On the bubble trapped underneath a droplet impacting a moving hydrophilic surface: From perfect slip to no slip

The bubble trapped underneath a droplet impacting a moving hydrophilic surface was investigated using high-speed photography. The bubble diameter was found to depend weakly on the surface speed Vs, but strongly on the Weber number We. The bubble and the surrounding liquid slip on the surface while accelerating to Vs, with the slip velocity gradually decreasing to zero, demonstrating that the no-slip boundary condition does not apply during the acceleration period. The terminal slip distance, identifying the maximum distance between the bubble and the impact point, increases with an increase of Vs and weakly depends on We. Its observed length was up to 1.39 mm. An acceleration extracted from the experiments quantifies the slip and provides a simple tool for predicting the terminal slip distance

Pedestrian Accessible Infrastructure Inventory: Assessing Zero-Shot Segmentation on Multi-Mode Geospatial Data for All Pedestrian Types

In this paper, a Segment Anything Model (SAM)-based pedestrian infrastructure segmentation workflow is designed and optimized, which is capable of efficiently processing multi-sourced geospatial data including LiDAR data and satellite imagery data. We used an expanded definition of pedestrian infrastructure inventory which goes beyond the traditional transportation elements to include street furniture objects that are important for accessibility but are often omitted from the traditional definition. Our contributions lie in producing the necessary knowledge to answer the following two questions. First, which data representation can facilitate zero-shot segmentation of infrastructure objects with SAM? Second, how well does the SAM-based method perform on segmenting pedestrian infrastructure objects? Our findings indicate that street view images generated from mobile LiDAR point cloud data, when paired along with satellite imagery data, can work efficiently with SAM to create a scalable pedestrian infrastructure inventory approach with immediate benefits to GIS professionals, city managers, transportation owners, and walkers, especially those with travel-limiting disabilities, such as individuals who are blind, have low vision, or experience mobility disabilities

Facial Data Minimization: Shallow Model as Your Privacy Filter

Face recognition service has been used in many fields and brings much convenience to people. However, once the user's facial data is transmitted to a service provider, the user will lose control of his/her private data. In recent years, there exist various security and privacy issues due to the leakage of facial data. Although many privacy-preserving methods have been proposed, they usually fail when they are not accessible to adversaries' strategies or auxiliary data. Hence, in this paper, by fully considering two cases of uploading facial images and facial features, which are very typical in face recognition service systems, we proposed a data privacy minimization transformation (PMT) method. This method can process the original facial data based on the shallow model of authorized services to obtain the obfuscated data. The obfuscated data can not only maintain satisfactory performance on authorized models and restrict the performance on other unauthorized models but also prevent original privacy data from leaking by AI methods and human visual theft. Additionally, since a service provider may execute preprocessing operations on the received data, we also propose an enhanced perturbation method to improve the robustness of PMT. Besides, to authorize one facial image to multiple service models simultaneously, a multiple restriction mechanism is proposed to improve the scalability of PMT. Finally, we conduct extensive experiments and evaluate the effectiveness of the proposed PMT in defending against face reconstruction, data abuse, and face attribute estimation attacks. These experimental results demonstrate that PMT performs well in preventing facial data abuse and privacy leakage while maintaining face recognition accuracy.Comment: 14 pages, 11 figure

Infection and Infertility

Infection is a multifactorial process, which can be induced by a virus, bacterium, or parasite. It may cause many diseases, including obesity, cancer, and infertility. In this chapter, we focus our attention on the association of infection and fertility alteration. Numerous studies have suggested that genetic polymorphisms influencing infection are associated with infertility. So we also review the genetic influence on infection and risk of infertility

DMV3D: Denoising Multi-View Diffusion using 3D Large Reconstruction Model

We propose \textbf{DMV3D}, a novel 3D generation approach that uses a transformer-based 3D large reconstruction model to denoise multi-view diffusion. Our reconstruction model incorporates a triplane NeRF representation and can denoise noisy multi-view images via NeRF reconstruction and rendering, achieving single-stage 3D generation in $\sim$30s on single A100 GPU. We train \textbf{DMV3D} on large-scale multi-view image datasets of highly diverse objects using only image reconstruction losses, without accessing 3D assets. We demonstrate state-of-the-art results for the single-image reconstruction problem where probabilistic modeling of unseen object parts is required for generating diverse reconstructions with sharp textures. We also show high-quality text-to-3D generation results outperforming previous 3D diffusion models. Our project website is at: https://justimyhxu.github.io/projects/dmv3d/ .Comment: Project Page: https://justimyhxu.github.io/projects/dmv3d

Electronic correlations and energy gap in the bilayer nickelate La3_{3}Ni2_{2}O7_{7}

The discovery of superconductivity with a critical temperature of 80~K in La$_{3}$Ni$_{2}$O$_{7}$ under pressure has received enormous attention. La$_{3}$Ni$_{2}$O$_{7}$ is not superconducting under ambient pressure but exhibits a density-wave-like transition at $T^{\ast} \simeq 115$~K. Understanding the electronic correlations, charge dynamics and dominant orbitals are important steps towards the mechanism of superconductivity and other instabilities. Here, our optical study shows that La$_{3}$Ni$_{2}$O$_{7}$ features strong electronic correlations which significantly reduce the electron's kinetic energy and place it in the proximity of the Mott phase. The low-frequency optical conductivity reveals two Drude components arising from multiple bands dominated by the Ni-$d_{x^2 - y^2}$ and Ni-$d_{3z^2 - r^2}$ orbitals at the Fermi level. Above $T^{\ast}$, the scattering rates for both Drude components vary linearly with temperature, indicating non-Fermi-liquid behavior which may be associated with spin-fluctuation scattering. Below $T^{\ast}$, a gap opens in the Ni-$d_{3z^2 - r^2}$ orbital, suggesting the importance of the Ni-$d_{3z^2 - r^2}$ orbital in the density-wave-like instability. Our experimental results provide key insights into the mechanism of the density-wave-like order and superconductivity in La$_{3}$Ni$_{2}$O$_{7}$.Comment: 26 pages, 4 figures, Comments are welcome and appreciate