321 research outputs found
THE ONE WITH NO AUTHOR: EXPLORATION OF TEXT GENERATION MODELS FOR FRIENDS
No full text(Statement of Responsibility) by Sunwoo Ha(Thesis) Thesis (B.A.) -- New College of Florida, 2019RESTRICTED TO NCF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE(Bibliography) Includes bibliographical references.This bibliographic record is available under the Creative Commons CC0 public domain dedication. The New College of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.Faculty Sponsor: Lepinski, Matthe
The Nomad of the Naked Body: The Trans-corporeal Ecopoetics of Sunwoo Kim
No full textThe material turn in the environmental humanities drastically changes our perception of who we are and challenges our attitude toward nature. In this article, the author argues that there is a critical connection between the works of Sunwoo Kim, one of the most prominent ecofeminist poets of Korea, and the trans-corporeal poetics of new materialist feminism. By resuscitating “dead” nature and recognizing the agency of things in the world, Sunwoo Kim deconstructs humanity’s prestigious position of all-powerful subjects and repositions them as equal actors with other nonhuman beings. Trans-corporeal poetics allows her to combine the two most conspicuous trends of her poetry: her feminist poetics and her ecological poetics. Owing to her new recognition of our essential corporeality, Kim rescues the female body from the patriarchal society’s debasement and brings it back to its original status. The meaning of her trans-corporeal body is most apparent in her poems on eating, since eating shares matter across corporeal boundaries. Because foodways are a major contributor toward climate change, Kim’s articulation of the trans-corporeal nature of food and her insistence on the mindful eating deserves our full attention, if we are to halt our mad rush into ecological disaster
A joint experimental and theoretical determination of the structures of oxidized and reduced molecules
No full textIn a joint study involving electrochemical experiments and density functional calculations, we determined the oxidized and reduced structures of ethylene carbonate (EC), vinylene carbonate (VC), N-methyl-ε-caprolactam (Me-CL), and N-acetyl-ε-caprolactam (Ac-CL). This study reveals that the four molecules maintain their ring structures under the one-electron oxidation condition. Me-CL and Ac-CL have linear chain forms, whereas EC and VC still have ring-structures under the one-electron reduction condition. We suggest that such a collaborative study, including both experimentation and theory, is a simple and practical method for determining the structures of oxidized and reduced molecules. © 2012 Elsevier B.V. All rights reserved.
Classification of Edge-dependent Labels of Nodes in Hypergraphs
No full textA hypergraph is a data structure composed of nodes and hyperedges, where each hyperedge is an any-sized subset of nodes. Due to the flexibility in hyperedge size, hypergraphs represent group interactions (e.g., co-authorship by more than two authors) more naturally and accurately than ordinary graphs. Interestingly, many real-world systems modeled as hypergraphs contain edge-dependent node labels, i.e., node labels that vary depending on hyperedges. For example, on co-authorship datasets, the same author (i.e., a node) can be the primary author in a paper (i.e., a hyperedge) but the corresponding author in another paper (i.e., another hyperedge). In this work, we introduce a classification of edge-dependent node labels as a new problem. This problem can be used as a benchmark task for hypergraph neural networks, which recently have attracted great attention, and also the usefulness of edge-dependent node labels has been verified in various applications. To tackle this problem, we propose WHATsNet, a novel hypergraph neural network that represents the same node differently depending on the hyperedges it participates in by reflecting its varying importance in the hyperedges. To this end, WHATsNet models the relations between nodes within each hyperedge, using their relative centrality as positional encodings. In our experiments, we demonstrate that WHATsNet significantly and consistently outperforms ten competitors on six real-world hypergraphs, and we also show successful applications of WHATsNet to (a) ranking aggregation, (b) node clustering, and (c) product return prediction
Hydrogen Peroxide Synthesis via Enhanced Two-Electron Oxygen Reduction Pathway on Carbon-Coated Pt Surface
No full textContinuous on-site electrochemical production of hydrogen peroxide (H2O2) can provide an attractive alternative to the present anthraquinone-based H2O2 production technology. A major challenge in the electrocatalyst design for H2O2 production is that O2 adsorption on the Pt surface thermodynamically favors “side-on” configuration over “end-on” configuration, which leads to a dissociation of O–O bond via dominant 4-electron pathway. This prefers H2O production rather than H2O2 production during the electrochemical oxygen reduction reaction (ORR). In the present work, we demonstrate that controlled coating of Pt catalysts with amorphous carbon layers can induce selective end-on adsorption of O2 on the Pt surface by eliminating accessible Pt ensemble sites, which allows significantly enhanced H2O2 production selectivity in the ORR. Experimental results and theoretical modeling reveal that 4-electron pathway is strongly suppressed in the course of ORR due to a thermodynamically unfavored end-on adsorption of O2 (the first electron transfer step) with 0.54 V overpotential. As a result, the carbon-coated Pt catalysts show an onset potential of ∼0.7 V for ORR and remarkably enhanced H2O2 selectivity up to 41%. Notably, the produced H2O2 cannot access the Pt surface due to the steric hindrance of the coated carbon layers, and thus no significant H2O2 decomposition via disproportionation/reduction reactions is observed. Furthermore, the catalyst shows superior stability without considerable performance degradation because the amorphous carbon layers protect Pt catalysts against the leaching and ripening in acidic operating conditions
Alternator Torque Model Based on Equivalent Circuit of Synchronous Generator for Electric Power Management
No full textThis paper presents an alternator model suitable for electric power management research. The proposed model estimates the alternator driving torque under various driving conditions, such as engine speed, output current, and generation voltage. The base equations of the proposed model are derived from the equivalent circuit and the phasor diagram of the field-wound-type synchronous generator. Model parameters that affect power conversion efficiency were defined and identified through open and short load tests on a bench. Validation tests were also performed to evaluate model accuracy under several representative driving conditions. Through a case study, we show that the proposed model is the effective way to research power management.This work was supported in part by the Ministry of Knowledge Economy, Korea, through the Energy Resource R&D Program under Grant 2006ETR11P091C; by the National Research Foundation of Korea funded by the Korean government under Grant 2011-0017495; and by the Ministry of Knowledge Economy through the Industrial Strategy Technology Development Program under Grant 10039673 and Grant 10042633. The review of this paper was coordinated by Dr. C. C. Mi. (Corresponding author: M. Sunwoo.
Supplementary Tables -Supplemental material for Procedural and clinical outcomes of endovascular recanalization therapy in patients with cancer-related stroke
No full textSupplemental material, Supplementary Tables for Procedural and clinical outcomes of endovascular recanalization therapy in patients with cancer-related stroke by Seunguk Jung, Cheolkyu Jung, Jae Hyoung Kim, Byung Se Choi, Yun Jung Bae, Leonard Sunwoo, Ho Geol Woo, Jun Young Chang, Beom Joon Kim, Moon-Ku Han and Hee-Joon Bae in Interventional Neuroradiology</p
Building an optimal predictive model for imputing tissue-specific gene expression by combining genotype and whole-blood transcriptome data
No full textAccurate imputation of tissue-specific gene expression can be a powerful tool for understanding the biological mechanisms underlying human complex traits. Existing imputation methods can be grouped into two categories according to the types of predictors used. The first category uses genotype data, while the second category uses whole-blood expression data. Both data types can be easily collected from blood, avoiding invasive tissue biopsies. In this study, we attempted to build an optimal predictive model for imputing tissue-specific gene expression by combining the genotype and whole-blood expression data. We first evaluated the imputation performance of each standalone model (using genotype data [GEN model] and using whole-blood expression data [WBE model]) using their respective data types across 47 human tissues. The WBE model outperformed the GEN model in most tissues by a large gain. Then, we developed several combined models that leverage both types of predictors to further improve imputation performance. We tried various strategies, including utilizing a merged dataset of the two data types (MERGED models) and integrating the imputation outcomes of the two standalone models (inverse variance-weighted [IVW] models). We found that one of the MERGED models noticeably outperformed the standalone models. This model involved a fixed ratio between the two regularization penalty factors for the two predictor types so that the contribution of the whole-blood transcriptome is upweighted compared with the genotype. Our study suggests that one can improve the imputation of tissue-specific gene expression by combining the genotype and whole-blood expression, but the improvement can be largely dependent on the combination strategy chosen.Y
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