DDF-HO: Hand-Held Object Reconstruction via Conditional Directed Distance Field

Reconstructing hand-held objects from a single RGB image is an important and challenging problem. Existing works utilizing Signed Distance Fields (SDF) reveal limitations in comprehensively capturing the complex hand-object interactions, since SDF is only reliable within the proximity of the target, and hence, infeasible to simultaneously encode local hand and object cues. To address this issue, we propose DDF-HO, a novel approach leveraging Directed Distance Field (DDF) as the shape representation. Unlike SDF, DDF maps a ray in 3D space, consisting of an origin and a direction, to corresponding DDF values, including a binary visibility signal determining whether the ray intersects the objects and a distance value measuring the distance from origin to target in the given direction. We randomly sample multiple rays and collect local to global geometric features for them by introducing a novel 2D ray-based feature aggregation scheme and a 3D intersection-aware hand pose embedding, combining 2D-3D features to model hand-object interactions. Extensive experiments on synthetic and real-world datasets demonstrate that DDF-HO consistently outperforms all baseline methods by a large margin, especially under Chamfer Distance, with about 80% leap forward. Codes and trained models will be released soon

U-RED: Unsupervised 3D Shape Retrieval and Deformation for Partial Point Clouds

In this paper, we propose U-RED, an Unsupervised shape REtrieval and Deformation pipeline that takes an arbitrary object observation as input, typically captured by RGB images or scans, and jointly retrieves and deforms the geometrically similar CAD models from a pre-established database to tightly match the target. Considering existing methods typically fail to handle noisy partial observations, U-RED is designed to address this issue from two aspects. First, since one partial shape may correspond to multiple potential full shapes, the retrieval method must allow such an ambiguous one-to-many relationship. Thereby U-RED learns to project all possible full shapes of a partial target onto the surface of a unit sphere. Then during inference, each sampling on the sphere will yield a feasible retrieval. Second, since real-world partial observations usually contain noticeable noise, a reliable learned metric that measures the similarity between shapes is necessary for stable retrieval. In U-RED, we design a novel point-wise residual-guided metric that allows noise-robust comparison. Extensive experiments on the synthetic datasets PartNet, ComplementMe and the real-world dataset Scan2CAD demonstrate that U-RED surpasses existing state-of-the-art approaches by 47.3%, 16.7% and 31.6% respectively under Chamfer Distance.Comment: ICCV202

CCD-3DR: Consistent Conditioning in Diffusion for Single-Image 3D Reconstruction

In this paper, we present a novel shape reconstruction method leveraging diffusion model to generate 3D sparse point cloud for the object captured in a single RGB image. Recent methods typically leverage global embedding or local projection-based features as the condition to guide the diffusion model. However, such strategies fail to consistently align the denoised point cloud with the given image, leading to unstable conditioning and inferior performance. In this paper, we present CCD-3DR, which exploits a novel centered diffusion probabilistic model for consistent local feature conditioning. We constrain the noise and sampled point cloud from the diffusion model into a subspace where the point cloud center remains unchanged during the forward diffusion process and reverse process. The stable point cloud center further serves as an anchor to align each point with its corresponding local projection-based features. Extensive experiments on synthetic benchmark ShapeNet-R2N2 demonstrate that CCD-3DR outperforms all competitors by a large margin, with over 40% improvement. We also provide results on real-world dataset Pix3D to thoroughly demonstrate the potential of CCD-3DR in real-world applications. Codes will be released soonComment: 11 page

MOHO: Learning Single-view Hand-held Object Reconstruction with Multi-view Occlusion-Aware Supervision

Previous works concerning single-view hand-held object reconstruction typically utilize supervision from 3D ground truth models, which are hard to collect in real world. In contrast, abundant videos depicting hand-object interactions can be accessed easily with low cost, although they only give partial object observations with complex occlusion. In this paper, we present MOHO to reconstruct hand-held object from a single image with multi-view supervision from hand-object videos, tackling two predominant challenges including object's self-occlusion and hand-induced occlusion. MOHO inputs semantic features indicating visible object parts and geometric embeddings provided by hand articulations as partial-to-full cues to resist object's self-occlusion, so as to recover full shape of the object. Meanwhile, a novel 2D-3D hand-occlusion-aware training scheme following the synthetic-to-real paradigm is proposed to release hand-induced occlusion. In the synthetic pre-training stage, 2D-3D hand-object correlations are constructed by supervising MOHO with rendered images to complete the hand-concealed regions of the object in both 2D and 3D space. Subsequently, MOHO is finetuned in real world by the mask-weighted volume rendering supervision adopting hand-object correlations obtained during pre-training. Extensive experiments on HO3D and DexYCB datasets demonstrate that 2D-supervised MOHO gains superior results against 3D-supervised methods by a large margin. Codes and key assets will be released soon

LmbU, a Cluster-Situated Regulator for Lincomycin, Consists of a DNA-Binding Domain, an Auto-Inhibitory Domain, and Forms Homodimer

Few studies were reported about the regulatory mechanism of lincomycin biosynthesis since it was found in 1962. Although we have proved that a cluster-situated regulator (CSR) LmbU (GenBank Accession No. ABX00623.1) positively modulates lincomycin biosynthesis in Streptomyces lincolnensis NRRL 2936, the molecular mechanism of LmbU regulation is still unclear. In this study, we demonstrated that LmbU binds to the target lmbAp by a central DNA-binding domain (DBD), which interacts with the binding sites through the helix-turn-helix (HTH) motif. N-terminal of LmbU includes an auto-inhibitory domain (AID), inhibiting the DNA-binding activity of LmbU. Without the AID, LmbU variant can bind to its own promoter. Interestingly, compared to other LmbU homologs, the homologs within the biosynthetic gene clusters (BGCs) of known antibiotics generally contain N-terminal AIDs, which offer them the abilities to play complex regulatory functions. In addition, cysteine 12 (C12) has been proved to be mainly responsible for LmbU homodimer formation in vitro. In conclusion, LmbU homologs naturally exist in hundreds of actinomycetes, and belong to a new regulatory family, LmbU family. The present study reveals the DBD, AID and dimerization of LmbU, and sheds new light on the regulatory mechanism of LmbU and its homologs

A general route via formamide condensation to prepare atomically dispersed metal-nitrogen-carbon electrocatalysts for energy technologies

Single-atom electrocatalysts (SAECs) have gained tremendous attention due to their unique active sites and strong metal–substrate interactions. However, the current synthesis of SAECs mostly relies on costly precursors and rigid synthetic conditions and often results in very low content of single-site metal atoms. Herein, we report an efficient synthesis method to prepare metal–nitrogen–carbon SAECs based on formamide condensation and carbonization, featuring a cost-effective general methodology for the mass production of SAECs with high loading of atomically dispersed metal sites. The products with metal inclusion were termed as formamide-converted metal–nitrogen–carbon (shortened as f-MNC) materials. Seven types of single-metallic f-MNC (Fe, Co, Ni, Mn, Zn, Mo and Ir), two bi-metallic (ZnFe and ZnCo) and one tri-metallic (ZnFeCo) SAECs were synthesized to demonstrate the generality of the methodology developed. Remarkably, these f-MNC SAECs can be coated onto various supports with an ultrathin layer as pyrolysis-free electrocatalysts, among which the carbon nanotube-supported f-FeNC and f-NiNC SAECs showed high performance for the O2 reduction reaction (ORR) and the CO2 reduction reaction (CO2RR), respectively. Furthermore, the pyrolysis products of supported f-MNC can still render isolated metallic sites with excellent activity, as exemplified by the bi-metallic f-FeCoNC SAEC, which exhibited outstanding ORR performance in both alkaline and acid electrolytes by delivering ∼70 and ∼20 mV higher half-wave potentials than that of commercial 20 wt% Pt/C, respectively. This work offers a feasible approach to design and manufacture SAECs with tuneable atomic metal components and high density of single-site metal loading, and thus may accelerate the deployment of SAECs for various energy technology applications

Common and distinct equity preferences in children and adults

Fairness plays a crucial role in children’s social life and has garnered considerable attention. However, previous research and theories primarily examined the development of children’s fairness behaviors in the conflict between self-interest motivation and fairness-complying motivation, neglecting the influence of advantage-seeking motivation. Moreover, despite the well-established role of gain/loss frame in human decision-making, it remains largely unclear whether the framing effect modulates fairness behaviors in children. It was hypothesized that children would exhibit advantage-seeking motivation resulting in more selfish behaviors in the loss context. To examine the hypothesis, we combined an adapted dictator game and computational modeling to investigate various motivations underlying fairness behaviors of children in both loss and gain contexts and to explore the developmental directions by contrasting children and adults. In addition, the current design enabled the dissociation between fairness knowledge and behaviors by asking participants to decide for themselves (the first-party role) or for others (the third-party role). This study recruited a total of 34 children (9–10 years, Mage = 9.82, SDage = 0.38, 16 females) and 31 college students (Mage = 19.81, SDage = 1.40, 17 females). The behavioral results indicated that children behaved more selfishly in first-party and more fairly in third-party than adults, without any significant framing effects. The computational results revealed that both children and adults exhibited aversion to advantageous and disadvantageous inequity in third-party. However, they showed distinct preferences for advantageous inequity in first-party, with advantage-seeking preferences among children and aversion to advantageous inequity among adults. These findings contribute to a deeper understanding of children’s social preferences and their developmental directions

Research on Influence Factors and Acceleration Methods of Current Commutation

The vacuum interrupter is widely used due to the advantages of no arc-extinguishing medium and high insulation strength. However, the arc voltage generated by the commonly used CuCr contacts is low. In hybrid DC circuit breakers (DCCB), hybrid automatic transfer switches (ATS), medium voltage compound switches and other fields, it is difficult to rely on vacuum arc to complete natural commutation, which restricts the development of hybrid switches. In order to understand the current commutation process deeply, the influence of internal and external factors on the current commutation is analyzed by experiments. The coupling mathematical model of arc-commutated branch is established. The criterion for the success of current commutation is summarized. The parameters of the arc model are reconstructed through repeated breaking experiments to explore the influence of internal factors on the arc characteristics. Based on this, the influence law of arc current, contacts gap and transverse magnetic field (TMF) is analyzed. An acceleration method of current commutation is proposed. A prototype for accelerating experiments with an electromagnetic repulsion mechanism and TMF is developed. The commutated branch equivalent to practical applications is built. The experimental results show that the commutation time is effectively shortened and meets the requirements of practical applications through the acceleration method, which provides new thought for the development of hybrid switches

Investigation of the Structure and Allergic Potential of Whey Protein by Both Heating Sterilization and Simulation with Molecular Dynamics

As the main allergens in milk, whey proteins are heat-sensitive proteins and are widespread in dairy products and items in which milk proteins are involved as food additives. The present work sought to investigate the effect of heating sterilization on the allergenicity of α-lactalbumin (α-LA) and β-lactoglobulin (β-LG), the main composite and allergen in whey protein isolate (WPI), by combining molecular dynamics with experimental techniques for detecting the spatial structure and IgE binding capacity. The structure of WPI was basically destroyed at heat sterilization conditions of 95 °C for 5 min and 65 °C for 30 min by SDS-PAGE analysis and spectroscopic analysis. In addition, α-lactalbumin (α-LA) may be more sensitive to temperature, resulting in exposure to allergic epitopes and increasing the allergic potential, while the binding capacity of β-lactoglobulin (β-LG) to IgE was reduced under 65 °C for 30 min. By the radius of gyration (Rg) and root-mean-square deviation (RMSD) plots calculated in molecular dynamics simulations, α-LA was less structurally stable at 368 K, while β-LG remained stable at higher temperatures, indicating that α-LA was more thermally sensitive. In addition, we observed that the regions significantly affected by temperatures were associated with the capacity of allergic epitopes (α-LA 80–101 and β-LG 82–93, 105–121) to bind IgE through root-mean-standard fluctuation (RMSF) plots, which may influence the two major allergens. We inferred that these regions are susceptible to structural changes after sterilization, thus affecting the allergenicity of allergens