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  1. Keypoint detection serves as the basis for many computer vision and robotics applications. Despite the fact that colored point clouds can be readily obtained, most existing keypoint detectors extract only geometry-salient keypoints, which can impede the overall performance of systems that intend to (or have the potential to) leverage color information. To promote advances in such systems, we propose an efficient multi-modal keypoint detector that can extract both geometry-salient and color-salient keypoints in colored point clouds. The proposed CEntroid Distance (CED) keypoint detector comprises an intuitive and effective saliency measure, the centroid distance, that can be used in both 3D space and color space, and a multi-modal non-maximum suppression algorithm that can select keypoints with high saliency in two or more modalities. The proposed saliency measure leverages directly the distribution of points in a local neighborhood and does not require normal estimation or eigenvalue decomposition. We evaluate the proposed method in terms of repeatability and computational efficiency (i.e. running time) against state-of-the-art keypoint detectors on both synthetic and real-world datasets. Results demonstrate that our proposed CED keypoint detector requires minimal computational time while attaining high repeatability. To showcase one of the potential applications of the proposed method, we further investigate the task of colored point cloud registration. Results suggest that our proposed CED detector outperforms state-of-the-art handcrafted and learning-based keypoint detectors in the evaluated scenes. The C++ implementation of the proposed method is made publicly available at https://github.com/UCR-Robotics/CED_Detector. 
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  2. Abstract

    Carbonic anhydrase (CA) has been shown to promote calcite dissolution (Liu, 2001,https://doi.org/10.1111/j.1755-6724.2001.tb00531.x; Subhas et al., 2017,https://doi.org/10.1073/pnas.1703604114), and understanding the catalytic mechanism will facilitate our understanding of the oceanic alkalinity cycle. We use atomic force microscopy (AFM) to directly observe calcite dissolution in CA‐bearing solution. CA is found to etch the calcite surface only when in extreme proximity (~1 nm) to the mineral. Subsequently, the CA‐induced etch pits create step edges that serve as active dissolution sites. The possible catalytic mechanism is through the adsorption of CA on the calcite surface, followed by proton transfer from the CA catalytic center to the calcite surface during CO2hydration. This study shows that the accessibility of CA to particulate inorganic carbon (PIC) in the ocean is critical in properly estimating oceanic CaCO3and alkalinity cycles.

     
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