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

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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A New Adaptive Prediction Algorithm for Judicial Sentencing with Empirical Studies

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Journal of Systems science & Complexity 2025年第01期 3-20页

作者： DAI Ruifen WANG Fang GUO Lei data science institute Shandong University Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences

With the development and applications of the Smart Court System(SCS) in China, the reliability and accuracy of legal artificial intelligence have become focal points in recent years. Notably,criminal sentencing prediction, a significant component of the SCS, has also garnered widespread attention. According to the Chinese criminal law, actual sentencing data exhibits a saturated property due to statutory penalty ranges, but this mechanism has been ignored by most existing studies. Given this, the authors propose a sentencing prediction model that combines judicial sentencing mechanisms including saturated outputs and floating boundaries with neural networks. Building on the saturated structure of our model, a more effective adaptive prediction algorithm will be constructed based on the fusion of several key ideas and techniques that include the utilization of the L1 loss together with the corresponding gradient update strategy, a data pre-processing method based on large language model to extract semantically complex sentencing elements using prior legal knowledge, the choice of appropriate initial conditions for the learning algorithm and the construction of a double-hidden-layer network structure. An empirical study on the crime of disguising or concealing proceeds of crime demonstrates that our method can achieve superior sentencing prediction accuracy and significantly outperform common baseline methods.

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Assessing the corrosion protection property of coatings loaded with corrosion inhibitors using the real-time atmospheric corrosion monitoring technique

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 119-126页

作者： Xiaoxue Wang Lulu Jin Jinke Wang Rongqiao Wang Xiuchun Liu Kai Gao Jingli Sun Yong Yuan Lingwei Ma Hongchang Qian Dawei Zhang School of Energy and Power Engineering Beihang UniversityBeijing 100191China Beijing institute of Space Long March Vehicle Beijing 100076China National Materials Corrosion and Protection data Center University of Science and Technology BeijingBeijing 100083China institute of Materials Intelligent Technology Liaoning Academy of MaterialsShenyang 110004China Shanghai Spaceflight Precision Machinery institute Shanghai 201600China

The atmospheric corrosion monitoring(ACM)technique has been widely employed to track the real-time corrosion behavior of metal ***,limited studies have applied ACM to the corrosion protection properties of organic *** study compared a bare epoxy coating with one containing zinc phosphate corrosion inhibitors,both applied on ACM sensors,to observe their corrosion protection properties over *** with artificial damage via scratches were exposed to immersion and alternating dry and wet environments,which allowed for monitoring galvanic corrosion currents in *** the corrosion tests,the ACM currents of the zinc phosphate/epoxy coating were considerably lower than those of the blank epoxy *** trend in ACM current variations closely matched the results obtained from regular electrochemical tests and surface *** alignment highlights the potential of the ACM technique in evaluating the corrosion protection capabilities of organic *** with the blank epoxy coating,the zinc phosphate/epoxy coating showed much-decreased ACM current values that confirmed the effective inhibition of zinc phosphate against steel corrosion beneath the damaged coating.

关键词： atmospheric corrosion monitoring technology corrosion inhibitor coating carbon steel corrosion protection

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Dimensional-noise-aware battery lifetime prediction via an EM-TLS framework

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Progress in Natural science:Materials International 2025年第01期 146-155页

作者： Chenlong Yu Ting Lu Guohua Liu Xiaoang Zhai Wuyan Deng Jiayu Wan Yang Liu Xin Li School of Computer science and Technology Donghua University Future Battery Research Center Global Institute of Future Technology Shanghai Jiaotong University data science Research Center Duke Kunshan University

Machine learning has been massively utilized to construct data-driven solutions for predicting the lifetime of rechargeable batteries in recent years, which project the physical measurements obtained during the early charging/discharging cycles to the remaining useful lifetime. While most existing techniques train the prediction model through minimizing the prediction error only, the errors associated with the physical measurements can also induce negative impact to the prediction accuracy. Although total-least-squares(TLS) regression has been applied to address this issue, it relies on the unrealistic assumption that the distributions of measurement errors on all input variables are equivalent, and cannot appropriately capture the practical characteristics of battery degradation. In order to tackle this challenge, this work intends to model the variations along different input dimensions, thereby improving the accuracy and robustness of battery lifetime prediction. In specific, we propose an innovative EM-TLS framework that enhances the TLS-based prediction to accommodate dimension-variate errors, while simultaneously investigating the distributions of them using expectation-maximization(EM). Experiments have been conducted to validate the proposed method based on the data of commercial Lithium-Ion batteries, where it reduces the prediction error by up to 29.9 % compared with conventional TLS. This demonstrates the immense potential of the proposed method for advancing the R&D of rechargeable batteries.

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Eigen microstate analysis unveils climate dynamics

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science China(Physics,Mechanics & Astronomy) 2025年第04期Mechanics & Astronomy) .卷 95-104页

作者： Hua Tu Shang Wang Jun Meng Yongwen Zhang Xiaosong Chen Deliang Chen Jingfang Fan School of Systems science/institute of Nonequilibrium Systems Beijing Normal University Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric PhysicsChinese Academy of Sciences data science Research Center Faculty of Science Kunming University of Science and Technology Department of Earth System science Tsinghua University Department of Earth sciences University of Gothenburg Potsdam institute for Climate Impact Research

The Earth's climate operates as a complex, dynamically interconnected system, driven by both anthropogenic and natural forcings and modulated by nonlinear interactions and feedback loops. This study employs a theoretical framework and the Eigen Microstate(EM) approach of statistical physics to examine global surface temperature variations since 1948, as revealed by a global reanalysis. We identified EMs significantly correlated with key climate phenomena such as the global monsoon system,tropical climates, and El Ni no. Our analysis reveals that these EMs have increasingly influenced global surface temperature variations over recent decades, highlighting the critical roles of hemispheric differences, land-sea contrasts, and tropical climate fluctuations in a warming world. Additionally, we used model simulations from more than 10 Coupled Model Intercomparison Project Phase 6(CMIP6) under three future climate scenarios to perform a comparative analysis of the changes in each EM contribution. The results indicate that under future warming scenarios, tropical climate fluctuations will become increasingly dominant, while traditional hemispheric and monsoonal patterns may decline. This shift underscores the importance of understanding tropical dynamics and their impact on global climate from a physics-based perspective. Our study provides a new perspective on understanding and addressing global climate change, enhancing the theoretical foundation of this critical field,and yielding findings with significant practical implications for improving climate models and developing effective mitigation and adaptation strategies.

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A novel method for clustering cellular data to improve classification

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Neural Regeneration Research 2025年第9期20卷 2697-2705页

作者： Diek W.Wheeler Giorgio A.Ascoli Center for Neural informatics Structures&PlasticityKrasnow Institute for Advanced Study Bioengineering Department Volgenau School of Engineering George Mason University FairfaxVAUSA

Many fields,such as neuroscience,are experiencing the vast prolife ration of cellular data,underscoring the need fo r organizing and interpreting large datasets.A popular approach partitions data into manageable subsets via hierarchical clustering,but objective methods to determine the appropriate classification granularity are *** recently introduced a technique to systematically identify when to stop subdividing clusters based on the fundamental principle that cells must differ more between than within *** we present the corresponding protocol to classify cellular datasets by combining datadriven unsupervised hierarchical clustering with statistical *** general-purpose functions are applicable to any cellular dataset that can be organized as two-dimensional matrices of numerical values,including molecula r,physiological,and anatomical *** demonstrate the protocol using cellular data from the Janelia MouseLight project to chara cterize morphological aspects of neurons.

关键词： cellular data clustering dendrogram data classification Levene's one-tailed statistical test unsupervised hierarchical clustering

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A Correntropy-Based Echo State Network With Application to Time Series Prediction

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 425-435页

作者： Xiufang Chen Zhenming Su Long Jin Shuai Li the School of Information science and Engineering Lanzhou University IEEE the Hangzhou institute for Advanced Study University of Chinese Academy of Science

As a category of recurrent neural networks, echo state networks(ESNs) have been the topic of in-depth investigations and extensive applications in a diverse array of fields, with spectacular triumphs achieved. Nevertheless, the traditional ESN and the majority of its variants are devised in the light of the second-order statistical information of data(e.g., variance and covariance), while more information is neglected. In the context of information theoretic learning, correntropy demonstrates the capacity to grab more information from data. Therefore, under the guidelines of the maximum correntropy criterion, this paper proposes a correntropy-based echo state network(CESN) in which the first-order and higher-order information of data is captured, promoting robustness to noise. Furthermore, an incremental learning algorithm for the CESN is presented, which has the expertise to update the CESN when new data arrives, eliminating the need to retrain the network from scratch. Finally, experiments on benchmark problems and comparisons with existing works are provided to verify the effectiveness and superiority of the proposed CESN.

关键词： Correntropy echo state network (ESN) noise time series prediction

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Optical transmittance and pulse shape discrimination of polystyrene/poly(methyl methacrylate)-based plastic scintillators

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Nuclear science and Techniques 2025年第1期36卷 94-102页

作者： Yi-Yao Liang Ying-Du Liu Pu-Sen Wang Jie Bao Xiao-Ping Ouyang School of Materials science and Engineering Xiangtan UniversityXiangtan 411105China Nuclear data Key Laboratory China Institute of Atomic EnergyBeijing 102413China

Polymethyl methacrylate(PMMA)is an optically transparent thermoplastic with favorable processing *** this study,a series of plastic scintillators are prepared via thermal polymerization,and the impact of PMMA content on their transparency and pulse shape discrimination(PSD)ability is *** fabricated samples,comprising a polystyrene(PS)-PMMA matrix,30.0 wt%2,5-diphenyloxazole(PPO),and 0.2 wt%9,10-diphenylanthracene(DPA),exhibit high transparency with transmissivity ranging from 70.0 to 90.0%(above 415.0 nm)and demonstrate excellent n/γdiscrimination *** increased with increasing PMMA content across the entire visible light ***,the PSD performance gradually deteriorated when the aromatic matrix was replaced with *** scintillator containing 20.0 wt%PMMA demonstrated the best stability concerning PSD properties and relative light yields.

关键词： Neutron detection Plastic scintillation Pulse shape discrimination Polymethyl-methacrylate Polystyrene

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PriChain: Efficient Privacy-Preserving Fine-Grained Redactable Blockchains in Decentralized Settings

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Chinese Journal of Electronics 2025年第1期34卷 82-97页

作者： Hongchen Guo Weilin Gan Mingyang Zhao Chuan Zhang Tong Wu Liehuang Zhu Jingfeng Xue School of Computer science and Technology Beijing Institute of Technology School of Cyberspace science and Technology Beijing Institute of Technology School of Computer and Communication Engineering University of Science and Technology Beijing

Recently, redactable blockchain has been proposed and leveraged in a wide range of real systems for its unique properties of decentralization, traceability, and transparency while ensuring controllable on-chain data redaction. However, the development of redactable blockchain is now obstructed by three limitations, which are data privacy breaches, high communication overhead, and low searching efficiency, respectively. In this paper, we propose PriChain, the first efficient privacy-preserving fine-grained redactable blockchain in decentralized settings. PriChain provides data owners with rights to control who can read and redact on-chain data while maintaining downward compatibility, ensuring the one who can redact will be able to read. Specifically, inspired by the concept of multi-authority attribute-based encryption, we utilize the isomorphism of the access control tree, realizing fine-grained redaction mechanism, downward compatibility, and collusion resistance. With the newly designed structure, PriChain can realize O（n） communication and storage overhead compared to prior O（n2） schemes. Furthermore, we integrate multiple access trees into a tree-based dictionary, optimizing searching efficiency. Theoretical analysis proves that PriChain is secure against the chosen-plaintext attack and has competitive complexity. The experimental evaluations show that PriChain realizes 10× efficiency improvement of searching and 100× lower communication and storage overhead on average compared with existing schemes.

关键词： Resistance Access control data privacy Dictionaries Blockchains Encryption Complexity theory Usability Protection

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Security Strategy of Digital Medical Contents Based on Blockchain in Generative AI Model

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Computers, Materials & Continua 2025年第1期82卷 259-278页

作者： Hoon Ko Marek R.Ogiela Division of Computer science and Engineering Sunmoon UniversityAsan31460Republic of Korea AGH University of Krakow Cryptography and Cognitive Informatics LaboratoryKrakow30-059Poland

This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain *** combining the strengths of blockchain and generative AI,the research team aimed to address the timely challenge of safeguarding visual medical *** participating researchers conducted a comprehensive analysis,examining the vulnerabilities of medical AI services,personal information protection issues,and overall security *** multi faceted exploration led to an indepth evaluation of the model’s performance and ***,the correlation between accuracy,detection rate,and error rate was *** analysis revealed insights into the model’s strengths and limitations,while the consideration of standard deviation shed light on the model’s stability and performance *** study proposed practical improvements,emphasizing the reduction of false negatives to enhance detection rate and leveraging blockchain technology to ensure visual data integrity in medical *** blockchain to generative AI-created medical content addresses key personal information protection *** utilizing the distributed ledger system of blockchain,the research team aimed to protect the privacy and integrity of medical data especially medical *** approach not only enhances security but also enables transparent and tamperproof ***,the use of generative AI models ensures the creation of novel medical content without compromising personal information,further safeguarding patient *** conclusion,this study showcases the potential of blockchain-based solutions in the medical field,particularly in securing sensitive medical data and protecting patient *** proposed approach,combining blockchain and generative AI,offers a promising direction toward more robust and secure medical content *** research and advancements

关键词： Digitalmedical content medical diagnostic visualization security analysis generativeAI blockchain vulnerability pattern recognition

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