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Structural designs and mechanism insights into electrocatalytic oxidation of 5-hydroxymethylfurfural

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Journal of Energy Chemistry 2025年第1期100卷 792-814页

作者： Jing Lei Huijie Zhang Jian Yang Jia Ran Jiqiang Ning Haiyan Wang Yong Hu key laboratory of the Ministry of Education for Advanced Catalysis Materials Department of Chemistry Zhejiang Normal University Jinhua Advanced Research Institute Department of optical science and Engineering Fudan University College of Chemistry and Materials Engineering Zhejiang A&F University

Biomass conversion offers an efficient approach to alleviate the energy and environmental *** oxidation of 5-hydroxymethylfurfural(HMF) has attracted tremendous attention in the latest few years for the mild synthesis conditions and high conversion efficiency to obtain 2,5-furan dicarboxylic acid(FDCA), but there still remain problems such as limited yield, short cycle life,and ambiguous reaction mechanism. Despite many reviews highlighting a variety of electrocatalysts for electrochemical oxidation of HMF, a detailed discussion of the structural modulation of catalyst and the underlying catalytic mechanism is still lacking. We herein provide a comprehensive summary of the recent development of electrochemical oxidation of HMF to FDCA, particularly focusing on the mechanism studies as well as the advanced strategies developed to regulate the structure and optimize the performance of the electrocatalysts, including heterointerface construction, defect engineering,single-atom engineering, and in situ reconstruction. Experimental characterization techniques and theoretical calculation methods for mechanism and active site studies are elaborated, and challenges and future directions of electrochemical oxidation of HMF are also prospected. This review will provide guidance for designing advanced catalysts and deepening the understanding of the reaction mechanism beneath electrochemical oxidation of HMF to FDCA.

关键词： Structural design

ImSpiRE: image feature-aided spatial resolution enhancement method

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science China Life sciences 2025年第1期68卷 272-283页

作者： Yuwei Hua Yizhi Zhang Zhenming Guo Shan Bian Yong Zhang State key laboratory of Cardiovascular Diseases and Medical Innovation Center Institute for Regenerative MedicineDepartment of NeurosurgeryShanghai East HospitalShanghai Key Laboratory of Signaling and Disease ResearchFrontier Science Center for Stem Cell ResearchSchool of Life Sciences and TechnologyTongji University

The resolution of most spatially resolved transcriptomic technologies usually cannot attain the single-cell level, limiting their applications in biological discoveries. Here, we introduce ImSpiRE, an image feature-aided spatial resolution enhancement method for in situ capturing spatial transcriptome. Taking the information stored in histological images, ImSpiRE solves an optimal transport problem to redistribute the expression profiles of spots to construct new transcriptional profiles with enhanced resolution, together with extending the gene expression profiles into unmeasured regions. Applications to multiple datasets confirm that ImSpiRE can enhance spatial resolution to the subspot level while contributing to the discovery of tissue domains, signaling communication patterns, and spatiotemporal characterization.

关键词： spatial transcriptome histological images spatial resolution enhancement

A stretchable, ionic conductive, and adhesive patch electrode with ultra-low on-skin impedance for electrophysiological signal recording

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science China(information sciences) 2025年

作者： Yang LI Yuzhe GU Sheng QIAN Yuncong PANG Aoxi YU Shuwen ZHENG Wenjie XIA Yuan LIAO Baoguang LIU Shujuan LIU Qiang ZHAO College of Electronic and optical Engineering & College of Flexible Electronics (Future technology) Nanjing University of Posts & Telecommunications (NJUPT) State key laboratory of Organic Electronics and information Displays & Jiangsu key laboratory for Biosensors Institute of Advanced Materials (IAM) Nanjing University of Posts & Telecommunications (NJUPT)

Flexible electrodes have significant potential in fields such as healthcare and neuroscience, as they enable comprehensive recording and analysis of human electrical signals, providing deeper insights into physiological conditions and the state of internal organs and tissues [1, 2]. However, commercial Ag/AgCl wet electrodes face issues such as dehydration,poor comfort, and insufficient mechanical strength, while other types of electrodes, like dry and semi-dry electrodes,also have their own limitations, including the higher contact impedance. In contrast, ionically conductive electrodes offer potential advantages such as transparency, stability, and low impedance, making them a promising alternative to existing electrically conductive electrodes [3]. Acrylic acid (AA)and 2-acrylamido-2-methylpropanesulfonic acid (AMPS) are commonly used in the synthesis of ionic gels, as they ionize in water to produce a large number of ions, helping to maintain moisture balance and reduce impedance caused by dehydration [4]. However, the presence of freely moving ions in the gel network can interfere with conductivity, highlighting the need to introduce new conductive networks to enhance performance [5].

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High-precision magnetic field measurement system based on a coherent population trapping magnetometer onboard the SATech-01 satellite

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science China Technological sciences 2025年

作者： Hongbo XUE Wei SONG Haoran ZHAO Yiteng ZHANG Shanzhi YE Jindong WANG Ran TAO Peng SANG Keli CHEN Xingzi BI Bingjun CHENG Bin ZHOU Yongliang XUE Yingying TANG Liu LIU Jinsong LI Xiaocheng ZHU Baoquan LI Jinguo LIU Wen CHEN Xiaofeng ZHANG Yonghe ZHANG Lei LI State key laboratory of Space Weather National Space Science Center Chinese Academy of Sciences key laboratory of Solar Activity and Space Weather National Space Science Center Chinese Academy of Sciences key laboratory of Electronics and information technology for Space Systems National Space Science Center Chinese Academy of Sciences State key laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Innovation Academy for microsatellites Chinese Academy of Sciences

On July 27, 2022, a high-precision system for measuring the magnetic field based on a coherent population trapping magnetometer（referred to as the CPT system） was launched onboard the Space Advanced technology demonstration satellite（SATech-01） by a ZK-1A rocket. The payload comprises a scalar coherent population trapping magnetometer（CPTM）, triaxial anisotropic magnetoresistance magnetometer（AMRM）, and nano star tracker mounted on a non-magnetic telescopic tubular mast. This configuration enables synchronized measurement of scalar and vector geomagnetic fields, as well as the attitude,making the payload with its compact sensors suitable for applications on miniature satellite platforms. On November 7, 2022,the novel telescopic tubular mast was deployed in orbit, extending to a length of 5.28 m. The CPTM, an absolute scalar magnetometer with an omnidirectional sensor, is the first China-developed quantum/atomic magnetometer successfully operating in space. In orbit, the CPTM has sensitivity of ～10 pT/Hz1/2and can automatically operate under complex magnetic field variations. The difference between the scalar fields obtained using the CPTM and CHAOS model has a mean deviation of–3.73 n T and a standard deviation of 26.11 nT（1σ）, without on-orbit calibration or correction. The miniaturized AMRM has a sensitivity of ～0.3 n T/Hz1/2and maintains stable and reliable operation in orbit. The low-power and miniaturized nano star tracker has a measurement uncertainty of 14.23″（1σ） in orbit. The mission has realized the on-orbit technical verification of the integrated and synchronized detection of the vector magnetic field and attitude and fully validated the system's performance,automation level, and reliability.

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Alkaline leaching mechanism of MSWI bottom ash: the pivotal role of Si(Al) chemical bonding environments

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science China Technological sciences 2025年

作者： Ningning SHAO Zekun JIAO Weipeng FENG Yu JIN Fanlong KONG Zhijun DONG Zuotai ZHANG Institute of technology for Marine Civil Engineering Shenzhen Institute of Information Technology (SZIIT) Guizhou NASH Ecological technology Co. LTD School of Environmental science and Engineering Key Laboratory of Municipal Solid Waste Recycling Technology and Management of Shenzhen City Southern University of Science and Technology (SUSTech)

Municipal solid waste incineration bottom ash(MSWIBA) is a complex assemblage of aluminosilicate materials encompassing diverse solid wastes. Thus, its complexity poses great challenges to their resource utilization. For the sake of the alkali activation use of MSWIBA, this work focused on the characterizations and alkaline leaching experiments of various classified MSWIBA after sorting. Among the different categories of MSWIBA, waste glass(BA-G) and other unidentified slags(BA-O) were identified as potential precursors for alkali activation use. The alkaline leaching experiments proved that alkaline concentration, reaction temperature, reaction time, and raw material classification influenced the leaching process and results. Among these, the Si/Al chemical bonding environments from the material type played a pivotal role. When the materials had Qn(n>2) as the primary bonding structure, steric hindrance by the chain frameworks affected the alkali dissolution process, resulting in gradual disintegration from the outer layers inward. For the materials dominated by Q1frameworks, OH-could penetrate the frameworks, leading to their rapid depolymerization and outward dissolution. Overall, the Si/Al bonding environment played a crucial role in alkaline dissolution, providing theoretical guidance for classifying the alkali-activation utilization of MSWIBA and other aluminosilicate solid wastes.

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COMPrompter: reconceptualized segment anything model with multiprompt network for camouflaged object detection

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science China(information sciences) 2025年第1期68卷 189-203页

作者： Xiaoqin ZHANG Zhenni YU Li ZHAO Deng-Ping FAN Guobao XIAO Zhejiang Province key laboratory of Intelligent Informatics for Safety and Emergency Wenzhou University Nankai International Advanced Research Institute (SHENZHEN FUTIAN) College of Computer science Nankai University School of Computer science and technology Tongji University

We rethink the segment anything model(SAM) and propose a novel multiprompt network called COMPrompter for camouflaged object detection(COD). SAM has zero-shot generalization ability beyond other models and can provide an ideal framework for COD. Our network aims to enhance the single prompt strategy in SAM to a multiprompt strategy. To achieve this, we propose an edge gradient extraction module, which generates a mask containing gradient information regarding the boundaries of camouflaged objects. This gradient mask is then used as a novel boundary prompt, enhancing the segmentation process. Thereafter, we design a box-boundary mutual guidance module, which fosters more precise and comprehensive feature extraction via mutual guidance between a boundary prompt and a box prompt. This collaboration enhances the model's ability to accurately detect camouflaged objects. Moreover, we employ the discrete wavelet transform to extract high-frequency features from image embeddings. The high-frequency features serve as a supplementary component to the multiprompt ***, our COMPrompter guides the network to achieve enhanced segmentation results, thereby advancing the development of SAM in terms of COD. Experimental results across COD benchmarks demonstrate that COMPrompter achieves a cutting-edge performance, surpassing the current leading model by an average positive metric of 2.2% in COD10K. In the specific application of COD, the experimental results in polyp segmentation show that our model is superior to top-tier methods as well. The code will be made available at https://***/guobaoxiao/COMPrompter.

关键词： segment anything model camouflaged object detection boundary prompt

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Fractal autoencoder with redundancy regularization for unsupervised feature selection

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science China(information sciences) 2025年

作者： Meiting SUN Fangyu LI Honggui HAN School of information science and technology Beijing University of Technology Beijing key laboratory of Computational Intelligence and Intelligent System Engineering Research Center of Digital Community Ministry of Education Beijing Institute of Artificial Intelligence(Beijing)

Feature selection is a crucial step in data preprocessing because feature selection reduces the dimensionality of data by eliminating irrelevant and redundant features. Since manual labeling is expensive, unsupervised feature selection has received increasing attention in recent years. However, existing unsupervised feature selection methods tend to prioritize selecting highly correlated features over exploring feature diversity. Thus, a regularized fractal autoencoder (RFAE) method is proposed to select informative features in an unsupervised way. Specifically, the fractal autoencoder network extends autoencoders to construct a correspondence neural network and a selection neural network. The correspondence neural network exploits interfeature correlations and the selection neural network selects the informative features. A redundancy regularization strategy consists of a redundancy elimination regularization term based on the dependency between features and a sparse regularization term based on the group lasso. The redundancy regularization strategy eliminates feature subset redundancy and enhances network generalization ability. Extensive experimental results on six publicly available datasets show that the proposed RFAE outperforms the compared methods regarding clustering accuracy and classification accuracy. Moreover, the proposed RFAE achieves acceptable computation efficiency.

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RepColor: deep coloring algorithm combining semantic categories

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Optoelectronics Letters 2025年

作者： Lei Sun Dongjie Ju School of Electrical Engineering and Automation， tianjin University of technology tianjin key laboratory for Control Theory and Complicated Industry Systems， tianjin University of technology

Image coloring is an inherently uncertain and multimodal problem. By inputting a grayscale image into a coloring network， visually plausible colored photos can be generated. Conventional methods primarily rely on semantic information for image colorization. Although effective in coloring images with clear semantic information， these methods still suffer from color contamination and semantic confusion. This is largely due to the limited capacity of convolutional neural networks to effectively learn deep semantic information inherent in *** this paper， we propose a network structure that addresses these limitations by leveraging multi-level semantic information classification and fusion. Additionally， we introduce a global semantic fusion network to combat the issues of color contamination. The proposed coloring encoder accurately extracts object-level semantic information from *** further enhance visual plausibility， we employ a self-supervised adversarial training method. We train the network structure on various datasets with varying amounts of data and evaluate its performance using the ImageNet validation set and COCO validation set. Experimental results demonstrate that our proposed RepColor can generate more realistic images compared to previous approaches， showcasing its high generalization ability.

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Software-defined process-near-memory architecture using 3D hybrid bonding integration

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science China(information sciences) 2025年第1期68卷 366-378页

作者： Anlin XU Chenchen DENG Jianfeng ZHU Yao WANG Shaojun WEI Leibo LIU School of Integrated Circuits Tsinghua University Beijing Institution of Tracking and Communication technology Beijing National Research Center for information science and technology Tsinghua University

With the unprecedented explosive growing amount of global data, the development of computing chips, which encounter bottlenecks such as power wall and memory wall, cannot satisfy the demanding requirement. This work proposes a software-defined process-near-memory(SDPNM) computing architecture implemented using 3D hybrid bonding *** software-defined chip architecture, featuring spatial computations and dynamic reconfiguration, innovates in a top-down manner to achieve high energy efficiency while maintaining flexibility after fabrication. The process-near-memory integration further advances the SDNPM chip in a bottom-up way to reduce the energy consumption of data movement while improving the bandwidth. Utilizing a relatively mature fabrication and bonding process can result in feasible solutions for both data-intensive and compute-intensive applications including digital signal processing and artificial intelligence. The logic die is fabricated in the SMIC 40 nm process and the DRAM die is fabricated in the PSMC 25 nm process. The hybrid bonding is implemented by XMC. The experimental results show that the energy efficiency of the proposed SDPNM chip is 33.1× better than the state-of-the-art FPGA ranging from 8.2× to 104.1×.

关键词： software-defined chips process near memory energy efficiency dynamic reconfiguration domain specific

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