Carbon dynamics of grasslands on the Qinghai-Tibetan Plateau may play an important role in regional and global carbon cycles. The CENTURY model (Version 4.5) is used to examine temporal and spatial variations of soil organic carbon (SOC) in grasslands on the Plateau for the period from 1960 to 2002. The model successfully simulates the dynamics of aboveground carbon and soil surface SOC at the soil depth of 0-20 cm and the simulated results agree well to the measurements. Examination of SOC for eight typical grasslands shows different patterns of temporal variation in different ecosystems in 1960-2002. The extent of temporal variation increases with the increase of SOC of ecosystem. SOC increases first and decreases quickly then during the period from 1990 to 2000. Spatially, SOC density obtained for the equilibrium condition declines gradually from the southeast to the northwest on the plateau and showed a high heterogeneity in the eastern plateau. The results suggest that (i) SOC density in the alpine grasslands shows remarkable response to climate change during the 42 years, and (ii) the net carbon exchange rate between the alpine grassland ecosystems and the atmosphere increases from 1990 to 2000 as compared with that before 1990. carbon cycle, CENTURY model, climate change, global warming, soil organic carbon.

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Interventional therapy is one of the most effective methods for diagnosing and treating vascular-related diseases at present. It relies on achieving precise and safe navigation of intravascular tools within a patient’s vasculature. Vascular Interventional Surgical Robots (VISR) can reduce surgeons’ exposure to operational hazards including radiation. However, the absence of apt position control and force feedback remains a challenge. This study presents an isomorphic master–slave VISR for precise navigation of endovascular tools viz. catheters and guidewires. The master console aids operators in issuing manipulation commands and logs feedback from the force, rotation, and translation data. The slave manipulator uses the commands received from the master platform for actual tool navigation. However, precise master–slave position control and force feedback are precursors for optimal patient outcomes. This study utilized a fuzzy-PID controller for precise tool navigation and a neural network model for resistance force modulation with 50 mN precision. Furthermore, we evaluated the performance of using the learning-based models within our VISR and compared it with the performances from conventional methods. Results show that the models enhanced the proposed robotic system with better navigation precision, faster response speed, and improved force measurement capabilities.