52 research outputs found
Affective Affordance of Message Balloon Animations: An Early Exploration of AniBalloons
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
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
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Large-area epitaxial growth of curvature-stabilized ABC trilayer graphene.
The properties of van der Waals (vdW) materials often vary dramatically with the atomic stacking order between layers, but this order can be difficult to control. Trilayer graphene (TLG) stacks in either a semimetallic ABA or a semiconducting ABC configuration with a gate-tunable band gap, but the latter has only been produced by exfoliation. Here we present a chemical vapor deposition approach to TLG growth that yields greatly enhanced fraction and size of ABC domains. The key insight is that substrate curvature can stabilize ABC domains. Controllable ABC yields ~59% were achieved by tailoring substrate curvature levels. ABC fractions remained high after transfer to device substrates, as confirmed by transport measurements revealing the expected tunable ABC band gap. Substrate topography engineering provides a path to large-scale synthesis of epitaxial ABC-TLG and other vdW materials
Integrative genomics analysis of genes with biallelic loss and its relation to the expression of mRNA and micro-RNA in esophageal squamous cell carcinoma
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Joint analysis of three genome-wide association studies of esophageal squamous cell carcinoma in Chinese populations
We conducted a joint (pooled) analysis of three genome-wide association studies (GWAS) 1-3 of esophageal squamous cell carcinoma (ESCC) in ethnic Chinese (5,337 ESCC cases and 5,787 controls) with 9,654 ESCC cases and 10,058 controls for follow-up. In a logistic regression model adjusted for age, sex, study, and two eigenvectors, two new loci achieved genome-wide significance, marked by rs7447927 at 5q31.2 (per-allele odds ratio (OR) = 0.85, 95% CI 0.82-0.88; P=7.72x10−20) and rs1642764 at 17p13.1 (per-allele OR= 0.88, 95% CI 0.85-0.91; P=3.10x10−13). rs7447927 is a synonymous single nucleotide polymorphism (SNP) in TMEM173 and rs1642764 is an intronic SNP in ATP1B2, near TP53. Furthermore, a locus in the HLA class II region at 6p21.32 (rs35597309) achieved genome-wide significance in the two populations at highest risk for ESSC (OR=1.33, 95% CI 1.22-1.46; P=1.99x10−10). Our joint analysis identified new ESCC susceptibility loci overall as well as a new locus unique to the ESCC high risk Taihang Mountain region
Rumen Fermentation Characteristics Require More Time to Stabilize When Diet Shifts
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
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
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
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
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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