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Innovative 3D Gold Microelectrode Arrays Enhance Understanding of Neuronal Network Communication
In a recent study published in ACS Nano, a group of scientists led by Prof. CAI Xinxia from the Aerospace Information Research Institute (AIR) under the Chinese Academy of Sciences (CAS), in collaboration with international collogues, have developed an innovative approach to investigating the dynamics of neuronal networks. Utilizing three-dimensional gold microelectrode arrays, the scientists have significantly improved the ability to monitor and analyze communication within neuronal networks.
Jul 14, 2024
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Novel Cloud Monitoring Algorithm Promises Enhanced Accuracy
Researchers led by Professor HUSI Letu at the Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), have developed a novel algorithm for measuring cloud property using neutral networks. The algorithm, known as CRANN (Cloud Retrieval Algorithm based on Neural Networks), focusing on retrieving cloud fraction and cloud-top pressure from hyperspectral measurements in the O2-O2 band. The findings were published in the journal Remote Sensing of Environment.
Jul 12, 2024
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Integrating Active and Passive Microwave Satellite Data Yields More Precise and Reliable Global Soil Moisture Mapping
Researchers from the Aerospace Information Research Institute (AIR) at the Chinese Academy of Sciences (CAS), in partnership with international colleagues, have made a stride in mapping surface soil moisture across the globe. By combining data from two advanced satellite systems—the Soil Moisture Active Passive (SMAP) and the Advanced Scatterometer (ASCAT)—they aim to provide more precise and reliable soil moisture data.
Jul 08, 2024
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High-Sensitivity TMR-Based Magnetrodes Usher in New Possibilities for Brain Magnetic Field Detection
Researchers at the Aerospace Information Research Institute (AIR) with the Chinese Academy of Sciences (CAS) have introduced a novel TMR-based magnetrode design that aims to revolutionize local magnetic field detection in the brain. These magnetrodes, which integrate TMR sensors with needle-shaped silicon substrates, are designed to be inserted into the brain for in-situ monitoring.
Jul 03, 2024
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New Global Satellite Dataset Fixes Time-Related Errors in Vegetation Chlorophyll Fluorescence
Scientists have developed a satellite dataset that provides new insights into the global ecosystem health and productivity over the past 15 years. This new dataset, known as the Temporally Consistent Solar-Induced Fluorescence (TCSIF), offers a more reliable way to track changes in vegetation and photosynthesis across the globe from 2007 to 2021. The study, led by Professor LIU Liangyun from the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences, was published in Earth System Science Data.
Jun 28, 2024
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