H2-Mapping: Real-time Dense Mapping Using Hierarchical Hybrid Representation

Constructing a high-quality dense map in real-time is essential for robotics, AR/VR, and digital twins applications. As Neural Radiance Field (NeRF) greatly improves the mapping performance, in this paper, we propose a NeRF-based mapping method that enables higher-quality reconstruction and real-time capability even on edge computers. Specifically, we propose a novel hierarchical hybrid representation that leverages implicit multiresolution hash encoding aided by explicit octree SDF priors, describing the scene at different levels of detail. This representation allows for fast scene geometry initialization and makes scene geometry easier to learn. Besides, we present a coverage-maximizing keyframe selection strategy to address the forgetting issue and enhance mapping quality, particularly in marginal areas. To the best of our knowledge, our method is the first to achieve high-quality NeRF-based mapping on edge computers of handheld devices and quadrotors in real-time. Experiments demonstrate that our method outperforms existing NeRF-based mapping methods in geometry accuracy, texture realism, and time consumption. The code will be released at: https://github.com/SYSU-STAR/H2-MappingComment: Accepted by IEEE Robotics and Automation Letter

Where to draw the line? Using movement data to inform protected area design and conserve mobile species

Protected areas (PAs) are a cornerstone of modern conservation. For PAs that are established to conserve mobile species, it is important to cover all the key areas regularly used by these species. However, zonation and boundaries of PAs have often been established with limited knowledge of animal movements, leaving the effectiveness of some PAs doubtful. We used radio tracking data to evaluate the extent to which two coastal PAs in mainland China encompassed the full range of habitats used by migratory shorebirds during non-breeding seasons. The core zone (highest restriction on human activities) of the Yalu Jiang Estuary National Nature Reserve (Liaoning) incorporated only 22 ± 6% (n = 34) of the diurnal home range (95% kernel density) of the endangered great knots Calidris tenuirostris. In contrast, the core zone of Chongming Dongtan (Shanghai) incorporated 73 ± 24% (n = 25) of the home range of dunlins Calidris alpina. During high tide, great knots in Yalu Jiang mostly occurred in the experimental zone (least restriction on human activities) or sometimes outside the PA boundary altogether, where the birds could face substantial threats. By investigating satellite tracking records, consulting published literature, interviewing local experts and mapping habitat composition in different coastal PAs in China, we found that wet artificial supratidal habitats were frequently used by migratory shorebirds but the coverage of these habitats in coastal PAs was low. These PA boundaries and/or zonations should be revised to conserve mobile species more effectively. With the increasing number of tracking studies, analysing the spatial relationships between PAs and the movement ranges of mobile species can increasingly inform the development of a representative, comprehensive PA network

Digital image analysis allows objective stratification of patients with silent PIT1‐lineage pituitary neuroendocrine tumors

Abstract Studies describing the clinical presentation and prognosis of patients with silent PIT1 (pituitary specific transcription factor)‐lineage pituitary neuroendocrine tumors (PitNETs) are rare. We identified patients with positive PIT1 tumor staining but without evidence of hormone hypersecretion at a tertiary center. Clusters were obtained according to cell morphology and immunostaining from each patient's digitally segmented whole slide image. We compared the clinical presentations, radiological features, and prognoses of the different clusters. We identified 146 patients (68 male, 42.9 ± 14.1 years old) with silent PIT1‐lineage PitNETs. Morphology clustering suggested that tumors with large nuclei and apparent eccentricity were associated with a higher proportion of aggressiveness and a higher hazard of recurrence [hazard ratio (HR): 2.64, (95% CI, 1.06–6.55), p = 0.037]. Immunohistochemical clustering suggested that tumors with thyroid stimulating hormone (TSH) staining or all negative PIT1‐lineage hormones were associated with a higher proportion of aggressiveness and a higher risk of recurrence [HR: 12.4, (95% CI, 1.60–93.5), p = 0.015]. We obtained three‐tier risk profiles by combining morphological and immunohistochemical clustering. Patients with the high‐risk profile presented the highest recurrence rate compared with those in the medium‐risk and low‐risk profiles [HR: 3.54, (95% CI, 1.40–8.93), p = 0.002]. In conclusion, digital image analysis based on cell morphology and immunohistochemical staining allows objective stratification of patients with silent PIT1‐lineage tumors. Typical morphological characteristics of high‐risk tumors are large tumor nuclei and high eccentricity, and typical immunostaining characteristics are TSH staining or negative staining for all PIT1‐lineage hormones