Fine-Grained Cross-View Geo-Localization Using a Correlation-Aware Homography Estimator

In this paper, we introduce a novel approach to fine-grained cross-view geo-localization. Our method aligns a warped ground image with a corresponding GPS-tagged satellite image covering the same area using homography estimation. We first employ a differentiable spherical transform, adhering to geometric principles, to accurately align the perspective of the ground image with the satellite map. This transformation effectively places ground and aerial images in the same view and on the same plane, reducing the task to an image alignment problem. To address challenges such as occlusion, small overlapping range, and seasonal variations, we propose a robust correlation-aware homography estimator to align similar parts of the transformed ground image with the satellite image. Our method achieves sub-pixel resolution and meter-level GPS accuracy by mapping the center point of the transformed ground image to the satellite image using a homography matrix and determining the orientation of the ground camera using a point above the central axis. Operating at a speed of 30 FPS, our method outperforms state-of-the-art techniques, reducing the mean metric localization error by 21.3% and 32.4% in same-area and cross-area generalization tasks on the VIGOR benchmark, respectively, and by 34.4% on the KITTI benchmark in same-area evaluation.Comment: 19 pages. Reducing the cross-view geo-localization problem to a 2D image alignment problem by utilizing BEV transformation, and completing the alignment process with a correlation-aware homography estimator. Code: https://github.com/xlwangDev/HC-Ne

A Graph-based Relevance Matching Model for Ad-hoc Retrieval

To retrieve more relevant, appropriate and useful documents given a query, finding clues about that query through the text is crucial. Recent deep learning models regard the task as a term-level matching problem, which seeks exact or similar query patterns in the document. However, we argue that they are inherently based on local interactions and do not generalise to ubiquitous, non-consecutive contextual relationships. In this work, we propose a novel relevance matching model based on graph neural networks to leverage the document-level word relationships for ad-hoc retrieval. In addition to the local interactions, we explicitly incorporate all contexts of a term through the graph-of-word text format. Matching patterns can be revealed accordingly to provide a more accurate relevance score. Our approach significantly outperforms strong baselines on two ad-hoc benchmarks. We also experimentally compare our model with BERT and show our advantages on long documents.Comment: To appear at AAAI 202

Inactivation of Myeloma Cancer Cells by Helium and Argon Plasma Jets: The Effect Comparison and the Key Reactive Species

In plasma cancer therapy, the inactivation of cancer cells under plasma treatment is closely related to the reactive oxygen and nitrogen species (RONS) induced by plasmas. Quantitative study on the plasma-induced RONS that related to cancer cells apoptosis is critical for advancing the research of plasma cancer therapy. In this paper, the effects of several reactive species on the inactivation of LP-1 myeloma cancer cells are comparatively studied with variable working gas composition, surrounding gas composition, and discharge power. The results show that helium plasma jet has a higher cell inactivation efficiency than argon plasma jet under the same discharge power. By comparing the concentration of aqueous phase reactive species and the cell inactivation efficiency under different working gases and discharge powers, it is demonstrated that the inactivation efficiency of LP-1 myeloma cancer cells is strongly correlated with the concentration of peroxynitrite (ONOOH/ONOO-). Published by AIP Publishing

Intracellular ROS Mediates Gas Plasma-Facilitated Cellular Transfection in 2D and 3D Cultures

This study reports the potential of cold atmospheric plasma (CAP) as a versatile tool for delivering oligonucleotides into mammalian cells. Compared to lipofection and electroporation methods, plasma transfection showed a better uptake efficiency and less cell death in the transfection of oligonucleotides. We demonstrated that the level of extracellular aqueous reactive oxygen species (ROS) produced by gas plasma is correlated with the uptake efficiency and that this is achieved through an increase of intracellular ROS levels and the resulting increase in cell membrane permeability. This finding was supported by the use of ROS scavengers, which reduced CAP-based uptake efficiency. In addition, we found that cold atmospheric plasma could transfer oligonucleotides such as siRNA and miRNA into cells even in 3D cultures, thus suggesting the potential for unique applications of CAP beyond those provided by standard transfection techniques. Together, our results suggest that cold plasma might provide an efficient technique for the delivery of siRNA and miRNA in 2D and 3D culture models

NO2- and NO3- Enhance Cold Atmospheric Plasma Induced Cancer Cell Death by Generation of ONOO-

Cold atmospheric plasma (CAP) is a rapidly developed technology that has been widely applied in biomedicine especially in cancer treatment. Due to the generation of various active species in plasma, CAP could induce various tumor cells death and showed a promising potential in cancer therapy. To enhance the biological effects of gas plasma, changing the discharging parameters is the most commonly used method, yet increasing discharging power will lead to a higher possibility of simultaneously damage surrounding tissues. In this study, by adding nontoxic concentration of additional nitrite and nitrate in the medium, we found that anti-tumor effect of CAP treatment was enhanced in the same discharging parameters. By microplate reader and cell flow cytometer we measured several extracellular and intracellular RONS and found that ONOO- was mostly correlated with the enhanced cancer cell killing effect. We proposed that more nitrogen supplies such as nitrite and nitrate could increase the production of RNS especially ONOO- and resulted in a better killing effect to cancer cells. Our results provided a new strategy to enhance the antitumor effect by plasma jet treatment without changing the discharging parameters. © 2018 Author(s)