Through the established time-delay model and the proposed method based on the cluster treatment of characteristic roots, the explicit time-delay stability switching boundary is detected in the delay space, which forms a determination flow of five stages: (1) system initialization: according to the cluster parameter values, the established time-delay model is initialized; (2) space transformation: applying the space mapping and the rationalization, the Sylvester resultant is constructed in the spectral delay space; (3) spectral boundary sketch: in uniformly divided blocks, spectral boundaries are found from the resultant; (4) crossing root calculation: with the spectral boundaries, crossing roots are calculated solving the characteristic equation; (5) boundary determination: back-mapping the spectral boundaries with the crossing roots, the overall boundary is presented. Comprehensive case studies are performed to study the time-delay stability switching boundary and to validate the proposed approach. The boundary existence and feature demonstrate the time-delay effect. Furthermore, the classified stable areas are revealed as well as the relevant strategies for the stability enhancement. © 20182015AA050403; U1766210, NSFC, National Natural Science Foundation of China; 51377117, NSFC, National Natural Science Foundation of ChinaNational High-tech R&D Program of China [2015AA050403]; National Natural Science Foundation of China [U1766210, 51377117

    Rumen Fermentation Characteristics Require More Time to Stabilize When Diet Shifts

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    This study was conducted to explore the proper time required to achieve stabilization in digestibility, serum metabolism, and rumen fermentation characteristics when different diets shift, thus providing decision-making of practical sampling frequency for basal nutritional research. For these purposes, 12 Holstein steers (body weight 467 ± 34 kg, age 14 ± 0.5 months) were equally assigned to two dietary treatments: high-density (metabolizable energy (ME) = 2.53 Mcal/kg and crude protein (CP) = 119 g/kg; both ME and CP were expressed on a dry matter basis) or low-density (ME = 2.35 Mcal/kg and CP = 105 g/kg). The samples of feces, serum, and rumen contents were collected with a 30-day interval. All data involved in this study were analyzed using the repeated measures in mixed model of SPSS. Results showed that nutrient apparent digestibility and serum metabolic parameters were stable across each monthly collection, while most rumen fermentation characteristics, namely concentrations of acetate, propionate, isobutyrate, and valerate, were affected by the interaction effects between collection period and dietary density. These findings indicate that rumen fermentation characteristics require more time to stabilize when diet shifts. It is recommended to collect ruminal digesta monthly to evaluate rumen fermentation characteristics, while unnecessary to sample monthly for digestion trials and blood tests in the long-term fattening of Holstein steers. This study may provide insights into exploring the associations between detected parameters and stabilization time, and between diet type and stabilization time when diet shifts

    Leveraging Multi-Modal Information for Cross-Lingual Entity Matching across Knowledge Graphs

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    In recent years, the scale of knowledge graphs and the number of entities have grown rapidly. Entity matching across different knowledge graphs has become an urgent problem to be solved for knowledge fusion. With the importance of entity matching being increasingly evident, the use of representation learning technologies to find matched entities has attracted extensive attention due to the computability of vector representations. However, existing studies on representation learning technologies cannot make full use of knowledge graph relevant multi-modal information. In this paper, we propose a new cross-lingual entity matching method (called CLEM) with knowledge graph representation learning on rich multi-modal information. The core is the multi-view intact space learning method to integrate embeddings of multi-modal information for matching entities. Experimental results on cross-lingual datasets show the superiority and competitiveness of our proposed method

    Leveraging Multi-Modal Information for Cross-Lingual Entity Matching across Knowledge Graphs

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    In recent years, the scale of knowledge graphs and the number of entities have grown rapidly. Entity matching across different knowledge graphs has become an urgent problem to be solved for knowledge fusion. With the importance of entity matching being increasingly evident, the use of representation learning technologies to find matched entities has attracted extensive attention due to the computability of vector representations. However, existing studies on representation learning technologies cannot make full use of knowledge graph relevant multi-modal information. In this paper, we propose a new cross-lingual entity matching method (called CLEM) with knowledge graph representation learning on rich multi-modal information. The core is the multi-view intact space learning method to integrate embeddings of multi-modal information for matching entities. Experimental results on cross-lingual datasets show the superiority and competitiveness of our proposed method

    Carbon nitride transparent counter electrode prepared by magnetron sputtering for a dye-sensitized solar cell

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    Carbon nitride (CNx) films supported on fluorine-doped tin oxide (FTO) glass are prepared by radio frequency magnetron sputtering, in which the film thicknesses are 90â100 nm, and the element components in the CNx films are in the range of x = 0.15â0.25. The as-prepared CNx is for the first time used as counter electrode for dye-sensitized solar cells (DSSCs), and show a preparation-temperature dependent electrochemical performance. X-ray photoelectron spectroscopy (XPS) demonstrates that there is a higher proportion of sp2 CîC and sp3 Cî¸N hybridized bonds in CNx-500 (the sample treated at 500 °C) than in CNx-RT (the sample without a heat treatment). It is proposed that the sp2 CîC and sp3 CâN hybridized bonds in the CNx films are helpful for improving the electrocatalytic activities in DSSCs. Meanwhile, Raman spectra also prove that CNx-500 has a relatively high graphitization level that means an increasing electrical conductivity. This further explains why the sample after the heat treatment has a higher electrochemical performance in DSSCs. In addition, the as-prepared CNx counter electrodes have a good light transmittance in the visible light region. The results are meaningful for developing low-cost metal-free transparent counter electrodes for DSSCs. Keywords: Solar cells, Counter electrodes, Carbon nitride, Electrocatalysis, Magnetron sputterin

    Digestive Ability, Physiological Characteristics, and Rumen Bacterial Community of Holstein Finishing Steers in Response to Three Nutrient Density Diets as Fattening Phases Advanced

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    The aim of this study is to track the dynamic alterations in nutrient intake and digestion, rumen fermentation and plasma metabolic characteristics, and rumen bacterial community of Holstein finishing steers in response to three nutrient density diets as fattening phases advanced. A total of eighteen Holstein steers were randomly allocated into three nutrient density groups and steers in each group were fed under a three-phase fattening strategy, with nutrient density increased in each group when fattening phase advanced. Results showed that both fattening phase and dietary nutrient density significantly influenced the nutrient digestion, most of the rumen fermentation parameters, and part of bacteria at phylum and genus levels. Individually, dietary nutrient density affected the concentrations of plasma alanine aminotransferase and urea N, bacterial richness and evenness. All determined nutrient intake and plasma biochemical parameters, except for alanine aminotransferase and triglyceride, differed among fattening phases. Spearman correlation analysis revealed strong correlations between fiber intake and bacterial richness and evenness, rumen fermentation characteristics and certain bacteria. Moreover, Patescibacteria abundance was positively correlated with ambient temperature and plasma total protein. These results indicate that rumen fermentation and nutrient digestion were influenced by both dietary nutrient density and fattening phase, and these influences were regulated by certain rumen bacterial community and ruminal bacteria may be affected simultaneously by ambient temperature. This study may provide insights into diet optimization and potentially adaptive mechanism of rumen bacterial community in response to fattening phases and gradually climatic change
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