科研成果

Hyperspectral imaging plays a critical role in numerous scientific and industrial fields. Conventional hyperspectral imaging systems often struggle with the trade-off between spectral and temporal resolution, particularly in dynamic environments. In ours work, we present an innovative event-based active hyperspectral imaging system designed for real-time performance in dynamic scenes. By integrating a diffraction grating and rotating mirror with an event-based camera, the proposed system captures high-fidelity spectral information at a microsecond temporal resolution, leveraging the event camera's unique capability to detect instantaneous changes in brightness rather than absolute intensity. The proposed system trade-off between conventional frame-based systems by reducing the bandwidth and computational load and mosaic-based system by remaining the original sensor spatial resolution. It records only meaningful changes in brightness, achieving high temporal and spectral resolution with minimal latency and is practical for real-time applications in complex dynamic conditions.

Alquimia v1.0 is a generic interface to geochemical solvers that facilitates development of multiphysics simulators by enabling code coupling, prototyping and benchmarking. The interface enforces the function arguments and their types for setting up, solving, serving up output data and carrying out other common auxiliary tasks while providing a set of structures for data transfer between the multiphysics code driving the simulation and the geochemical solver. Alquimia relies on a single-cell approach that permits operator splitting coupling and parallel computation. We describe the implementation in Alquimia of two widely used open-source codes that perform geochemical calculations: PFLOTRAN and CrunchFlow. We then exemplify its use for the implementation and simulation of reactive transport in porous media by two open-source flow and transport simulators: Amanzi and ParFlow. We also demonstrate its use for the simulation of coupled processes in novel multiphysics applications including the effect of multiphase flow on reaction rates at the pore scale with OpenFOAM, the role of complex biogeochemical processes in land surface models such as the E3SM Land Model (ELM) and the impact of surface–subsurface hydrological interactions on hydrogeochemical export from watersheds with the Advanced Terrestrial Simulator (ATS). These applications make it apparent that the availability of a well-defined yet flexible interface has the potential to improve the software development workflow, freeing up resources to focus on advances in process models and mechanistic understanding of coupled problems.

This study explores how L1 and L2 Chinese speakers use world knowledge and classifier information to predict fine-grained referent features. In a visual-world-paradigm eye-tracking experiment, participants were presented with two visual objects that were denoted by the same noun in Chinese but matched different shape classifiers. Meanwhile, they heard sentences containing world knowledge triggering context and classifiers. The effect of world knowledge has been differentiated from word-level associations. Native speakers generated anticipations about the shape/state features of the referents at an early processing stage and quickly integrated linguistic information with world knowledge upon hearing the classifiers. In contrast, L2 speakers show delayed, reduced anticipation based on world knowledge and minimal use of classifier cues. The findings reveal different cue-weighting strategies in L1 and L2 processing. Specifically, L2 speakers whose first languages lack obligatory classifiers do not employ classifier cues in a timely manner, even though the semantic meanings of shape classifiers are accessible to them. No evidence supports over-reliance on world knowledge in L2 processing. This study contributes to the understanding of L2 real-time processing, particularly in L2 speakers’ utility of linguistic and non-linguistic information in anticipating fine-grained referent features.