Publications by authors named "Lingjing Wang"

The value of the ecosystem's ultimate goods and services for human welfare and long-term economic and social development is known as the gross ecosystem product (GEP). For the study of GEP accounting, the suggested water-energy-food (WEF) nexus offers a fresh viewpoint. This work aims to build a GEP accounting index system based on WEF, investigate its spatio-temporal evolution characteristics, and assess trade-offs and synergies between and within the water, energy, and food subsystems.

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We propose a self-supervised method for partial point set registration. Although recently proposed learning-based methods demonstrate impressive registration performance on full shape observations, these methods often suffer from performance degradation when dealing with partial shapes. To bridge the performance gap between partial and full point set registration, we propose to incorporate a shape completion network to benefit the registration process.

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To better address the deformation and structural variation challenges inherently present in 3D shapes, researchers have shifted their focus from designing handcrafted point descriptors to learning point descriptors and their correspondences in a data-driven manner. Recent studies have developed deep neural networks for robust point descriptor and shape correspondence learning in consideration of local structural information. In this article, we developed a novel shape correspondence learning network, called TC-NET, which further enhances performance by encouraging the topological consistency between the embedding feature space and the input shape space.

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Malignant peripheral nerve sheath tumor (MPNST) in the nasopharynx and oropharynx has not been reported. A 3-year-old boy was referred to hospital after experiencing intermittent inspiratory dyspnea for 3 years. Preoperative imaging showed that the lymph nodes were clear.

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While urban systems demonstrate high spatial heterogeneity, many urban planning, economic and political decisions heavily rely on a deep understanding of local neighborhood contexts. We show that the structure of 311 Service Requests enables one possible way of building a unique signature of the local urban context, thus being able to serve as a low-cost decision support tool for urban stakeholders. Considering examples of New York City, Boston and Chicago, we demonstrate how 311 Service Requests recorded and categorized by type in each neighborhood can be utilized to generate a meaningful classification of locations across the city, based on distinctive socioeconomic profiles.

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