NeUDF: Learning Unsigned Distance Fields from Multi-view Images for Reconstructing Non-watertight Models

Volume rendering-based 3D reconstruction from multi-view images has gained popularity in recent years, largely due to the success of neural radiance fields (NeRF). A number of methods have been developed that build upon NeRF and use neural volume rendering to learn signed distance fields (SDFs) for reconstructing 3D models. However, SDF-based methods cannot represent non-watertight models and, therefore, cannot capture open boundaries. This paper proposes a new algorithm for learning an accurate unsigned distance field (UDF) from multi-view images, which is specifically designed for reconstructing non-watertight, textureless models. The proposed method, called NeUDF, addresses the limitations of existing UDF-based methods by introducing a simple and approximately unbiased and occlusion-aware density function. In addition, a smooth and differentiable UDF representation is presented to make the learning process easier and more efficient. Experiments on both texture-rich and textureless models demonstrate the robustness and effectiveness of the proposed approach, making it a promising solution for reconstructing challenging 3D models from multi-view images

Effect of soil bacteriomes on mycorrhizal colonization by <i>Rhizophagus irregularis</i>:Interactive effects on maize (<i>Zea mays</i> L.) growth under salt stress

In this study, we investigated the interactive effects of the arbuscular mycorrhizal fungus (AMF) Rhizophagus irregularis and soil bacteriomes on maize growth under salt stress (100 mM NaCl) and also the effect of salt and bacteriomes on the mycorrhizal infection levels. We found that soil bacteriomes directly promoted the growth of maize and indirectly enhanced maize biomass by increasing mycorrhizal colonization levels, irrespective of salt stress. Although R. irregularis by itself had no maize growth-promoting effect even at a high mycorrhizal colonization level in roots, its benefits to maize were reflected in other aspects, evidenced by the significantly increased rate of arbuscule formation (a proxy for a functional plant-AMF nutritional exchange) under salinity. A negative correlation between arbuscule colonization and root biomass suggested R. irregularis expands the role of maize roots. Besides, the positive correlation between the overall AMF colonization level and shoot biomass supported the tenet of a positive contribution of R. irregularis to maize growth. Our findings suggest that soil bacteriomes interactively work with R. irregularis, modulating the growth of maize by affecting the colonization of AMF in roots

Soil microbiome manipulation triggers direct and possible indirect suppression against <i>Ralstonia solanacearum</i> and <i>Fusarium oxysporum</i>

Soil microbiome manipulation can potentially reduce the use of pesticides by improving the ability of soils to resist or recover from pathogen infestation, thus generating natural suppressiveness. We simulated disturbance through soil fumigation and investigated how the subsequent application of bio-organic and organic amendments reshapes the taxonomic and functional potential of the soil microbiome to suppress the pathogens Ralstonia solanacearum and Fusarium oxysporum in tomato monocultures. The use of organic amendment alone generated smaller shifts in bacterial and fungal community composition and no suppressiveness. Fumigation directly decreased F. oxysporum and induced drastic changes in the soil microbiome. This was further converted from a disease conducive to a suppressive soil microbiome due to the application of organic amendment, which affected the way the bacterial and fungal communities were reassembled. These direct and possibly indirect effects resulted in a highly efficient disease control rate, providing a promising strategy for the control of the diseases caused by multiple pathogens

What makes efficient circularly polarised luminescence in the condensed phase: aggregation-induced circular dichroism and light emission

In this contribution, we conceptually present a new avenue to construction of molecular functional materials with high performance of circularly polarised luminescence (CPL) in the condensed phase. A molecule (1) containing luminogenic silole and chiral sugar moieties was synthesized and thoroughly characterized. In a solution of 1, no circular dichroism (CD) and fluorescence emission are observed, but upon molecular aggregation, both the CD and fluorescence are simultaneously turned on, showing aggregation-induced CD (AICD) and emission (AIE) effects. The AICD effect is supported by the fact that the molecules readily assemble into right-handed helical nanoribbons and superhelical ropes when aggregated. The AIE effect boosts the fluorescence quantum efficiency (ΦF) by 136 fold (ΦF, ∼0.6% in the solution versus ∼81.3% in the solid state), which surmounts the serious limitations of aggregation-caused quenching effect encountered by conventional luminescent materials. Time-resolved fluorescence study and theoretical calculation from first principles conclude that restriction of the low-frequency intramolecular motions is responsible for the AIE effect. The helical assemblies of 1 prefer to emit right-handed circularly polarised light and display large CPL dissymmetry factors (gem), whose absolute values are in the range of 0.08–0.32 and are two orders of magnitude higher than those of commonly reported organic materials. We demonstrate for the first time the use of a Teflon-based microfluidic technique for fabrication of the fluorescent pattern. This shows the highest gem of −0.32 possibly due to the enhanced assembling order in the confined microchannel environment. The CPL performance was preserved after more than half year storage under ambient conditions, revealing the excellent spectral stability. Computational simulation was performed to interpret how the molecules in the aggregates interact with each other at the molecular level. Our designed molecule represents the desired molecular functional material for generating efficient CPL in the solid state, and the current study shows the best results among the reported organic conjugated molecular systems in terms of emission efficiency, dissymmetry factor, and spectral stability

Prompt-to-afterglow transition of optical emission in a long gamma-ray burst consistent with a fireball

Long gamma-ray bursts (GRBs), which signify the end-life collapsing of very massive stars, are produced by extremely relativistic jets colliding into circumstellar medium. Huge energy is released both in the first few seconds, namely the internal dissipation phase that powers prompt emissions, and in the subsequent self-similar jet-deceleration phase that produces afterglows observed in broad-band electromagnetic spectrum. However, prompt optical emissions of GRBs have been rarely detected, seriously limiting our understanding of the transition between the two phases. Here we report detection of prompt optical emissions from a gamma-ray burst (i.e. GRB 201223A) using a dedicated telescope array with a high temporal resolution and a wide time coverage. The early phase coincident with prompt {\gamma}-ray emissions show a luminosity in great excess with respect to the extrapolation of {\gamma}-rays, while the later luminosity bump is consistent with onset of the afterglow. The clearly detected transition allows us to differentiate physical processes contributing to early optical emissions and to diagnose the composition of the jetComment: Authors' version of article published in Nature Astronomy, see their website for official versio

E3 ubiquitin ligase CHIP facilitates Toll-like receptor signaling by recruiting and polyubiquitinating Src and atypical PKCζ

In mouse macrophages and dendritic cells, the CHIP E3 ubiquitin ligase is needed for transduction of signals initiated by TLR4 and TLR9 stimulation

Occluded Vehicle Detection via Multi-Scale Hybrid Attention Mechanism in the Road Scene

The obstruction of vehicles by surrounding vehicles, obstacles, etc. is a common phenomenon in the practical application of automatic driving. In view of the problem that the vehicle’s vision is affected by the occlusion, the vehicle feature information is incomplete, resulting in the low detection accuracy of the occlusion vehicle, and the occlusion vehicle detection method based on the multi-scale hybrid attention mechanism is proposed. The paper aims to fully excavate the advantages of multi-scale feature extraction, channel/space attention and other modules, and to design a multi-scale hybrid attention module suitable for occlusion vehicle detection to improve the detection accuracy of occlusion vehicles. Multi-scale features are enriched by the grouping convolution of different sizes of multi-scale feature extraction networks, and the parallel connection channels and spatial attention modules form different scale hybrid domain attention modules, which enhance the local feature information of the occluded vehicles and realize the reinforcement learning of multi-scale features and the suppression of occlusion interference information. Experimental results show that in the self-made occlusion vehicle dataset and the BDD100K occlusion vehicle dataset, the average mean accuracy of this method is 95.2% and 59.3%, respectively, which is 1.5% and 2.9% higher than that of the baseline network YOLOv5, respectively

Improved YOLOv5 Based on Hybrid Domain Attention for Small Object Detection in Optical Remote Sensing Images

The object detection technology of optical remote sensing images has been widely applied in military investigation, traffic planning, and environmental monitoring, among others. In this paper, a method is proposed for solving the problem of small object detection in optical remote sensing images. In the proposed method, the hybrid domain attention units (HDAUs) of channel and spatial attention mechanisms are combined and employed to improve the feature extraction capability and suppress background noise. In addition, we designed a multiscale dynamic weighted feature fusion network (MDW-Net) to improve adaptive optimization and deep fusion of shallow and deep feature layers. The model is trained and tested on the DIOR dataset, and some ablation and comparative experiments are carried out. The experimental results show that the mAP of the proposed model surpasses that of YOLOv5 by a large margin of +2.3 and has obvious advantages regarding the detection performance for small object categories, such as airplane, ship, and vehicle, which support its application for small target detection in optical remote sensing images

Analysis and Optimization of Milling Deformations of TC4 Alloy Thin-Walled Parts Based on Finite Element Simulations

TC4 (DIN3.7164/5) alloy thin-walled parts are widely used in aviation and aerospace industries. However, due to their special structure, shape and poor machinability, large milling forces and milling deformation often occur in the milling process, which cannot guarantee the machining quality and accuracy. The milling processing parameters and milling geometric parameters have a significant impact on the milling force and the deformation, and optimization of the influence factors of milling deformations is important for milling quality. Considering that performing milling experiments under multiple conditions is often costly and time-consuming, this paper provides a finite-element-simulation-based method to study effects of the factors on the forces and deformations during milling thin-walled parts. Firstly, using ABAQUS, a finite element simulation model of the milling process of thin-walled parts is established. Additionally, an orthogonal experimental scheme is designed for optimization of the milling parameters, so as to determine the optimized experimental scheme, and then the optimized experimental scheme is verified to reduce the milling force and deformation by finite element simulations. The optimal parameters for a minimal milling force are a spindle speed of 2000 r/min, a feed rate per tooth of 0.04 mm/z, a milling depth of 1.6 mm, a milling width of 1 mm, a diameter of 6 mm, a rake angle of 20°, a tilt angle of 45°, and two teeth. Similarly, the optimal parameters for minimal node deformations are a spindle speed of 4800 r/min, a feed rate per tooth of 0.18 mm/z, a milling depth of 1 mm, a milling width of 1 mm, a diameter of 16 mm, a rake angle of 20°, a tilt angle of 40°, and four teeth. In addition, this paper uses an optimization algorithm to fit the empirical function with a certain practical value, which can provide a reference for the machining of TC4 titanium alloy. By doing so, we can optimize the milling parameters to obtain the desired machining quality and accuracy, while also saving on time and resources