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CMM-EmbedCluster:a clustering framework for Chinese materia medica based on large language model and Chinese materia medica property theory 认领 引用
1
作者 Jiayi He Jiadong Xie +1 位作者 Kongfa Hu Haiyan Li 《Digital Chinese Medicine》 CAS CSCD 2026年第2期278-289,共12页
Objective This study proposes a clustering framework for Chinese materia medica(CMM)based on a large language model(LLM),aiming to explore potential compatibility patterns among CMMs from the semantic perspective of C... Objective This study proposes a clustering framework for Chinese materia medica(CMM)based on a large language model(LLM),aiming to explore potential compatibility patterns among CMMs from the semantic perspective of CMM property theory.Methods First,a CMM property knowledge base was constructed based on Chinese Materia Medica,including 567 commonly used CMMs characterized by four properties,five flavors,and meridian tropism.Then,49 CMMs derived from 10 prescriptions for Zangdu(脏毒,pathogenic toxins)recorded in Waike Zhengzong(《外科正宗》,Orthodox Manual of External Medicine)and Yangke Xinde Ji(《疡科心得集》,Collected Insights on Ulcer Medicine)were selected as the experimental dataset.Five semantic representation methods—One-Hot,Word2Vec,Bidirectional Encoder Representations from Transformers(BERT),Beijing Academy of Artificial Intelligence General Embedding(BGE),and Qwen—were applied to encode CMM property information into vector representations.Subsequently,t-distributed Stochastic Neighbor Embedding(t-SNE)was used for nonlinear dimensionality reduction on high-dimensional semantic vectors,followed by k-means clustering(k=7).Clustering performance was evaluated using the Silhouette Score(SS),Davies-Bouldin Index(DBI),and Calinski-Harabasz Index(CHI).Results The Qwen-based clustering method,CMM-EmbedCluster,achieved the highest SS(0.6074)and CHI(158.0572),as well as the lowest DBI(0.4995),indicating improved cluster separation and compactness compared with other methods.Visualization of CMM clustering results showed that the clusters were well separated in the low-dimensional space,with strong inter-cluster discrimination and high intra-cluster functional consistency.Further interpretability analysis of CMM clustering results revealed stable structural differences among clusters in terms of four properties,five flavors,and meridian tropism,forming functional partitions consistent with CMM property theory.Conclusion CMM-EmbedCluster utilizes an LLM to achieve semantic-level representation and clustering of CMMs within the framework of CMM property theory,providing support for exploring potential compatibility patterns among CMMs from the perspective of CMM property semantics. 展开更多
关键词 Large language model Chinese materia medica property theory Chinese materia medica clustering Semantic representation k-Means clustering CMM-EmbedCluster
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Support Vector Clustering Uncovered:Insights,Challenges,and Future Outlook 认领 引用
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作者 M.Tanveer Mohammad Tabish +2 位作者 Anuradha Kumari Ashwani Kumar Malik Weiping Ding 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第4期749-775,共27页
Support vector clustering(SVC)has emerged as a powerful unsupervised learning technique,derived from support vector machines(SVMs),offering a robust solution to a wide range of complex clustering challenges.Its unique... Support vector clustering(SVC)has emerged as a powerful unsupervised learning technique,derived from support vector machines(SVMs),offering a robust solution to a wide range of complex clustering challenges.Its unique ability to handle noise,outliers,and clusters of diverse,irregular shapes sets it apart from traditional clustering methods.SVC's distinct advantage lies in its capacity to autonomously determine the optimal number of clusters without prior topological knowledge of the data.SVC maps data to a higher-dimensional space,encloses it in a minimal sphere,and identifies clusters when mapped back,supporting complex shapes and ensuring optimality through kernel functions.This review paper provides a comprehensive analysis of the SVC algorithms,exploring their variants such as robust,sparse,and fuzzy-based models and adaptations for large-scale data.Moreover,we analyze the potential of twin support vector clustering(TWSVC),with an emphasis on the use of various loss functions.Finally,the paper explores emerging trends and outlines promising future research directions for both SVC and twin SVC.These include advancements in feature engineering,extension to semi-supervised and weakly supervised learning,and the integration of multi-view and multi-modal data.Our work aims to deepen the understanding of SVC,fostering advancements that address the evolving needs of clustering in real-world scenarios. 展开更多
关键词 Clustering kernel methods support vector machine(SVM) twin support vector clustering (TWSVC) unsupervised learning
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NbodyCP:A Direct N-body Simulation Code for Composite Stellar Populations of Single and Binary Star Clusters 认领 引用
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作者 Zhong-Mu Li Rainer Spurzem 《Research in Astronomy and Astrophysics》 SCIE CAS CSCD 2026年第1期109-118,共10页
It is well-known that some star clusters contain composite stellar populations(CSPs),in which the metallicities or(and)ages of stars are different.The formation and evolution of such clusters and their stellar populat... It is well-known that some star clusters contain composite stellar populations(CSPs),in which the metallicities or(and)ages of stars are different.The formation and evolution of such clusters and their stellar populations remain unclear.Both single and binary cluster channels may lead to such CSPs.In order to simulate the formation and evolution of such CSPs in star clusters,this work develops a code of direct N-body simulation of CSPs,NbodyCP.It is applied to different clusters,in particular,to binary clusters.It shows that CSPs and different kinds of cluster pairs can be formed via dynamical processes.This will help to partially explain the formation of CSPs and various clusters.Some special cluster structures,e.g.,two cores or bar-like shape,are shown to be the results of evolution of some binary clusters.The simulation also shows that the separation between the members of a binary cluster affects the time of two member clusters to combine or move away significantly. 展开更多
关键词 methods numerical-(Galaxy)globular clusters general-(Galaxy)open clusters and associations general
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Genome-wide terpene gene clusters analysis in Euphorbiaceae 认领 引用 被引量：2
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作者 Yinhang Wang Yunxiao Zhao +3 位作者 Ming Gao Yangdong Wang Wei Li Yicun Chen 《Horticulture Research》 SCIE CSCD 2025年第7期284-294,共11页
Euphorbiaceae species are renowned not only for horticultural significance but for their production of numerous bicyclic diterpenes with antitumor and antiviral activities.However,the gene clusters responsible for the... Euphorbiaceae species are renowned not only for horticultural significance but for their production of numerous bicyclic diterpenes with antitumor and antiviral activities.However,the gene clusters responsible for the biosynthesis of these terpenes remain largely unidentified.We here initiated the construction of a comprehensive procedure for terpene gene clusters in Euphorbiaceae species.A total of 1824 candidate gene clusters with the range of 30–800 kb were identified across seven representative species including Ricinus communis,Hevea brasiliensis,Euphorbia peplus,Jatropha curcas,Manihot esculenta,Vernicia montana,and Vernicia fordii in Euphorbiaceae.The 16 high-confidence terpene gene clusters were ultimately pinpointed in Euphorbiaceae after satisfied the three stringent screening criteria:TPS/CYP pairwise relationship,copathway and coexpression patterns.Notably,the well-known casbene and casbene-derived diterpenoid gene cluster,involved in the biosynthesis of casbene,neocembrene,ingenanes,and jatrophanes,were identified.It was observed that casbene gene clusters were universally presented in Euphorbiaceae species,except M.esculenta.Among the casbene gene cluster,the alcohol dehydrogenase(ADH)was initially appeared,and neocembrene synthase is exclusively present in R.communis while absent in all the other species.These findings represent a significant step toward understanding the genetic basis of terpene biosynthesis in Euphorbiaceae species.Moreover,this knowledge on gene clusters responsible for the biosynthesis of pharmacologically relevant terpenes can serve as a theoretical foundation for future applications. 展开更多
关键词 Euphorbiaceae biosynthesis terpene gene clusters genome wide analysis gene clusters construction comprehensive procedure terpene gene clusters antitumor candidate gene clusters
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Evolution Characteristics and Driving Mechanism of‘Bottom-up’and‘Top-down’Endogenous Automobile Industry Clusters:A Comparative Study in Taizhou and Wuhu,China 认领 引用 被引量：1
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作者 JIANG Haining ZHANG Jun +1 位作者 CHEN Jiaqi JIN Xingxing 《Chinese Geographical Science》 SCIE CAS CSCD 2026年第1期34-49,共16页
Bottom-up and top-down endogenous automobile clusters exhibit distinct evolutionary traits and driving mechanisms,yet their comparative analysis remains understudied.Therefore,using Taizhou automobile industry cluster... Bottom-up and top-down endogenous automobile clusters exhibit distinct evolutionary traits and driving mechanisms,yet their comparative analysis remains understudied.Therefore,using Taizhou automobile industry cluster(TAIC)and Wuhu automobile industry cluster(WAIC)as cases,using historical statistical data and field interview data from the 1980s to 2023,combined with qualitative research methods of thematic and diachronic analysis,and quantitative research methods of social network analysis,we compare both endogenous automobile clusters’evolutionary traits and driving mechanisms.The results confirm both clusters undergo multi-scale spatial reconfiguration,organizational complexification,and intelligent networking technological transformation,yet diverge fundamentally:TAIC evolves through market-driven progressive expansion,transitioning from single to dual-core structures via private enterprise networking,with innovation following market-integrated logic and institutional thickness built on demand-driven evolution.Conversely,WAIC follows planned expansion,maintaining state-led hierarchical single-core stability through policy-driven breakthrough innovation and supply-dominated institutional construction-though both ultimately require formal-informal system synergy.Their coevolution is driven by dynamic interactions of path dependence(weakening influence),learning-innovation(strengthening influence),and relationship selection(inverted U-shaped trajectory),with divergent development paths rooted in TAIC’s grassroots self-organization genes versus WAIC’s top-level design genes,amplified by core enterprises’strategic disparities.The research findings can not only provide decision-making support for China’s industrial upgrading,but also contribute China’s insights to global economic governance. 展开更多
关键词 endogenous automobile industrial clusters evolutionary characteristics driving mechanism Taizhou Wuhu China
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A Resilient BIRCH-Based Smart Framework for Real-Time IoT Data Clustering 认领 引用
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作者 Prabhat Das Dibya Jyoti Bora +2 位作者 Sajal Saha Cheng-Chi Lee Hirak Mazumdar 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第4期864-898,共35页
Real-time data processing is essential in the evolving landscape of IoT applications,ensuring efficiency,reliability,and adaptability.However,conventional clustering algorithms often face difficulties in managing high... Real-time data processing is essential in the evolving landscape of IoT applications,ensuring efficiency,reliability,and adaptability.However,conventional clustering algorithms often face difficulties in managing highfrequency,continuous IoT data streams due to limited adaptability and high computational overhead.To address these challenges,this study proposes a resilient adaptation of the BIRCH(Balanced Iterative Reducing and Clustering using Hierarchies)algorithm,tailored specifically for streaming IoT data.The enhanced approach dynamically recalculates clusters and determines the optimal number of clusters using the KneeLocator method.Unlike the original batchoriented BIRCH,the modified version processes data incrementally,enabling continuous adaptation to changing data distributions.The proposed method was validated on benchmark IoT datasets and compared against K-Means,DBSCAN,standard BIRCH,and other state-of-the-art streaming-based clustering algorithms.Results consistently show that the modified BIRCH outperforms existing approaches in execution speed,memory efficiency,scalability,and clustering accuracy.In addition,the algorithm has been deployed within a web-based application featuring interactive visualization and anomaly detection,highlighting its practical relevance for smart city and industrial IoT scenarios.To promote reproducibility and future research,the complete framework and source code have been made publicly available. 展开更多
关键词 IoT applications clustering algorithms smart city applications real-time data processing industrial IoT real-time clustering
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Peptide-Coupled Gold Nanoclusters:Syntheses,Properties,and Bioapplications 认领 引用
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作者 Jie Liu Huihui Liu +3 位作者 Yafang Zhang Shihua Li Xiaorong Song Huanghao Yang 《Rare Metals》 SCIE EI CAS CSCD 2026年第4期304-320,共17页
Gold nanoclusters(AuNCs)have garnered significant attention in biomedicine.Particularly,peptide-coupled AuNCs(PepAuNCs)are emerging as a fascinating class of cluster probes that enable highly tailorable design in thei... Gold nanoclusters(AuNCs)have garnered significant attention in biomedicine.Particularly,peptide-coupled AuNCs(PepAuNCs)are emerging as a fascinating class of cluster probes that enable highly tailorable design in their optical,catalytic,targeting,and therapeutic capabilities via peptide engineering.However,a comprehensive review dedicated to decoding the peptide-directed AuNC design and bioapplication paradigms is still lacking.This review systematically summarizes recent advances in the synthesis,probe design,and bioapplication of Pep-AuNCs from the perspective of peptide design.The strategies to couple AuNCs with peptides are first discussed,including in situ template synthesis and post-synthesis modification.Furthermore,we elucidate in detail how peptide sequence,structure,and coupling chemistry dictate the physicochemical and biological properties of AuNCs.We also summarize advanced functions such as specific targeting,stimuli-responsiveness,and therapeutics that can be rendered from the peptides for broadening the bioapplication potentials of AuNCs.Finally,we discuss the key challenges in their precise synthesis,long-term stability,and biotransformation study that must be addressed for clinical translation.By linking the peptide programming with the properties and application outcomes of AuNCs,this review aims to offer fundamental insights into the design principles of next-generation AuNC probes for diagnostic and therapeutic applications. 展开更多
关键词 gold clusters metal nanoclusters nanomedicine nanoprobe peptide
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Social Network and Value Chain Integration:Unraveling the Formation and Evolution of Meizhou Pomelo Industry Cluster in China 认领 引用 被引量：1
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作者 YANG Ren LIN Yuancheng ZHANG Xin 《Chinese Geographical Science》 SCIE CAS CSCD 2026年第2期239-255,共17页
The shift toward specialized and large-scale agricultural production has spurred the emergence of agricultural clusters as key forces of rural vitalization and sustainable development.This paper explored the formation... The shift toward specialized and large-scale agricultural production has spurred the emergence of agricultural clusters as key forces of rural vitalization and sustainable development.This paper explored the formation and evolution of Meizhou pomelo industry cluster in China,focusing on its role in restructuring rural socio-economic systems and integrating the whole value chains.Based on a case study employing qualitative methods such as in-depth interviews and participatory observation,the agricultural cluster evolution of Meizhou pomelo was categorized into three key phases of initial decentralization,self-organized scaling,and reorganized clustering.Geographical proximity and industrial agglomeration constitute the physical foundation,while vertical/horizontal linkages,technologic-al innovation,and policy support enhance competitiveness.Special mechanisms emerge through localized social networks,farmer co-operatives’activation,and cross-regional market expansion.The cluster’s impact is manifested in the shift from extensive to standard-ized and modernized production,diversified and flexible livelihood of farmers,and the integration of agriculture with industry and ser-vices.The development of the whole value chain based on agricultural cluster represents a critical pathway for achieving agricultural modernization,encompassing both internal and external value chain optimization.Through quality assurance systems,product diversi-fication strategies,operational efficiency improvements,and brand enhancement,these clusters amplify product value propositions and market competitiveness.This systemic approach facilitates supply-demand coordination,enables resource synergies,and optimizes eco-nomic returns across the horizontal and vertical value chain.This paper argues that agricultural clusters serve as strategic catalysts for sustainable rural development by reconstructing local production systems,fostering innovation ecosystems,and aligning agricultural modernization.It contributes to debates on rural vitalization by demonstrating how agricultural clustering can reconfigure rural areas as hubs of ecological modernization,rather than mere urban peripheries. 展开更多
关键词 agricultural cluster sustainable rural development agricultural systems social network whole value chain China
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Molecular tweezers in thiolate-protected Cu(Ⅰ)clusters:A framework platform for investigating ligand effects in cluster catalysis 认领 引用
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作者 Jiaojiao Zhang Yifan Wu +4 位作者 Yifei Li Fuxing Lin Shengchang Xiang Xi Fan Zhangjing Zhang 《Chinese Chemical Letters》 SCIE CAS CSCD 2026年第6期657-661,共5页
Scarce investigations have focused on coinage metal clusters possessing fixed cores but varying binding ligands in the context of catalysis.Here in this work,we successfully employed two types of carboxylic acid-based... Scarce investigations have focused on coinage metal clusters possessing fixed cores but varying binding ligands in the context of catalysis.Here in this work,we successfully employed two types of carboxylic acid-based molecular tweezers to selectively capture two Cu6clusters(Cu6-a and Cu6-b).Cu6-a and Cu6-b have identical cluster cores but different protected ligands,therefore provide accurate platform for investigating ligand effects in cluster catalysis.Notably,Cu6-b represents a rare example of a two-directional rod framework,marking the first instance of such a structure in coinage metal cluster-based MOFs.The integration of oxygen within OBB significantly enhances local spatial polarization,facilitating the charge separation and ROS generation efficiency of Cu6-b under visible-light irradiation.Consequently,the oxygen-containing Cu6-b exhibits superior photocatalytic performance in the aerobic oxidation of sulfide,achieving both high yield and selectivity.This work provides a valuable approach for precisely control the Cu clusters structures to regulate their properties. 展开更多
关键词 Coinage metal clusters Cu nanoclusters Framework Molecular tweezers Ligand effects
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Charging Scheduling of Clustered Wireless Rechargeable Sensor Networks Considering Dynamic Selection of Cluster Heads 认领 引用
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作者 Mengqi Liu Haiqing Yao 《Computers, Materials & Continua》 SCIE EI 2026年第7期1062-1085,共24页
For the wide-coverage application scenarios,wireless rechargeable sensor networks are normally divided into multiple clusters to support the diversity and flexibility for monitoring,and use the mobile charger(MC)to su... For the wide-coverage application scenarios,wireless rechargeable sensor networks are normally divided into multiple clusters to support the diversity and flexibility for monitoring,and use the mobile charger(MC)to support the sustainable charging of the network.Many efforts focus on optimizing the cluster head selection and mobile charger scheduling to improve the network energy efficiency and reliability.However,the existing work tends to use fixed triggering mechanism for cluster head(CH)rotation,and may trigger the rotation either too early or too late.Besides,the existing charging triggering mechanisms cannot track the changes in network topology in real time.As a result,both the network energy efficiency and the node failure rate degenerate correspondingly.To solve these problems,this work proposes a dynamic cluster head selection algorithm(DCHSA),which evaluates potential candidate CH sets based on the energy consumption,remaining energy and topological structure,and then select a new CH within this set based on the CH rotation energy consumption and the candidate CH evaluation mechanism.Furthermore,an adaptive dual-threshold selection algorithm based on dynamic energy consumption(ADTSA-DEC)is proposed to determine the set of requiring charging nodes and the trigger time for charging scheduling.The particle swarm optimization is then employed to implement the charging scheduling.Finally,extensive simulations validate that the newly proposed algorithms have outstanding accuracy and robustness in improving overall network energy efficiency and node survivability compared with existing methods. 展开更多
关键词 Clustered wireless rechargeable sensor networks cluster head rotation adaptive dual-threshold charging scheduling strategy particle swarm optimization
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基于Cluster Contrast和ViT的东北虎个体重识别无监督学习框架研究 认领 引用
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作者 赵亚凤 于继超 +2 位作者 孙骞 康嘉璐 王梓丞 《智能系统学报》 CSCD 北大核心 2026年第2期435-443,共9页
针对东北虎个体重识别中野外数据标注困难、样本失衡等挑战,以野外东北虎(Amur tiger re-identification in the wild,ATRW)数据集为基础提出一种“全局特征提取−空间位置强化−无监督均衡训练”的协同框架,完成无监督重识别。使用vision... 针对东北虎个体重识别中野外数据标注困难、样本失衡等挑战,以野外东北虎(Amur tiger re-identification in the wild,ATRW)数据集为基础提出一种“全局特征提取−空间位置强化−无监督均衡训练”的协同框架,完成无监督重识别。使用vision Transformer(ViT)自注意力机制捕捉东北虎条纹的全局长距离的依赖特征,通过坐标注意力机制加强对条纹空间位置的精确解析,解决传统卷积神经网络局部性导致的特征关联缺失问题。引入Cluster Contrast机制构建簇级内存字典,通过动量更新平衡不同样本量东北虎的特征优化速率,避免无监督学习中样本失衡导致的特征偏差。实验表明,模型在ATRW(r+i)数据集上平均精度的值为86.4%,高于原有的特征提取ViT和Resnet50_ibn模型,对不同数据分布和数据量具有良好泛化能力,适配野外可见光/红外多设备协同监测需求。本文所提方法为东北虎个体识别提供了兼具准确性与鲁棒性的技术方案。 展开更多
关键词 东北虎 重识别 深度学习 无监督学习 ATRW数据集 Cluster Contrast机制 vision Transformer 坐标注意力
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Ion-cluster-optimized microphase separation in shape-memory polydisulfides for enhanced mechanical performance 认领 引用
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作者 Chengyuan Yu Huiyao Lin +5 位作者 Le Li Ruirui Gu Qi Zhang Chenyu Shi Chenchen Zhang Fei Tong 《Chinese Chemical Letters》 SCIE CAS CSCD 2026年第2期494-500,共7页
Developing advanced polymeric materials with enhanced mechanical properties and functionalities has been a long-standing goal in materials science.Recently,supramolecular polymeric materials (SPMs) have drawn increase... Developing advanced polymeric materials with enhanced mechanical properties and functionalities has been a long-standing goal in materials science.Recently,supramolecular polymeric materials (SPMs) have drawn increased attention due to their unique properties and potential applications in self-healing,shape memory,sensors,and flexible electronics.Here,we develop an ionic cluster-optimized microphase separation strategy to enhance the toughening and energy dissipation capabilities of polydisulfide-based supramolecular polymers.The mechanical properties,including Young’s modulus and toughness,are significantly improved by integrating the quadruple H-bonding 2-ureido-4-pyrimidone (UPy) induced microphase separation with iron(Ⅲ)-to-carboxylate ionic clusters.By combining established chemical approaches with adjustable polymer phase ratios,it is revealed that the synergistic effect of these factors expands the interchain spacing,facilitates the formation of microphase domains,and enhances the tolerance of polythioctic acid-based polymers to external mechanical and thermal stimuli,meeting the practical requirements for industrial plastic applications.Moreover,the UPy-functionalized polymers incorporating iron carboxylate clusters exhibit good one-way shape memory behavior with practical applicability at a relatively low recovery temperature.Our work demonstrates a novel strategy for constructing industrially viable shape memory dynamic SPMs and paves the way for future innovations in developing SPMs. 展开更多
关键词 Polydisulfides Network toughening lonic clusters Microphase separation Shape-memory supramolecular polymers
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Microstructure and properties of Cu-Ni-Co-Si alloy designed by cluster formula approach 认领 引用
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作者 Shi-fang LI Zhu XIAO +3 位作者 Xiang-peng MENG Zhou LI Yan-lin JIA Yan-bin JIANG 《Transactions of Nonferrous Metals Society of China》 SCIE EI CAS CSCD 2026年第3期872-886,共15页
A Cu-1.9Ni-1.9Co-0.9Si(mass fraction,%)alloy with high strength and electrical conductivity was designed by cluster formula approach.The microstructure evolution of the alloy during thermomechanical treatment was syst... A Cu-1.9Ni-1.9Co-0.9Si(mass fraction,%)alloy with high strength and electrical conductivity was designed by cluster formula approach.The microstructure evolution of the alloy during thermomechanical treatment was systematically investigated.The strengthening mechanism and electrical conductivity of the alloy were discussed in detail.The optimal thermomechanical treatment process was as follows:solid solution→80%cold rolling→(450℃,4 h)aging→50%cold rolling→(400℃,4 h)aging.The designed alloy achieved excellent comprehensive properties with a microhardness of HV 260,a yield strength of 843 MPa,a tensile strength of 884 MPa,and an electrical conductivity of 42.6%(IACS).Compared to direct aging treatment,the designed alloy subjected to multi-stage thermomechanical treatment had refined grains,high density of dislocations,and accelerated of precipitation of(Ni,Co)2Si precipitates.High strength was mainly attributed to the combined effect of dislocation strengthening,work hardening and sub-grain strengthening,while good electrical conductivity was maintained through the precipitation of the large number of nanoparticles. 展开更多
关键词 Cu-Ni-Co-Si alloys cluster formula approach thermomechanical treatment microstructure strengthening mechanism
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A multi-scale fracture prediction method based on improved deep embedded clustering 认领 引用
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作者 Yu-jia Lu Chao Chen +2 位作者 Zhu-jiang Liu Fu-bin Wei Zhe-ge Liu 《Applied Geophysics》 SCIE CSCD 2026年第2期571-590,867,共20页
Accurately characterizing the distribution and scale characteristics of fractures in subsurface media is a crucial step for quantitatively evaluating shale gas sweet spots and guiding reservoir fracturing stimulation.... Accurately characterizing the distribution and scale characteristics of fractures in subsurface media is a crucial step for quantitatively evaluating shale gas sweet spots and guiding reservoir fracturing stimulation.However,a single seismic attribute is often used to identify fracture features of a specifi c scale,making it diffi cult to achieve detailed characterization of fractures across multiple scales simultaneously.Multi-attribute fusion algorithms often focus on statistical correlations,lacking in-depth exploration of the spatial topological relationships and intrinsic physical connections among fractures of diff erent scales,resulting in reduced accuracy in complex structural areas.To address this challenge,we propose a multi-scale integrated fracture prediction method based on an improved deep embedded clustering(DEC)framework,using the marine shale reservoir of the Wufeng–Longmaxi Formation in southeastern Sichuan Basin as a case study.Specifically,(1)an improved DEC objective function integrating fracture topology constraints and cluster-balancing mechanisms is developed to enhance the model’s adaptability to complex geological structures;(2)an“expand–then–contract”stacked autoencoder architecture is designed to better capture nonlinear relationships among multi-attribute data and decouple multi-scale fracture features;and(3)an integrated workfl ow from multi-attribute optimization,intelligent fusion clustering to geological interpretation is established,enabling diff erentiated and high-precision characterization of multi-scale fractures.Furthermore,based on the geological characteristics of the study area,we systematically analyze the spatial mapping relationships of the autoencoder’s multi-layer features and elucidate their implicit geophysical signifi cance.This analysis reveals the intrinsic processes through which the proposed model performs fracture attribute optimization,noise separation,and multi-scale feature extraction.Finally,by integrating intelligent fault identifi cation,micro-fracture amplitude variation with azimuth(AVAZ)inversion,and conventional geometric attributes,high-precision spatial characterization of the fracture system is achieved,spanning from large-scale faults to micro-fractures.The prediction results show strong agreement with geological understanding. 展开更多
关键词 Multi-scale fractures Deep embedded clustering Deep learning Autoencoding Marine shale
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LAMOST Medium-resolution Spectroscopic Survey of Galactic Open Clusters(LAMOST-MRS-O):Open Cluster Catalog 认领 引用
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作者 Xi Zhang Jing Zhong +3 位作者 Li Chen Jinliang Hou Zhongmu Li Chengzhi Liu 《Research in Astronomy and Astrophysics》 SCIE CAS CSCD 2026年第5期23-39,共17页
Based on the spectral data from the LAMOST Medium-Resolution Spectroscopic Survey(LAMOST-MRS)DR11-v1.1,combined with a publicly available open cluster catalog,we built a large-sample database of open clusters with med... Based on the spectral data from the LAMOST Medium-Resolution Spectroscopic Survey(LAMOST-MRS)DR11-v1.1,combined with a publicly available open cluster catalog,we built a large-sample database of open clusters with medium-resolution spectroscopic parameters.This sample encompasses radial velocity measurements from medium-resolution spectroscopy for 1033 open clusters,among which 446 clusters further offer metallicity profiles and abundance distributions for dozens of chemical elements.Based on this comprehensive data set,we performed statistical analyses on key parameters of open clusters,including radial velocities,metallicities,and chemical element abundances.Notably,when the star cluster radial velocities are compared with results from the high-resolution spectroscopic survey,the mean difference is constrained within 1 km s−1,with a standard deviation less than 10 km s−1.For metallicity[Fe/H]comparisons with published highresolution literature values,the average discrepancy falls in the range of 0.02–0.04 dex,accompanied by a standard deviation of 0.06–0.08 dex.These findings demonstrate that open cluster properties derived by LAMOST-MRS exhibit reliable precision,making them suitable as probes for in-depth investigations into the chemical evolution of the Milky Way.Finally,we have compiled a catalog of 1033 open clusters,complemented by parameter lists for approximately 7000 member stars—all including their LAMOST-MRS spectroscopic parameters.This data set provides a valuable resource for advancing galactic astrophysics research. 展开更多
关键词 (Galaxy:)open clusters and associations general-methods data analysis-catalogs
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A Mix Location Privacy Preservation Method Based on Differential Privacy with Clustering 认领 引用
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作者 Fang Liu Xianghui Meng +1 位作者 Jiachen Li Sibo Guo 《Computers, Materials & Continua》 SCIE EI 2026年第2期632-652,共21页
With the popularization of smart devices,Location-Based Services(LBS)greatly facilitates users’life,but at the same time brings the risk of users’location privacy leakage.Existing location privacy protection methods... With the popularization of smart devices,Location-Based Services(LBS)greatly facilitates users’life,but at the same time brings the risk of users’location privacy leakage.Existing location privacy protection methods are deficient,failing to reasonably allocate the privacy budget for non-outlier location points and ignoring the critical location information that may be contained in the outlier points,leading to decreased data availability and privacy exposure problems.To address these problems,this paper proposes a Mix Location Privacy Preservation Method Based on Differential Privacy with Clustering(MLDP).The method first utilizes the DBSCAN clustering algorithm to classify location points into non-outliers and outliers.For non-outliers,the scoring function is designed by combining geographic information and semantic information,and the privacy budget is allocated according to the heat intensity of the hotspot area;for outliers,the scoring function is constructed to allocate the privacy budget based on their correlation with the hotspot area.By comprehensively considering the geographic information,semantic information,and correlation with hotspot areas of the location points,a reasonable privacy budget is assigned to each location point,andfinallynoise is added throughthe Laplacemechanismto realizeprivacyprotection.Experimental results on tworeal trajectory datasets,Geolife and T-Drive,show that the MLDP approach significantly improves data availability while effectively protecting location privacy.Compared with the comparison methods,the maximum available data ratio of MLDP is 1.Moreover,compared with the RandomNoise method,its execution time is 0.056–0.061 s longer,and the logRE is 0.12951–0.62194 lower;compared with KemeansDP,QTK-DP,DPK-F,IDP-SC,and DPK-Means-up methods,it saves 0.114–0.296 s in execution time,and the logRE is 0.01112–0.38283 lower. 展开更多
关键词 Location privacy protection DBSCAN clustering differential privacy hotspot area
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Machine learning-driven pathogen cluster analysis identifies highrisk subtypes of infected pancreatic necrosis in a multi-center cohort 认领 引用
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作者 Bai-Qi Liu Ze-Fang Sun +9 位作者 Cai-Hong Ning Jie Xiao Di Wu Chia-Yen Lin Xiao-Yue Hong Rong Guo Lu Chen Xin-Tong Cao Ding-Cheng Shen Geng-Wen Huang 《World Journal of Gastroenterology》 SCIE CAS 2026年第27期40-51,共12页
BACKGROUND Infected pancreatic necrosis(IPN)presents with highly variable clinical trajectories that are significantly influenced by the underlying microbial profile.Although established prognostic models,such as the ... BACKGROUND Infected pancreatic necrosis(IPN)presents with highly variable clinical trajectories that are significantly influenced by the underlying microbial profile.Although established prognostic models,such as the Acute Physiology and Chronic Health Evaluation II and Bedside Index of Severity in Acute Pancreatitis scoring systems,evaluate host physiological severity,they do not adequately account for the impact of specific pathogen compositions on patient survival.AIM To utilize machine learning-driven pathogen cluster analysis to stratify patients with IPN into distinct clusters for precise risk prediction.METHODS We conducted a hierarchical clustering analysis on microbiological data from 396 IPN patients,using the Jaccard distance to identify distinct pathogen-driven clusters.Clinical outcomes were compared across these clusters.External cohort validation was conducted to assess the effect of clusters.RESULTS Four distinct pathogen clusters(α-δ)were identified,including an Enterococcus faecium/Enterobacter cloacae-predominant cluster(α),an Escherichia coli-dominantcluster(β),a multidrug-resistant organism-enriched cluster(γ),and an Acinetobacter baumannii-Candida glabrata coinfection cluster(δ).Clusterα,characterized by Enterococcus faecium and Enterobacter cloacae,demonstrated moderate severity and 20.5% in-hospital mortality.Cluster β,dominated by Escherichia coli,showed the lowest mortality(10.3%)and clinical severity.Cluster γ,enriched with multidrug-resistant organisms(e.g.,Klebsiella pneumoniae and Pseudomonas aeruginosa),had a high mortality(26.3%)and more severe clinical manifestations.Clusterδ,marked by Acinetobacter baumannii and Candida glabrata,had the highest mortality(31.5%).External cohort validation confirmed the robustness of these four subtypes,supporting their clinical relevance.CONCLUSION The study highlights the role of pathogen compositions in IPN,revealing how specific microbial profiles influence prognosis.It provides a novel approach for pathogen-based risk stratification in IPN. 展开更多
关键词 Infected pancreatic necrosis Machine learning Pathogen clustering Multidrug-resistant organisms Risk stratification
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Cluster-Driven Strengthening and Oxide Stripes-Induced Embrittlement in Internally Oxidized AgMg Alloys 认领 引用
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作者 Hai-Cheng Zhu Shao-Hong Liu +10 位作者 Li-Min Zhou Hao Cui Hong-Ying Pei Wen-Yan Zhou Man-Men Liu Hai-Gang Dong Ming Wen Li Chen Wei Wang Song Li Liang Zuo 《Rare Metals》 SCIE EI CAS CSCD 2026年第2期383-394,共12页
Internal oxidation has been identified as an effective method for enhancing the strength of AgMg alloys.However,the concurrent occurrence of embrittlement remains inadequately understood,thus limiting their broader ap... Internal oxidation has been identified as an effective method for enhancing the strength of AgMg alloys.However,the concurrent occurrence of embrittlement remains inadequately understood,thus limiting their broader application.This study investigates the oxidation behavior of AgMg alloys with Mg concentrations ranging from 1 at% to 7 at% at 800 ℃,revealing a composition-dependent evolution of microstructure and mechanical properties.The oxidation process results in the formation of two distinct zones:a Mg/O solid solution zone (Mg/O SSZ),characterized by~3 nm Mg/O clusters,and an internal oxide band zone (IOBZ),where nanocrystalline MgO stripes emerge at Mg concentrations of 2 at%or higher.The Mg/O SSZ is responsible for substantial strengthening,with surface hardness increasing from 74 HV (as-cast) to 224 HV at 7 at %Mg,and tensile strength rising from less than 50 MPa (pure Ag) to 269 MPa at 1 at%Mg.In contrast,the development of MgO stripes within the IOBZ induces localized stress concentrations at incoherent MgO/Ag interfaces,resulting in embrittlement and a reduction in mechanical performance at higher Mg contents.The oxidation kinetics deviate progressively from Wagner's theory with increasing Mg concentration,as the formation of MgO stripes impedes oxygen transport,decreasing the oxidation rate from 7.83µm s-1/2at 1 at% Mg to 0.69µm s-1/2at 7 at% Mg.These results elucidate a compositionally tunable balance between nanoscale cluster-driven strengthening and oxide stripe-induced embrittlement,providing a mechanistic framework for the design of high-performance AgMg alloys for structural and electronic applications. 展开更多
关键词 AgMg alloy internal oxidation Mg/O cluster oxidation kinetics oxide stripe
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Using Immune Clusters for Classifying Heterogeneity of Immunity in Healthy Adults 认领 引用
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作者 Xiao-hui Wu Yi Huang +4 位作者 Si-yu Zou Kai-shan Jiang Shi-ji Wu Hong-yan Hou Feng Wang 《Current Medical Science》 SCIE CAS CSCD 2026年第2期367-381,共15页
Objective Quantification of immunity is a challenge in clinical practice due to the complexity and heterogeneity of immune cells.This study aimed to establish comprehensive reference ranges for immune indicators and c... Objective Quantification of immunity is a challenge in clinical practice due to the complexity and heterogeneity of immune cells.This study aimed to establish comprehensive reference ranges for immune indicators and characterize immune heterogeneity in healthy adults.Methods A total of 115 healthy adults aged 1865 years were enrolled.Sixty immune indicators encompassing natural immunity(NK cells,monocytes,dendritic cells,myeloid-derived suppressor cells),cellular immunity(T cells,regulatory T cells,T follicular helper cells,T helper cells),and humoral immunity(B cells),along with nutritional and metabolic indicators,were simultaneously detected.Flow cytometry was used to measure the number,phenotype,and functional subsets of immune cells.Unsupervised k-means clustering was performed to identify immune subtypes.RNA-sequencing was conducted on representative individuals from each cluster for transcriptomic validation.Results The reference ranges for 60 immune indicators were established,with over half(38/60)exhibiting coefficient of variation>30%,indicating substantial heterogeneity.Gender differences were minimal,whereas age-related changes were pronounced in adaptive immune cells.Specifically,human leukocyte antigen DR-positive(HLA-DR+)T cells(%)increased from 20.76%±7.75%(1830years)to 30.06%±10.82%(5165 years,P=0.001),while CD45RA+regulatory T(Treg)cells(%)and naive CD8+T cells(%)decreased progressively with age(P<0.001).Correlation analysis between immune cells and routine laboratory indicators revealed that nutritional indicators like albumin(ALB)were positively correlated with the number of immune cells such as CD8+T cells,while lipid metabolism indicators like low-density lipoprotein(LDL)were negatively correlated with T helper cell differentiation(P<0.01).Clustering analysis identified three distinct immune subtypes:"potential type"(26.1%,n=30)characterized by high naive T cells(44.91%±9.88%CD4+T cells,33.86%±13.82%CD8+T cells)and CD1c-positive myeloid dendritic cells(CD1c+mDCs)(45.17%±11.58%);"effector NK type"(34.8%,n=45)with elevated NK cell count(704.22±280.79 cells/μL)and cytotoxic function(93.16%±2.38%perforin+NK cells);and"effector T type"(39.1%,n=40)distinguished by increased HLA-DR+T cells(19.48%±7.1%CD4+T cells,45.11%±10.92%CD8+T cells)and effector memory(EM)CD4+T cells(37.85%±11.01%).A further RNA-sequencing analysis confirmed the transcriptomic characteristics of different immune subtypes,which was in accordance with phenotype analysis.Specifically,adults in the potential type had strong adaptive immunity;those in the effector NK type showed upregulated NK cell-mediated cytotoxicity;those in the effector T type exhibited enhanced T-helper 1 immune responses.Conclusion This study provides a systematic framework for immunity quantification by establishing reference ranges and classifying healthy adults into three immune subtypes with distinct metabolic and transcriptomic features.These findings could enhance understanding of immune heterogeneity in healthy individuals and guide personalized immune monitoring and intervention strategies in clinical practice. 展开更多
关键词 Immune heterogeneity Healthy adults Immune characteristics Lymphocytes Nutritional indicators Clustering analysis Prediction model
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Characteristics and formation mechanism of non-metallic inclusion clusters in vacuum arc remelted Ni-based superalloys 认领 引用
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作者 Yu Gu Kai-Xuan Gui +1 位作者 Peng Zhao Shu-Feng Yang 《Journal of Iron and Steel Research International》 SCIE EI CSCD 2026年第5期18-32,共15页
A quantitative study of inclusions in an industrial superalloy ingot produced by vacuum arc remelting(VAR)was conducted,and the characteristics as well as the formation mechanism of non-metallic inclusion clusters wer... A quantitative study of inclusions in an industrial superalloy ingot produced by vacuum arc remelting(VAR)was conducted,and the characteristics as well as the formation mechanism of non-metallic inclusion clusters were discussed.Results showed that inclusions within the VAR ingot primarily consisted of individual nitrides and composite inclusions such as oxide-nitrides.The quantity density of individual inclusions increases radially from the center to the edge of the ingot,while decreasing axially from the top to the bottom,with the average size gradually decreasing in both radial and axial directions.Clustered inclusions were identified in the subsurface regions(2-10 mm in depth)and sidewall surfaces of the ingot.The formation mechanism and distribution characteristics of clustered inclusions during the VAR process were studied by combining in-situ high-temperature laser confocal microscopy observation and numerical analysis.In-situ observations confirm that larger inclusions lead to reduced critical aggregation distance,while smaller spacing enhances attraction and promotes cluster formation.The cavity bridge force between inclusions is significantly greater than the capillary force and van der Waals force,serving as the primary force responsible for the aggregation of inclusions.Numerical analysis reveals that inclusions within the VAR melt pool exhibit typical flow-following behavior and size effects,with their trajectory leading to preferential accumulation patterns along both the sidewall and subsurface regions,thereby facilitating cluster formation through particle agglomeration. 展开更多
关键词 Inclusion cluster Formation mechanism Aggregation behavior Ni-based superalloy Vacuum arc remelting
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