378 research outputs found

    Simulation of a Solar Jet Formed from an Untwisting Flux Rope Interacting with a Null Point

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    Coronal jets are eruptions identified by a collimated, sometimes twisted spire. They are small-scale energetic events compared with flares. Using multi-wavelength observations from the Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA) and a magnetogram from Hinode/Spectro-Polarimeter (Hinode/SP), we study the formation and evolution of a jet occurring on 2019 March 22 in the active region NOAA 12736. A zero-β\beta magnetohydrodynamic (MHD) simulation is conducted to probe the initiation mechanisms and appearance of helical motion during this jet event. As the simulation reveals, there are two pairs of field lines at the jet base, indicating two distinct magnetic structures. One structure outlines a flux rope lying low above the photosphere in the north of a bald patch region and the other structure shows a null point high in the corona in the south. The untwisting motions of the observed flux rope was recovered by adding an anomalous (artificial) resistivity in the simulation. A reconnection occurs at the bald patch in the flux rope structure, which is moving upwards and simultaneously encounters the field lines of the null point structure. The interaction of the two structures results in the jet while the twist of the flux rope is transferred to the jet by the reconnected field lines. The rotational motion of the flux rope is proposed to be an underlying trigger of this process and responsible for helical motions in the jet spire.Comment: 17pages, 9 figures. Accepted for publication in The Astrophysical Journa

    Adaptive 3D Mesh Steganography Based on Feature-Preserving Distortion

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    3D mesh steganographic algorithms based on geometric modification are vulnerable to 3D steganalyzers. In this paper, we propose a highly adaptive 3D mesh steganography based on feature-preserving distortion (FPD), which guarantees high embedding capacity while effectively resisting 3D steganalysis. Specifically, we first transform vertex coordinates into integers and derive bitplanes from them to construct the embedding domain. To better measure the mesh distortion caused by message embedding, we propose FPD based on the most effective sub-features of the state-of-the-art steganalytic feature set. By improving and minimizing FPD, we can efficiently calculate the optimal vertex-changing distribution and simultaneously preserve mesh features, such as steganalytic and geometric features, to a certain extent. By virtue of the optimal distribution, we adopt the Q-layered syndrome trellis coding (STC) for practical message embedding. However, when Q varies, calculating bit modification probability (BMP) in each layer of Q-layered will be cumbersome. Hence, we contrapuntally design a universal and automatic BMP calculation approach. Extensive experimental results demonstrate that the proposed algorithm outperforms most state-of-the-art 3D mesh steganographic algorithms in terms of resisting 3D steganalysis.Comment: IEEE TVCG major revisio

    TIFace: Improving Facial Reconstruction through Tensorial Radiance Fields and Implicit Surfaces

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    This report describes the solution that secured the first place in the "View Synthesis Challenge for Human Heads (VSCHH)" at the ICCV 2023 workshop. Given the sparse view images of human heads, the objective of this challenge is to synthesize images from novel viewpoints. Due to the complexity of textures on the face and the impact of lighting, the baseline method TensoRF yields results with significant artifacts, seriously affecting facial reconstruction. To address this issue, we propose TI-Face, which improves facial reconstruction through tensorial radiance fields (T-Face) and implicit surfaces (I-Face), respectively. Specifically, we employ an SAM-based approach to obtain the foreground mask, thereby filtering out intense lighting in the background. Additionally, we design mask-based constraints and sparsity constraints to eliminate rendering artifacts effectively. The experimental results demonstrate the effectiveness of the proposed improvements and superior performance of our method on face reconstruction. The code will be available at https://github.com/RuijieZhu94/TI-Face.Comment: 1st place solution in the View Synthesis Challenge for Human Heads (VSCHH) at the ICCV 2023 worksho

    Enhancing Text-based Knowledge Graph Completion with Zero-Shot Large Language Models: A Focus on Semantic Enhancement

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    The design and development of text-based knowledge graph completion (KGC) methods leveraging textual entity descriptions are at the forefront of research. These methods involve advanced optimization techniques such as soft prompts and contrastive learning to enhance KGC models. The effectiveness of text-based methods largely hinges on the quality and richness of the training data. Large language models (LLMs) can utilize straightforward prompts to alter text data, thereby enabling data augmentation for KGC. Nevertheless, LLMs typically demand substantial computational resources. To address these issues, we introduce a framework termed constrained prompts for KGC (CP-KGC). This CP-KGC framework designs prompts that adapt to different datasets to enhance semantic richness. Additionally, CP-KGC employs a context constraint strategy to effectively identify polysemous entities within KGC datasets. Through extensive experimentation, we have verified the effectiveness of this framework. Even after quantization, the LLM (Qwen-7B-Chat-int4) still enhances the performance of text-based KGC methods \footnote{Code and datasets are available at \href{https://github.com/sjlmg/CP-KGC}{https://github.com/sjlmg/CP-KGC}}. This study extends the performance limits of existing models and promotes further integration of KGC with LLMs.Comment: new versio

    Pedestrian Accessible Infrastructure Inventory: Assessing Zero-Shot Segmentation on Multi-Mode Geospatial Data for All Pedestrian Types

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    In this paper, a Segment Anything Model (SAM)-based pedestrian infrastructure segmentation workflow is designed and optimized, which is capable of efficiently processing multi-sourced geospatial data including LiDAR data and satellite imagery data. We used an expanded definition of pedestrian infrastructure inventory which goes beyond the traditional transportation elements to include street furniture objects that are important for accessibility but are often omitted from the traditional definition. Our contributions lie in producing the necessary knowledge to answer the following two questions. First, which data representation can facilitate zero-shot segmentation of infrastructure objects with SAM? Second, how well does the SAM-based method perform on segmenting pedestrian infrastructure objects? Our findings indicate that street view images generated from mobile LiDAR point cloud data, when paired along with satellite imagery data, can work efficiently with SAM to create a scalable pedestrian infrastructure inventory approach with immediate benefits to GIS professionals, city managers, transportation owners, and walkers, especially those with travel-limiting disabilities, such as individuals who are blind, have low vision, or experience mobility disabilities

    Design of multifunctional color routers with Kerker switching using generative adversarial networks

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    To achieve optoelectronic devices with high resolution and efficiency, there is a pressing need for optical structural units that possess an ultrasmall footprint yet exhibit strong controllability in both the frequency and spatial domains. For dielectric nanoparticles, the overlap of electric and magnetic dipole moments can scatter light completely forward or backward, which is called Kerker theory. This effect can expand to any multipoles and any directions, re-named as generalized Kerker effect, and realize controllable light manipulation at full space and full spectrum using well-designed dielectric structures. However, the complex situations of multipole couplings make it difficult to achieve structural design. Here, generative artificial intelligence (AI) is utilized to facilitate multi-objective-oriented structural design, wherein we leverage the concept of "combined spectra" that consider both spectra and direction ratios as labels. The proposed generative adversarial network (GAN) is named as DDGAN (double-discriminator GAN) which discriminates both images and spectral labels. Using trained networks, we achieve the simultaneous design for scattering color and directivities, RGB color routers, as well as narrowband light routers. Notably, all generated structures possess a footprint less than 600x600 nm indicating their potential applications in optoelectronic devices with ultrahigh resolution

    Anisodamine combined with lidocaine improves healing of myocardial ischemia reperfusion injury in rats via PI3K/Akt signaling pathway

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    Purpose: To study the effects of anisodamine (Ad) combined with lidocaine (Ldc) on myocardial ischemia-reperfusion injury (MIRI) in rats, and its correlation with PI3K/AKT signaling pathway.Methods: A total of 70 healthy rats were randomly divided into S group, M group, Ad group, Ldc group, Ad + Ldc group, Ad + Ldc + LY group, and LY group. The cardiac hemodynamic indices in each group were determined, and the area of myocardial infarction measured. Serum biochemical indices were also determined. Furthermore, the protein expressions of p-Akt, T-Akt, Bcl-2, and Bax in myocardial cells were determined by Western blotting.Results: Compared with those in M group, Ad group, Ldc group, Ad + Ldc + LY group, and LY group, cardiac hemodynamic indices significantly improved, while the area of myocardial infarction was significantly reduced (p < 0.01). Furthermore, serum malondialdehyde (MDA) concentration but the activities of CK, CK-MB, TNF-α, and IL-6 declined, while the activities of superoxide dismutase (SOD), CAT and GSH-Px rose in Ad + Ldc group (p < 0.01). In Ad + Ldc group, p-Akt, T-Akt, and Bcl-2 increased, while Bax significantly decreased. Through comparison LY294002 significantly inhibited the protective effect of Ad combined with Ldc against MIRI in rats (p < 0.01).Conclusion: Anisodamine combination with lidocaine has a protective effect against MIRI in rats via PI3K/Akt signaling pathway, thus indicating that it is a potential therapeutic strategy for the management of myocardial ischemia-reperfusion

    Cooperative Cognitive Dynamic System in UAV Swarms: Reconfigurable Mechanism and Framework

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    As the demands for immediate and effective responses increase in both civilian and military domains, the unmanned aerial vehicle (UAV) swarms emerge as effective solutions, in which multiple cooperative UAVs can work together to achieve specific goals. However, how to manage such complex systems to ensure real-time adaptability lack sufficient researches. Hence, in this paper, we propose the cooperative cognitive dynamic system (CCDS), to optimize the management for UAV swarms. CCDS leverages a hierarchical and cooperative control structure that enables real-time data processing and decision. Accordingly, CCDS optimizes the UAV swarm management via dynamic reconfigurability and adaptive intelligent optimization. In addition, CCDS can be integrated with the biomimetic mechanism to efficiently allocate tasks for UAV swarms. Further, the distributed coordination of CCDS ensures reliable and resilient control, thus enhancing the adaptability and robustness. Finally, the potential challenges and future directions are analyzed, to provide insights into managing UAV swarms in dynamic heterogeneous networking
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