Online Adaptation for Implicit Object Tracking and Shape Reconstruction in the Wild

Tracking and reconstructing 3D objects from cluttered scenes are the key components for computer vision, robotics and autonomous driving systems. While recent progress in implicit function has shown encouraging results on high-quality 3D shape reconstruction, it is still very challenging to generalize to cluttered and partially observable LiDAR data. In this paper, we propose to leverage the continuity in video data. We introduce a novel and unified framework which utilizes a neural implicit function to simultaneously track and reconstruct 3D objects in the wild. Our approach adapts the DeepSDF model (i.e., an instantiation of the implicit function) in the video online, iteratively improving the shape reconstruction while in return improving the tracking, and vice versa. We experiment with both Waymo and KITTI datasets and show significant improvements over state-of-the-art methods for both tracking and shape reconstruction tasks. Our project page is at https://jianglongye.com/implicit-tracking .Comment: Accepted to RA-L 2022 & IROS 2022. Project page: https://jianglongye.com/implicit-trackin

Causal relationships between susceptibility and severity of COVID-19 and neuromyelitis optica spectrum disorder (NMOSD) in European population: a bidirectional Mendelian randomized study

BackgroundNeurological disorders can be caused by viral infections. The association between viral infections and neuromyelitis optica spectrum disorder (NMOSD) has been well-documented for a long time, and this connection has recently come to attention with the occurrence of SARS-CoV-2 infection. However, the precise nature of the causal connection between NMOSD and COVID-19 infection remains uncertain.MethodsTo investigate the causal relationship between COVID-19 and NMOSD, we utilized a two-sample Mendelian randomization (MR) approach. This analysis was based on the most extensive and recent genome-wide association study (GWAS) that included SARS-CoV-2 infection data (122616 cases and 2475240 controls), hospitalized COVID-19 data (32519 cases and 2062805 controls), and data on severe respiratory confirmed COVID-19 cases (13769 cases and 1072442 controls). Additionally, we incorporated a GWAS meta-analysis comprising 132 cases of AQP4-IgG-seropositive NMOSD (NMO-IgG+), 83 cases of AQP4-IgG-seronegative NMOSD (NMO-IgG−), and 1244 controls.ResultsThe findings of our study indicate that the risk of developing NMO-IgG+ is elevated when there is a genetic predisposition to SARS-CoV-2 infection (OR = 5.512, 95% CI = 1.403-21.657, P = 0.014). Furthermore, patients with genetically predicted NMOSD did not exhibit any heightened susceptibility to SARS-CoV2 infection, COVID-19 hospitalization, or severity.Conclusionour study using Mendelian randomization (MR) revealed, for the first time, that the presence of genetically predicted SARS-CoV2 infection was identified as a contributing factor for NMO-IgG+ relapses

MVDream: Multi-view Diffusion for 3D Generation

We propose MVDream, a multi-view diffusion model that is able to generate geometrically consistent multi-view images from a given text prompt. By leveraging image diffusion models pre-trained on large-scale web datasets and a multi-view dataset rendered from 3D assets, the resulting multi-view diffusion model can achieve both the generalizability of 2D diffusion and the consistency of 3D data. Such a model can thus be applied as a multi-view prior for 3D generation via Score Distillation Sampling, where it greatly improves the stability of existing 2D-lifting methods by solving the 3D consistency problem. Finally, we show that the multi-view diffusion model can also be fine-tuned under a few shot setting for personalized 3D generation, i.e. DreamBooth3D application, where the consistency can be maintained after learning the subject identity.Comment: Our project page is https://MV-Dream.github.i

GIS-based landslide susceptibility modeling using data mining techniques

Introduction: Landslide is one of the most widespread geohazards around the world. Therefore, it is necessary and meaningful to map regional landslide susceptibility for landslide mitigation. In this research, landslide susceptibility maps were produced by four models, namely, certainty factors (CF), naive Bayes (NB), J48 decision tree (J48), and multilayer perceptron (MLP) models.Methods: In the first step, 328 landslides were identified via historical data, interpretation of remote sensing images, and field investigation, and they were divided into two subsets that were assigned different uses: 70% subset for training and 30% subset for validating. Then, twelve conditioning factors were employed, namely, altitude, slope angle, slope aspect, plan curvature, profile curvature, TWI, NDVI, distance to rivers, distance to roads, land use, soil, and lithology. Later, the importance of each conditioning factor was analyzed by average merit (AM) values, and the relationship between landslide occurrence and various factors was evaluated using the certainty factor (CF) approach. In the next step, the landslide susceptibility maps were produced based on four models, and the effect of the four models were quantitatively compared by receiver operating characteristic (ROC) curves, area under curve (AUC) values, and non-parametric tests.Results: The results demonstrated that all the four models can reasonably assess landslide susceptibility. Of these four models, the CF model has the best predictive performance for the training (AUC=0.901) and validating data (AUC=0.892).Discussion: The proposed approach is an innovative method that may also help other scientists to develop landslide susceptibility maps in other areas and that could be used for geo-environmental problems besides natural hazard assessments

Copper-based charge transfer multiferroics with a d9d^9 configuration

Multiferroics are materials with a coexistence of magnetic and ferroelectric order allowing the manipulation of magnetism by applications of an electric field through magnetoelectric coupling effects. Here we propose an idea to design a class of multiferroics with a $d^9$ configuration using the magnetic order in copper-oxygen layers appearing in copper oxide high-temperature superconductors by inducing ferroelectricity. Copper-based charge transfer multiferroics SnCuO2 and PbCuO2 having the inversion symmetry breaking $P4mm$ polar space group are predicted to be such materials. The active inner s electrons in Sn and Pb hybridize with O $2p$ states leading the buckling in copper-oxygen layers and thus induces ferroelectricity, which is known as the lone pair mechanism. As a result of the $d^9$ configuration, SnCuO2 and PbCuO2 are charge transfer insulators with the antiferromagnetic ground state of the moment on Cu retaining some strongly correlated physical properties of parent compounds of copper oxide high-temperature superconductors. Our work reveals the possibility of designing multiferroics based on copper oxide high-temperature superconductors.Comment: 18 pages, 5 figures, 1 tabl

Elemental topological ferroelectrics and polar metals of few-layer materials

Ferroelectricity can exist in elemental phases as a result of charge transfers between atoms occupying inequivalent Wyckoff positions. We investigate the emergence of ferroelectricity in two-dimensional elemental materials with buckled honeycomb lattices. Various multi-bilayer structures hosting ferroelectricity are designed by stacking-engineering. Ferroelectric materials candidates formed by group IV and V elements are predicted theoretically. Ultrathin Bi films show layer-stacking-dependent physical properties of ferroelectricity, topology, and metallicity. The two-bilayer Bi film with a polar stacking sequence is found to be an elemental topological ferroelectric material. Three and four bilayers Bi films with polar structures are ferroelectric-like elemental polar metals with topological nontrivial edge states. For Ge and Sn, trivial elemental polar metals are predicted. Our work reveals the possibility of design two-dimensional elemental topological ferroelectrics and polar metals by stacking-engineering.Comment: 18 pages, 6 figure

Anisotropic, Intermediate Coupling Superconductivity in Cu0.03TaS2

The anisotropic superconducting state properties in Cu0.03TaS2 have been investigated by magnetization, magnetoresistance, and specific heat measurements. It clearly shows that Cu0.03TaS2 undergoes a superconducting transition at TC = 4.03 K. The obtained superconducting parameters demonstrate that Cu0.03TaS2 is an anisotropic type-II superconductor. Combining specific heat jump = 1.6(4), gap ratio 2/kBTC = 4.0(9) and the estimated electron-phonon coupling constant ~ 0.68, the superconductivity in Cu0.03TaS2 is explained within the intermediate coupling BCS scenario. First-principles electronic structure calculations suggest that copper intercalation of 2H-TaS2 causes a considerable increase of the Fermi surface volume and the carrier density, which suppresses the CDW fluctuation and favors the raise of TC.Comment: 16pages, 5figure

Aerosol meteorology of Maritime Continent for the 2012 7SEAS southwest monsoon intensive study - Part 2: Philippine receptor observations of fine-scale aerosol behavior

Abstract. The largest 7 Southeast Asian Studies (7SEAS) operations period within the Maritime Continent (MC) occurred in the August–September 2012 biomass burning season. Data included were observations aboard the M/Y Vasco, dispatched to the Palawan Archipelago and Sulu Sea of the Philippines for September 2012. At these locations, the Vasco observed MC smoke and pollution entering the southwest monsoon (SWM) monsoonal trough. Here we describe the research cruise findings and the finer-scale aerosol meteorology of this convectively active region. This 2012 cruise complemented a 2-week cruise in 2011 and was generally consistent with previous findings in terms of how smoke emission and transport related to monsoonal flows, tropical cyclones (TC), and the covariance between smoke transport events and the atmosphere's thermodynamic structure. Biomass burning plumes were usually mixed with significant amounts of anthropogenic pollution. Also key to aerosol behavior were squall lines and cold pools propagating across the South China Sea (SCS) and scavenging aerosol particles in their path. However, the 2012 cruise showed much higher modulation in aerosol frequency than its 2011 counterpart. Whereas in 2011 large synoptic-scale aerosol events transported high concentrations of smoke into the Philippines over days, in 2012 measured aerosol events exhibited a much shorter-term variation, sometimes only 3–12 h. Strong monsoonal flow reversals were also experienced in 2012. Nucleation events in cleaner and polluted conditions, as well as in urban plumes, were observed. Perhaps most interestingly, several cases of squall lines preceding major aerosol events were observed, as opposed to 2011 observations where these lines largely scavenged aerosol particles from the marine boundary layer. Combined, these observations indicate pockets of high and low particle counts that are not uncommon in the region. These perturbations are difficult to observe by satellite and very difficult to model. Indeed, the Navy Aerosol Analysis and Prediction System (NAAPS) simulations captured longer period aerosol events quite well but largely failed to capture the timing of high-frequency phenomena. Ultimately, the research findings of these cruises demonstrate the real world challenges of satellite-based missions, significant aerosol life cycle questions such as those the future Aerosol/Clouds/Ecosystems (ACE) will investigate, and the importance of small-scale phenomena such as sea breezes, squall lines, and nucleation events embedded within SWM patterns in dominating aerosol life cycle and potential relationships to clouds