科研成果

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.

Abstract Subsurface gas storage is crucial for achieving a sustainable energy future, as it helps to reduce CO2 emissions and facilitates the provision of renewable energy sources. The confinement effect of the nanopores in caprock induces distinctive thermophysical properties and fluid dynamics. In this paper, we present a multi-scale study to characterize the subsurface transport of CO2, CH4, and H2. A nanoscale-extended volume-translated Cubic-Plus-Association equation of state was developed and incorporated in a field-scale numerical simulation, based on a full reservoir-caprock suite model. Results suggest that in the transition from nanoscale to bulk-scale, gas solubility in water decreases while phase density and interfacial tension increase. For the first time, a power law relationship was identified between the capillary pressure within nanopores and the pore size. Controlled by buoyancy, viscous force and capillary pressure, gases transport vertically and horizontally in reservoir and caprock. H2 has the maximum potential to move upward and the lowest areal sweep efficiency; in short term, CH4 is more prone to upward migration compared to CO2, while in long term, CH4 and CO2 perform comparably. Thicker caprock and larger caprock pore size generally bring greater upward inclination. Gases penetrate the caprock when CH4 is stored with a caprock thickness smaller than 28 m or H2 is stored with a caprock pore size of 2–10 nm or larger than 100 nm. This study sheds light on the fluid properties and dynamics in nanoconfined environment and is expected to contribute to the safe implementation of gigatonne scale subsurface gas storage.

Fragmentation and evolution for the molecular shells of the compact H ii regions are less explored compared to their evolved counterparts. We map nine compact H ii regions with a typical diameter of 0.4 pc that are surrounded by molecular shells traced by CCH. Several to a dozen dense gas fragments probed by H13CO+ are embedded in these molecular shells. These gas fragments, strongly affected by the H ii region, have a higher surface density, mass, and turbulence than those outside the shells but within the same pc-scale natal clump. These features suggest that the shells swept up by the early H ii regions can enhance the formation of massive dense structures that may host the birth of higher-mass stars. We examine the formation of fragments and find that fragmentation of the swept-up shell is unlikely to occur in these early H ii regions, by comparing the expected time scale of shell fragmentation with the age of H ii region. We propose that the appearance of gas fragments in these shells is probably the result of sweeping up pre-existing fragments into the molecular shell that has not yet fragmented. Taken together, this work provides a basis for understanding the interplay of star-forming sites with an intricate environment containing ionization feedback such as those observed in starburst regions.

Automotive audio systems often face sub-optimal sound quality due to the intricate acoustic properties of car cabins. Acoustic channel equalization methods are generally employed to improve sound reproduction quality in such environments. In this paper, we propose an acoustic channel equalization method using convex optimization in the modal domain. The modal domain representation is used to model the whole sound field to be equalized. Besides integrating it into the convex formulation of the acoustic channel reshaping problem, to further control the prering artifacts, the temporal window function modified according to the backward masking effect of the human auditory system is used during equalizer design. Objective and subjective experiments in a real automotive cabin proved that the proposed method enhances spatial robustness and avoids the audible prering artifacts.

The collapse of the former Soviet Union signaled failure of large-scale experiment in communitarian property. Privatization reform consequently was taken as the start point to transfer the planned economy to a market economy by the post socialist countries. This also occurred in economic transition countries such as China. However, in overcoming the tragedy of the commons privatization might create anticommons problems. Here we develop a nested common-private interface framework from the perspective of resource system and resource units and apply this framework to explain reforms of rangeland property in China and Kyrgyzstan. We confirmed that the root of the dilemma, either caused by commons or anticommons, can be attributed to the interface mismatch between individual elements and common elements. Trying to overcome the dilemma by changing property arrangements alone cannot eliminate the incentive mismatch caused by the common-private interface. Institutions aimed at alleviating the mismatch are accordingly required. Theoretically, this framework converts Ostrom's concept of commons into liberal commons that the members have options to exit, which is becoming increasingly common in the current global context of marketization. In the real world, this framework can serve to understand the property reform progress of transition countries, and may enlighten future property reforms.

With the big popularity and success of Judea Pearl's original causality book, this review covers the main topics updated in the second edition in 2009 and illustrates an easy-to-follow causal inference strategy in a forecast scenario. It further discusses some potential benefits and challenges for causal inference with time series forecasting when modeling the counterfactuals, estimating the uncertainty and incorporating prior knowledge to estimate causal effects in different forecasting scenarios.

Horizontally aligned carbon nanotube (HACNT) arrays hold significant potential for various applications in nanoelectronics and material science. However, their high-throughput characterization remains challenging due to the lack of methods with both high efficiency and high accuracy. Here, we present a novel technique, Calibrated Absolute Optical Contrast (CAOC), achieved through the implementation of differential principles to filter out stray signals and high-resolution calibration to endow optical contrast with physical significance. CAOC offers major advantages over previous characterization techniques, providing consistent and reliable measurements of HACNT array density with high throughput and non-destructive assessment. To validate its utility, we demonstrate wafer-scale uniformity assessment by rapid density mapping. This technique not only facilitates the practical evaluation of HACNT arrays but also provides insights into balancing high throughput and high resolution in nanomaterial characterization.

Textual information from online news is more timely than insurance claim data during catastrophes, and there is value in using this information to achieve earlier damage estimates. In this paper, we use text-based information to predict the duration and severity of catastrophes. We construct text vectors through Word2Vec and BERT models, using Random Forest, LightGBM, and XGBoost as different learners, all of which show more satisfactory prediction results. This new approach is informative in providing timely warnings of the severity of a catastrophe, which can aid decision-making and support appropriate responses.