This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
A research team led by Prof. Liu Liangyun from the Aerospace Information Research Institute of the Chinese Academy of ...
🌟 Tip: With GIS MCP Server, your AI can now “think spatially,” unlocking new capabilities for environmental analysis, mapping, and location intelligence.
In the race to deliver faster, smarter, and more resilient networks, CSP and telco leaders are finding a powerful ally in geospatial innovation. Once used primarily for emergency response and basic ...
What does geospatial science look like at Audubon California in 2025? It starts at the Salton Sea, where our science is helping move roughly 2,000 acres of wetland habitat toward restoration planning.
Abstract: Geospatial data are often uncertain due to measurement, spatial, or temporal limitations. A knowledge gap exists about how geospatial uncertainty visualization techniques influence human ...
Remotely sensed geospatial data are critical for applications including precision agriculture, urban planning, disaster monitoring and response, and climate change research, among others. Deep ...
Acquiring, processing, and visualizing geospatial data requires significant computing resources, especially for large spatio-temporal domains. This challenge hinders the rapid discovery of predictive ...
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