Dynamic Voxel Grid Optimization for High-Fidelity RGB-D Supervised Surface Reconstruction

Direct optimization of interpolated features on multi-resolution voxel grids has emerged as a more efficient alternative to MLP-like modules. However, this approach is constrained by higher memory expenses and limited representation capabilities. In this paper, we introduce a novel dynamic grid optimization method for high-fidelity 3D surface reconstruction that incorporates both RGB and depth observations. Rather than treating each voxel equally, we optimize the process by dynamically modifying the grid and assigning more finer-scale voxels to regions with higher complexity, allowing us to capture more intricate details. Furthermore, we develop a scheme to quantify the dynamic subdivision of voxel grid during optimization without requiring any priors. The proposed approach is able to generate high-quality 3D reconstructions with fine details on both synthetic and real-world data, while maintaining computational efficiency, which is substantially faster than the baseline method NeuralRGBD.Comment: For the project, see https://yanqingan.github.io

PlanarNeRF: Online Learning of Planar Primitives with Neural Radiance Fields

Identifying spatially complete planar primitives from visual data is a crucial task in computer vision. Prior methods are largely restricted to either 2D segment recovery or simplifying 3D structures, even with extensive plane annotations. We present PlanarNeRF, a novel framework capable of detecting dense 3D planes through online learning. Drawing upon the neural field representation, PlanarNeRF brings three major contributions. First, it enhances 3D plane detection with concurrent appearance and geometry knowledge. Second, a lightweight plane fitting module is proposed to estimate plane parameters. Third, a novel global memory bank structure with an update mechanism is introduced, ensuring consistent cross-frame correspondence. The flexible architecture of PlanarNeRF allows it to function in both 2D-supervised and self-supervised solutions, in each of which it can effectively learn from sparse training signals, significantly improving training efficiency. Through extensive experiments, we demonstrate the effectiveness of PlanarNeRF in various scenarios and remarkable improvement over existing works

Regional uncertainty of GOSAT XCO_2 retrievals in China: quantification and attribution

The regional uncertainty of the column-averaged dry air mole fraction of CO_2 (XCO_2) retrieved using different algorithms from the Greenhouse gases Observing SATellite (GOSAT) and its attribution are still not well understood. This paper investigates the regional performance of XCO_2 within a latitude band of 37–42° N segmented into 8 cells in a grid of 5° from west to east (80–120° E) in China, where typical land surface types and geographic conditions exist. The former includes desert, grassland and built-up areas mixed with cropland; and the latter includes anthropogenic emissions that change from small to large from west to east, including those from the megacity of Beijing. For these specific cells, we evaluate the regional uncertainty of GOSAT XCO_2 retrievals by quantifying and attributing the consistency of XCO_2 retrievals from four algorithms (ACOS, NIES, OCFP and SRFP) by intercomparison. These retrievals are then specifically compared with simulated XCO_2 from the high-resolution nested model in East Asia of the Goddard Earth Observing System 3-D chemical transport model (GEOS-Chem). We also introduce the anthropogenic CO_2 emissions data generated from the investigation of surface emitting point sources that was conducted by the Ministry of Environmental Protection of China to GEOS-Chem simulations of XCO_2 over the Chinese mainland. The results indicate that (1) regionally, the four algorithms demonstrate smaller absolute biases of 0.7–1.1 ppm in eastern cells, which are covered by built-up areas mixed with cropland with intensive anthropogenic emissions, than those in the western desert cells (1.0–1.6 ppm) with a high-brightness surface from the pairwise comparison results of XCO_2 retrievals. (2) Compared with XCO_2 simulated by GEOS-Chem (GEOS-XCO_2), the XCO_2 values from ACOS and SRFP have better agreement, while values from OCFP are the least consistent with GEOS-XCO_2. (3) Viewing attributions of XCO_2 in the spatio-temporal pattern, ACOS and SRFP demonstrate similar patterns, while OCFP is largely different from the others. In conclusion, the discrepancy in the four algorithms is the smallest in eastern cells in the study area, where the megacity of Beijing is located and where there are strong anthropogenic CO_2 emissions, which implies that XCO_2 from satellite observations could be reliably applied in the assessment of atmospheric CO_2 enhancements induced by anthropogenic CO_2 emissions. The large inconsistency among the four algorithms presented in western deserts which displays a high albedo and dust aerosols, moreover, demonstrates that further improvement is still necessary in such regions, even though many algorithms have endeavored to minimize the effects of aerosols scattering and surface albedo

Three Capsular Polysaccharide Synthesis-Related Glucosyltransferases, GT-1, GT-2 and WcaJ, Are Associated With Virulence and Phage Sensitivity of Klebsiella pneumoniae

Klebsiella pneumoniae (K. pneumoniae) spp. are important nosocomial and community-acquired opportunistic pathogens, which cause various infections. We observed that K. pneumoniae strain K7 abruptly mutates to rough-type phage-resistant phenotype upon treatment with phage GH-K3. In the present study, the rough-type phage-resistant mutant named K7RR showed much lower virulence than K7. Liquid chromatography-tandem mass spectrometry (LC-MS-MS) analysis indicated that WcaJ and two undefined glycosyltransferases (GTs)- named GT-1, GT-2- were found to be down-regulated drastically in K7RR as compared to K7 strain. GT-1, GT-2, and wcaJ are all located in the gene cluster of capsular polysaccharide (CPS). Upon deletion, even of single component, of GT-1, GT-2, and wcaJ resulted clearly in significant decline of CPS synthesis with concomitant development of GH-K3 resistance and decline of virulence of K. pneumoniae, indicating that all these three GTs are more likely involved in maintenance of phage sensitivity and bacterial virulence. Additionally, K7RR and GT-deficient strains were found sensitive to endocytosis of macrophages. Mitogen-activated protein kinase (MAPK) signaling pathway of macrophages was significantly activated by K7RR and GT-deficient strains comparing with that of K7. Interestingly, in the presence of macromolecular CPS residues (>250 KD), K7(ΔGT-1) and K7(ΔwcaJ) could still be bounded by GH-K3, though with a modest adsorption efficiency, and showed minor virulence, suggesting that the CPS residues accumulated upon deletion of GT-1 or wcaJ did retain phage binding sites as well maintain mild virulence. In brief, our study defines, for the first time, the potential roles of GT-1, GT-2, and WcaJ in K. pneumoniae in bacterial virulence and generation of rough-type mutation under the pressure of bacteriophage

Research on Rail Transit Network System and its Connection Model in the Metropolitan Area

In order to plan rail transit network in metropolitan area, this paper firstly analyzes metropolitan space structure and features of land layout. It then proposes an effective rail transit network system in Chinese metropolitan area and provides technical suggestions based on the available experience with rail transit network systems and corresponding connection models in foreign metropolitan areas. This study considers the land layout, passenger flow distribution and the corridor characteristics. It also employs Yangzhou as an example. The article suggests that the suburban transit with ribbon land layout in the metropolitan area is not suitable to directly enter the city centre and station is needed in the periphery of the city centre to connect urban rail transit network system

A Step-Up Nonisolated Modular Multilevel DC–DC Converter With Self-Voltage Balancing and Soft Switching

Evolving from the popular modular multilevel ac-dc converter, the single-stage nonisolated modular multilevel dc-dc converter (MMDC) is advantageous for medium- and high-voltage applications. However, exploiting ac circulating power to balance the submodule energy, when utilized for high step ratio applications, existing MMDC topologies suffer from circulating current through the arms and large filter inductor at the low-voltage side. To overcome these issues, this article presents a new power transfer mechanism to balance the submodule energy automatically by reconstructing the half-bridge submodule into a quasi-resonant circuit. Based on this submodule structure, a new MMDC topology for step-up applications is proposed. Compared to the existing MMDCs, the proposed one offers the following advantages. First, the common-mode circulating current through the lower and upper arms is avoided. Second, the self-balancing of the capacitor voltages is guaranteed by the proposed modulation method to insert and bypass adjacent submodules in a complementary manner. Third, the soft-switching operation is achieved for the majority of the switches to alleviate switching losses. Fourth, the voltage stress across the input side inductor is limited to the submodule voltage, thereby reducing the size of the inductor. Simulation analysis and experimental results verify the performance of the proposed MMDC.Ministry of Education (MOE)Nanyang Technological UniversityThis work was supported in part by the National Natural Science Foundation of China under Grant 51677117 and in part by the Singapore ACRF Tier 1 Grant RG 85/18. The work of Xin Zhang was supported by the NTU Start-up Grant (SCOPES)