科研成果

Impurity-containing iron hydroxides, abundant in many natural and engineered soil and aqueous environments, control the fate and transport of multiple aqueous contaminants. Fe(III) hydroxide was reported to simultaneously detoxicate As(III) and Cr(VI). However, the mechanisms and reaction intermediates are not clear, and the effects of impurities in ferrihydrite were far from being well understood. Here, Cr(III)-incorporated Fe(III) hydroxides were precipitated from acidic solutions (pH ∼ 3.0) with varied Fe(III)/Cr(III) molar ratios (10 : 0 to 8 : 2) for simultaneous removal of As(III) and Cr(VI). Multiple characterization techniques were combined to investigate the effects of Cr-incorporation on the size, band gap, adsorption, and catalytic efficiency of Fe hydroxides. With the amounts of Cr-incorporation increasing, the particle size of Fe hydroxides rapidly decreased (from 16.7 to 6.0 nm), and the removal of total As/Cr increased, as the Cr-incorporated Fe hydroxides with smaller size had larger surface area, promoting As/Cr removal by adsorption. Based on As/Cr speciation analysis of both aqueous and solid phases, the molar ratios of the oxidized As(III) (88%) to reduced Cr(VI) (∼56%) were calculated to be ∼1.5, indicating that the coupled redox conversion was the dominant removal mechanism over As(III)/Cr(VI) adsorption and As(III) oxidation. Intermediate characterization and molecular simulation found that Cr-incorporation promoted the early formation of H2O2 and Cr(V) intermediates, and enhanced the adsorption of reaction intermediates on Cr-incorporated Fe hydroxides, thus promoting their catalytic efficiency for coupled As(III)/Cr(VI) redox reactions.

The Transformer model, particularly its cross-attention module, is widely used for feature fusion in target sound extraction which extracts the signal of interest based on given clues. Despite its effectiveness, this approach suffers from low computational efficiency. Recent advancements in state space models, notably the latest work Mamba, have shown comparable performance to Transformer-based methods while significantly reducing computational complexity in various tasks. However, Mamba’s applicability in target sound extraction is limited due to its inability to capture dependencies between different sequences as the cross-attention does. In this paper, we propose CrossMamba for target sound extraction, which leverages the hidden attention mechanism of Mamba to compute dependencies between the given clues and the audio mixture. The calculation of Mamba can be divided to the query, key and value. We utilize the clue to generate the query and the audio mixture to derive the key and value, adhering to the principle of the cross-attention mechanism in Transformers. Experimental results from two representative target sound extraction methods validate the efficacy of the proposed CrossMamba

ABSTRACT An increasing body of research has investigated the role of enjoyment in second language acquisition (SLA); however, few studies have explored whether learners of Chinese as a second/foreign language (CS/FL) experience enjoyment in learning Hanzi (Chinese characters) and how enjoyment impacts Hanzi recognition performance. To address this gap, a Hanzi Learning Enjoyment Scale was developed and administered to 446 Arabic CS/FL learners, 144 of whom also completed a Hanzi recognition test. Two key findings emerged. First, the results of factor analysis revealed four factors underlying Hanzi learning enjoyment: Hanzi culture, personal attitudes, teacher support, and personal fulfillment. Second, enjoyment did not emerge as a significant predictor of Hanzi recognition performance. Notably, the variance in Hanzi recognition scores explained by enjoyment ranked among the top three explanatory variables, comparable to the predictive power of years spent learning Chinese. This study concludes with theoretical insights into the construct of foreign language enjoyment (FLE) across different languages and language components, as well as practical recommendations for enhancing Hanzi instruction.

Bijdragen irregularly organizes a book debate. This time we chose Rudolf Mrázek, Amir Sjarifoeddin: Politics and Truth in Indonesia, 1907–1948 (2024). We invited Henk Schulte Nordholt, KanKan Xie and Faizah Zakaria to share their critical insights from this book, to which Rudolf Mrázek responds.

https://arxiv.org/abs/2312.01848

Existing diffusion models for low-light image enhancement typically incrementally remove noise introduced during the forward diffusion process using a denoising loss, with the process being conditioned on input low-light images. While these models demonstrate remarkable abilities in generating realistic high-frequency details, they often struggle to restore fine details that are faithful to the input. To address this, we present a novel detail-preserving diffusion model for realistic and faithful low-light image enhancement. Our approach integrates a size-agnostic diffusion process with a reverse process reconstruction loss, significantly enhancing the fidelity of enhanced images to their low-light counterparts and enabling more accurate recovery of fine details. To ensure the preservation of region- and content-aware details, we employ an efficient noise estimation network with a simplified channel-spatial attention mechanism. Additionally, we propose a multiscale ensemble scheme to maintain detail fidelity across diverse illumination regions. Comprehensive experiments on eight benchmark datasets demonstrate that our method achieves state-of-the-art results compared to over twenty existing methods in terms of both perceptual quality (LPIPS) and distortion metrics (PSNR and SSIM). The code is available at: https://github.com/CSYanH/DePDiff.

Surface ozone (O3) pollution affects air quality, human health, and the ecosystem. Understanding the complex non-linear relationship between ozone formation and its precursors, nitrogen oxides (NOx), and volatile organic compounds (VOCs) is critical for policymakers to mitigate the pollution. The Empirical Kinetic Modeling Approach (EKMA) based on classical observation-constrained zero-dimension box model provides the sensitivity of ozone production to precursor concentrations instead of emissions. This makes the box-model EKMA hard to apply in a real emission reduction scenario. Here, we developed an alternative box model approach driven by localized emissions, which are derived from the field-observed concentrations. This model approach reproduced the O3 variations well by capturing the short-term changes of NOx and AVOCs emissions among different phases of pollution control during the 31st World University Games in Chengdu in 2023. The EKMA analysis based on this model approach showed a different O3 response to precursor reductions from the concentration-constrained approach, which overestimated the baseline of O3 concentration. The result from the EKMA analysis demonstrated that the O3 level was most sensitive to NOx due to stringent control strategies during the event and rapidly rebounded to almost VOC-limited regime after the event. The effects of VOCs reduction on O3 control examined by concentration-constrained model approach were less pronounced than those by emission-driven approach due to the lack of consideration of the emission-to-reaction process. Our findings suggest that the emission-driven box model is applicable for developing O3 control strategy in the local scale.

In the context of supply chain digitization and green development in full swing, it is crucial to clarify the impact of the former on green energy innovation. Using exogenous shocks deriving from supply chain innovation and application pilot events, this study examines the impact of supply chain digitization on green energy innovation based on the data of Chinese listed companies from 2012 to 2021. The findings show that supply chain digitization significantly enhances corporate green energy innovation and that receivable asset management is a path mechanism for supply chain digitization to drive green energy innovation. Moreover, there is a significant positive intra-city spillover. Supply chain digitization contributes significantly to corporate green energy innovation in state-controlled manufacturing firms with effective internal controls in the eastern region. This study has important policy implications for promoting green energy innovation and accelerating the development of modern supply chain systems.