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Physical Review E 2020年第4期101卷 042702-042702页

作者： Jung-Shen B. Tai (戴榮身) Ivan I. Smalyukh Department of Physics University of Colorado Boulder Colorado 80309 USA Materials Science and Engineering Program Soft Materials Research Center and Department of Electrical Computer and Energy Engineering University of Colorado Boulder Colorado 80309 USA Renewable and Sustainable Energy Institute National Renewable Energy Laboratory and University of Colorado Boulder Colorado 80309 USA

Chiral condensed matter systems, such as liquid crystals and magnets, exhibit a host of spatially localized topological structures that emerge from the medium's tendency to twist and its competition with confinement and field coupling effects. We show that the strength of perpendicular surface boundary conditions can be used to control the structure and topology of solitonic and other localized field configurations. By combining numerical modeling and three-dimensional imaging of the director field, we reveal structural stability diagrams and intertransformation of twisted walls and fingers, torons, and skyrmions and their crystalline organizations upon changing boundary conditions. Our findings provide a recipe for controllably realizing skyrmions, torons, and hybrid solitonic structures possessing features of both of them, which will aid in fundamental explorations and technological uses of such topological solitons. Moreover, we discuss how other material parameters can be used to determine soliton stability and how similar principles can be systematically applied to other liquid crystal solitons and solitons in other material systems.

关键词： Skyrmions Topological defects Ferromagnetic liquid crystals Liquid crystals Solitons Topology

Colloidal Surfaces with Boundaries, Apex Boojums, and Nested Elastic Self-Assembly of Nematic Colloids

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Physical Review Letters 2016年第27期117卷 277801-277801页

作者： Sungoh Park Qingkun Liu Ivan I. Smalyukh Department of Physics University of Colorado Boulder Colorado 80309 USA Department of Electrical Computer and Energy Engineering Soft Materials Research Center and Materials Science and Engineering Program University of Colorado Boulder Colorado 80309 USA Renewable and Sustainable Energy Institute University of Colorado and National Renewable Energy Laboratory Boulder Colorado 80309 USA

Self-assembly of colloidal particles is poised to become a powerful composite material fabrication technique, but remains challenged by a limited control over the ensuing structures. We develop a new breed of nematic colloids that are physical analogs of a mathematical surface with boundary, interacting with the molecular alignment field without inducing defects when flat. However, made from a thin nanofoil, they can be shaped to prompt formation of self-compensating defects that drive preprogramed elastic interactions mediated by the nematic host. To show this, we wrap the nanofoil on all triangular side faces of a pyramid, except its square base. The ensuing pyramidal cones induce point defects with fractional hedgehog charges of opposite signs, spontaneously align with respect to the far-field director to form elastic dipoles and nested assemblies with tunable spacing. Nanofoils shaped into octahedrons interact as elastic quadrupoles. Our findings may drive realization of low-symmetry colloidal phases.

关键词： Defects Point defects Self-assembly Colloids Liquid crystals Nematic liquid crystals

Hopf Solitons in Helical and Conical Backgrounds of Chiral Magnetic Solids

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Physical Review Letters 2020年第5期125卷 057201-057201页

作者： Robert Voinescu Jung-Shen B. Tai (戴榮身) Ivan I. Smalyukh Department of Physics University of Colorado Boulder Colorado 80309 USA Materials Science and Engineering Program Soft Materials Research Center and Department of Electrical Computer and Energy Engineering University of Colorado Boulder Colorado 80309 USA Renewable and Sustainable Energy Institute National Renewable Energy Laboratory and University of Colorado Boulder Colorado 80309 USA

Three-dimensional topological solitons attract a great deal of interest in fields ranging from particle physics to cosmology, but remain experimentally elusive in solid-state magnets. Here we numerically predict magnetic heliknotons, an embodiment of such nonzero-Hopf-index solitons localized in all spatial dimensions while embedded in a helical or conical background of chiral magnets. We describe conditions under which heliknotons emerge as metastable or ground-state localized nonsingular structures with fascinating knots of magnetization field in widely studied materials. We demonstrate magnetic control of three-dimensional spatial positions of such solitons, as well as show how they interact to form moleculelike clusters and possibly even crystalline phases comprising three-dimensional lattices of such solitons with both orientational and positional order. Finally, we discuss both fundamental importance and potential technological utility of magnetic heliknotons.

关键词： Dzyaloshinskii-Moriya interaction Skyrmions Chiral magnets Micromagnetic modeling Topology

Learning universal representations from word to sentence

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arXiv 2020年

作者： Li, Yian Zhao, Hai Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University Shanghai China MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University China

Despite the well-developed cut-edge representation learning for language, most language representation models usually focus on specific level of linguistic unit, which cause great inconvenience when being confronted with handling multiple layers of linguistic objects in a unified way. Thus this work introduces and explores the universal representation learning, i.e., embeddings of different levels of linguistic unit in a uniform vector space through a task-independent evaluation. We present our approach of constructing analogy datasets in terms of words, phrases and sentences and experiment with multiple representation models to examine geometric properties of the learned vector space. Then we empirically verify that well pre-trained Transformer models incorporated with appropriate training settings may effectively yield universal representation. Especially, our implementation of fine-tuning ALBERT on NLI and PPDB datasets achieves the highest accuracy on analogy tasks in different language levels. Further experiments on the insurance FAQ task show effectiveness of universal representation models in real-world applications. Copyright © 2020, The Authors. All rights reserved.

关键词： Linguistics

Improving Out-of-Distribution Generalization in Graphs via Hierarchical Semantic Environments

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arXiv 2024年

作者： Piao, Yinhua Lee, Sangseon Lu, Yijingxiu Kim, Sun Department of Computer Science and Engineering Seoul National University Korea Republic of Institute of Computer Technology Seoul National University Korea Republic of AIGENDRUG Co. Ltd. Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of

Out-of-distribution (OOD) generalization in the graph domain is challenging due to complex distribution shifts and a lack of environmental contexts. Recent methods attempt to enhance graph OOD generalization by generating flat environments. However, such flat environments come with inherent limitations to capture more complex data distributions. Considering the DrugOOD dataset, which contains diverse training environments (e.g., scaffold, size, etc.), flat contexts cannot sufficiently address its high heterogeneity. Thus, a new challenge is posed to generate more semantically enriched environments to enhance graph invariant learning for handling distribution shifts. In this paper, we propose a novel approach to generate hierarchical semantic environments for each graph. Firstly, given an input graph, we explicitly extract variant subgraphs from the input graph to generate proxy predictions on local environments. Then, stochastic attention mechanisms are employed to re-extract the subgraphs for regenerating global environments in a hierarchical manner. In addition, we introduce a new learning objective that guides our model to learn the diversity of environments within the same hierarchy while maintaining consistency across different hierarchies. This approach enables our model to consider the relationships between environments and facilitates robust graph invariant learning. Extensive experiments on real-world graph data have demonstrated the effectiveness of our framework. Particularly, in the challenging dataset DrugOOD, our method achieves up to 1.29% and 2.83% improvement over the best baselines on IC50 and EC50 prediction tasks, respectively. © 2024, CC BY.

关键词： Semantics

computer simulation of heart-pacemaker interaction

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Journal of Electrocardiology 1990年第SUPPL.期23卷 156-156页

作者： Greenhut, Saul E. MacDonald, Robert S. Jenkins, Janice M. Department of Electrical Engineering Computer Science The University of Michigan Ann Arbor MI United States the Bioengineering Program The University of Michigan Ann Arbor MI United States

Robust Saliency-Aware Distillation for Few-shot Fine-grained Visual Recognition

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arXiv 2023年

作者： Liu, Haiqi Chen, C.L. Philip Gong, Xinrong Zhang, Tong The School of Computer Science and Engineering South China University of Technology Guangzhou510006 China The Brain and Affective Cognitive Research Center Pazhou Lab. Guangzhou510335 China The Engineering Research Center The Ministry of Education on Health Intelligent Perception and Paralleled Digital-Human Guangzhou510006 China

Recognizing novel sub-categories with scarce samples is an essential and challenging research topic in computer vision. Existing literature addresses this challenge by employing local-based representation approaches, which may not sufficiently facilitate meaningful object-specific semantic understanding, leading to a reliance on apparent background correlations. Moreover, they primarily rely on high-dimensional local descriptors to construct complex embedding space, potentially limiting the generalization. To address the above challenges, this article proposes a novel model, Robust Saliency-aware Distillation (RSaD), for few-shot fine-grained visual recognition. RSaD introduces additional saliency-aware supervision via saliency detection to guide the model toward focusing on the intrinsic discriminative regions. Specifically, RSaD utilizes the saliency detection model to emphasize the critical regions of each sub-category, providing additional object-specific information for fine-grained prediction. RSaD transfers such information with two symmetric branches in a mutual learning paradigm. Furthermore, RSaD exploits inter-regional relationships to enhance the informativeness of the representation and subsequently summarize the highlighted details into contextual embeddings to facilitate the effective transfer, enabling quick generalization to novel sub-categories. The proposed approach is empirically evaluated on three widely used benchmarks, demonstrating its superior performance. Copyright © 2023, The Authors. All rights reserved.

关键词： Distillation

Load Manipulation by a Triangular Formation of Quadrotors

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Load Manipulation by a Triangular Formation of Quadrotors

International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Valentim Ernandes Neto Alexandre Santos Brandão Mário Sarcinelli-Filho Graduate Program on Electrical Engineering Federal University of Espírito Santo Vitória ES Brazil Núcleo de Especialização em Robótica Department of Electrical Engineering and Graduate Program on Computer Science Federal University of Viçosa Viçosa MG Brazil

ISBN: (数字)9781728142784

ISBN: (纸本)9781728142791

This work discusses a trajectory tracking task accomplished by a group of three Bebop 2 quadrotors working cooperatively to transport a load. Such unmanned aerial vehicles (UAVs) are considered as a triangular formation, and the load, a triangle-shaped structure, is attached to them through massless flexible cables. The reason to use three quadrotors is the gain in terms of the payload capability and the stability of the load, since it is attached to three vehicles, staying vertically aligned with the center of mass of the triangle correspondent to the formation. A formation controller, actually a kinematic controller applied to a virtual massless robot correspondent to the center of mass of the triangle, is adopted, which generates reference velocities for the three UAVs, whose movement generates the movement and reshaping of the triangular formation. Then, individual dynamic compensators are adopted for each UAV, whose input is the reference velocity delivered by the formation controller. Finally, experimental results are discussed, which validate the proposal.

关键词： Vehicle dynamics Aerodynamics Atmospheric modeling Aircraft Robot kinematics Mathematical model

A Wearable Device Network to Track Animal Behavior and Relationships in the Wild

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A Wearable Device Network to Track Animal Behavior and Relat...

IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)

作者： Luis Camal Anup Kirtane Teresa Blanco Roberto Casas Federico Rossano Baris Aksanli Electrical and Computer Engineering San Diego State University San Diego CA USA GeoSpatiumLab S.L. Aragon Institute of Engineering Research Zaragoza Spain Aragon Institute of Engineering Research University of Zaragoza Zaragoza Spain Cognitive Science University of California San Diego San Diego CA USA

ISBN: (纸本)9781728138862

The advancements in sensor technology have made it possible to design wearable devices specifically designed for animals. These wearable devices can be used for locating individual animals, monitor their status, and track their trajectories in the wild. Some animal groups (such as chimpanzees) exhibit complex group behavior and these group dynamics play an important role in the physical and mental health of the animals. Scientists have traditionally been monitoring group dynamics manually in the wild. This requires extensive field trips, costing a lot of time and money. This calls for using the recent developments in technology, such as smart wearable devices for this purpose. However, lack of infrastructure support (limited connectivity, limited power, etc.) in the wilderness makes this a tedious task. In this work-in-progress paper, we present our technological approach and how we address the issues of wilderness to study animal behavior. We demonstrate how we build a network of lightweight wearable devices, and how the digital output of these devices can be used to analyze animal relationship. We show an initial, exploratory experiment, outlining the capabilities of the devices and technologies used in terms of communication efficiency, and the potential of the devices that can be used in the wilderness. Our initial results show that up to 90% of the proximity-based interactions can be captured.

关键词： behavioural sciences computerised monitoring wearable computers wireless sensor networks zoology Behavioral sciences computerized monitoring Wearable computers Zoology animal behaviour wilderness Wearable group dynamics Wireless sensor networks field trips Technology Development Animals

Do humans and Convolutional Neural Networks attend to similar areas during scene classification: Effects of task and image type

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arXiv 2023年

作者： Müller, Romy Dürschmidt, Marcel Ullrich, Julian Knoll, Carsten Weber, Sascha Seitz, Steffen Faculty of Psychology Chair of Engineering Psychology and Applied Cognitive Research TUD Dresden University of Technology Dresden Germany Faculty of Electrical and Computer Engineering Chair of Fundamentals of Electrical Engineering TUD Dresden University of Technology Dresden Germany Faculty of Mathematics and Natural Sciences Department of Computer Science Machine Learning Group Heinrich-Heine-Universität Düsseldorf Düsseldorf Germany

Deep Learning models like Convolutional Neural Networks (CNN) are powerful image classifiers, but what factors determine whether they attend to similar image areas as humans do? While previous studies have focused on technological factors, little is known about the role of factors that affect human attention. In the present study, we investigated how the tasks used to elicit human attention maps interact with image characteristics in modulating the similarity between humans and CNN. We varied the intentionality of human tasks, ranging from spontaneous gaze during categorization over intentional gaze-pointing up to manual area selection. Moreover, we varied the type of image to be categorized, using either singular, salient objects, indoor scenes consisting of object arrangements, or landscapes without distinct objects defining the category. The human attention maps generated in this way were compared to the CNN attention maps revealed by explainable artificial intelligence (Grad-CAM). The influence of human tasks strongly depended on image type: For objects, human manual selection produced maps that were most similar to CNN, while the specific eye movement task has little impact. For indoor scenes, spontaneous gaze produced the least similarity, while for landscapes, similarity was equally low across all human tasks. To better understand these results, we also compared the different human attention maps to each other. Our results highlight the importance of taking human factors into account when comparing the attention of humans and CNN. © 2023, CC BY.

关键词： Eye movements