159 research outputs found

    ShaDDR: Real-Time Example-Based Geometry and Texture Generation via 3D Shape Detailization and Differentiable Rendering

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    We present ShaDDR, an example-based deep generative neural network which produces a high-resolution textured 3D shape through geometry detailization and conditional texture generation applied to an input coarse voxel shape. Trained on a small set of detailed and textured exemplar shapes, our method learns to detailize the geometry via multi-resolution voxel upsampling and generate textures on voxel surfaces via differentiable rendering against exemplar texture images from a few views. The generation is real-time, taking less than 1 second to produce a 3D model with voxel resolutions up to 512^3. The generated shape preserves the overall structure of the input coarse voxel model, while the style of the generated geometric details and textures can be manipulated through learned latent codes. In the experiments, we show that our method can generate higher-resolution shapes with plausible and improved geometric details and clean textures compared to prior works. Furthermore, we showcase the ability of our method to learn geometric details and textures from shapes reconstructed from real-world photos. In addition, we have developed an interactive modeling application to demonstrate the generalizability of our method to various user inputs and the controllability it offers, allowing users to interactively sculpt a coarse voxel shape to define the overall structure of the detailized 3D shape

    Bilayer Kagome Borophene with Multiple van Hove Singularities

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    The appearance of van Hove singularities near the Fermi level leads to prominent phenomena, including superconductivity, charge density wave, and ferromagnetism. Here a bilayer Kagome lattice with multiple van Hove singularities is designed and a novel borophene with such lattice (BK-borophene) is proposed by the first-principles calculations. BK-borophene, which is formed via three-center two-electron (3c-2e) sigma-type bonds, is predicted to be energetically, dynamically, thermodynamically, and mechanically stable. The electronic structure hosts both conventional and high-order van Hove singularities in one band. The conventional van Hove singularity resulting from the horse saddle is 0.065 eV lower than the Fermi level, while the high-order one resulting from the monkey saddle is 0.385 eV below the Fermi level. Both the singularities lead to the divergence of electronic density of states. Besides, the high-order singularity is just intersected to a Dirac-like cone, where the Fermi velocity can reach 1340000 m/s. The interaction between the two Kagome lattices is critical for the appearance of high-order van Hove singularities. The novel bilayer Kagome borophene with rich and intriguing electronic structure offers an unprecedented platform for studying correlation phenomena in quantum material systems and beyond

    D2^2CSG: Unsupervised Learning of Compact CSG Trees with Dual Complements and Dropouts

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    We present D2^2CSG, a neural model composed of two dual and complementary network branches, with dropouts, for unsupervised learning of compact constructive solid geometry (CSG) representations of 3D CAD shapes. Our network is trained to reconstruct a 3D shape by a fixed-order assembly of quadric primitives, with both branches producing a union of primitive intersections or inverses. A key difference between D2^2CSG and all prior neural CSG models is its dedicated residual branch to assemble the potentially complex shape complement, which is subtracted from an overall shape modeled by the cover branch. With the shape complements, our network is provably general, while the weight dropout further improves compactness of the CSG tree by removing redundant primitives. We demonstrate both quantitatively and qualitatively that D2^2CSG produces compact CSG reconstructions with superior quality and more natural primitives than all existing alternatives, especially over complex and high-genus CAD shapes.Comment: 9 page

    A Novel Dynamic Measurement System for Evaluating the Braking Coordination of Articulated Vehicles

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    The braking coordination between tractor and semitrailer is vital to the safety of articulated vehicles. Traditional evaluation about braking coordination is based on the pressure measurement along air braking pipeline, which needs to change original braking structure to install gauges and cannot directly reflect the final braking coordination of different wheels. To overcome these limitations, this paper proposes a novel dynamic measurement system for evaluating the braking coordination of articulated vehicles. During the brake test, all wheel velocities of the whole articulated vehicle are synchronously obtained through a specially designed distributed acquisition platform. To effectively eliminate gross errors and noises in wheel angular velocity data, a 3-order autoregressive (AR) model and an improved-thresholding wavelet filtering algorithm are developed. Further, a novel direct evaluation method about braking coordination is proposed according to the differences in angular velocity dropping time of all wheels. Finally, the overall system is assessed through real field tests. The results validate the feasibility and effectiveness of the proposed system

    Scalable Scheduling for Industrial Time-Sensitive Networking: A Hyper-flow Graph Based Scheme

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    Industrial Time-Sensitive Networking (TSN) provides deterministic mechanisms for real-time and reliable flow transmission. Increasing attention has been paid to efficient scheduling for time-sensitive flows with stringent requirements such as ultra-low latency and jitter. In TSN, the fine-grained traffic shaping protocol, cyclic queuing and forwarding (CQF), eliminates uncertain delay and frame loss by cyclic traffic forwarding and queuing. However, it inevitably causes high scheduling complexity. Moreover, complexity is quite sensitive to flow attributes and network scale. The problem stems in part from the lack of an attribute mining mechanism in existing frame-based scheduling. For time-critical industrial networks with large-scale complex flows, a so-called hyper-flow graph based scheduling scheme is proposed to improve the scheduling scalability in terms of schedulability, scheduling efficiency and latency & jitter. The hyper-flow graph is built by aggregating similar flow sets as hyper-flow nodes and designing a hierarchical scheduling framework. The flow attribute-sensitive scheduling information is embedded into the condensed maximal cliques, and reverse maps them precisely to congestion flow portions for re-scheduling. Its parallel scheduling reduces network scale induced complexity. Further, this scheme is designed in its entirety as a comprehensive scheduling algorithm GH^2. It improves the three criteria of scalability along a Pareto front. Extensive simulation studies demonstrate its superiority. Notably, GH^2 is verified its scheduling stability with a runtime of less than 100 ms for 1000 flows and near 1/430 of the SOTA FITS method for 2000 flows

    Characteristic on the Stability of <em>Haloxylon ammodendron</em> Plantation in the Southern Fringe of Gurbantunggut Desert, Northwest China

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    Using chronosequence theory and method, the characteristics of vegetation-soil coupling and structure stability of Haloxylon ammodendron plantations in the southern fringe of Gurbantunggut Desert were analyzed. The results showed, the canopy storey of H. ammodendron plantation experienced three stages, rapid growth (the age of 7 to 20), then slow growth (the age of 20 to 28) and last decline (over the age of 28). The best natural regeneration started from 17-yr-old plantation. Vegetation-soil system coupling degree (C) and coupling coordinative degree (D) of plantations with different age were not one-to-one correspondence. The system of H. ammodendron plantations always stayed in disorder recession, vegetation and soil were prone to loss type during the process of sand-fixation. Five principal components evaluated that the first rank was 42-yr-old plantation. It was inferred that the trend of the vegetation and soil system was from senescence to harmonious development. So the trend of coordinated development between vegetation and soil would be promoted, if the artificial tending and management measures strengthened

    Construction and Characterization of a Chimeric Virus (BIV/HIV-1) Carrying the Bovine Immunodeficiency Virus \u3ci\u3egag\u3c/i\u3e-\u3ci\u3epol\u3c/i\u3e Gene: Research Letters

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    HIV-1HXB2 5′LTR region, most of BIVR29 gag-pol segment and HIV-1HXB2 pol IN-3′LTR region were respectively amplified. A chimeric clone, designated as pHBIV3753, was constructed by cloning three fragments sequentially into pUC18. MT4 cells were transfected with pHBIV3753. The replication and expressions of the chimeric virus (HBIV3753) were monitored by RT activity and IFA. The results firstly demonstrated that it is possible to generate a new type of the BIV/HIV-1 chimeric virus containing BIV gag-pol gene
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