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Effect of solidification rate on dendrite segregation and mechanical properties of Cu-15Ni-8Sn alloy prepared by directional solidification

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Journal of Iron and Steel Research International 2023年第8期30卷 1586-1597页

作者： yu-fan shi Cheng-jun Guo Ming-quan yuan Zhen-bin Jia Gui-huan An Xiang-peng Xiao Bin Yang Faculty of Materials Metallurgy and Chemistry Jiangxi University of Science and TechnologyGanzhou 341000JiangxiChina Jiangxi Advanced Copper Industry Research Institute Yingtan 335000JiangxiChina

The microstructures and mechanical properties of the directionally solidified Cu-15Ni-8Sn alloy were investigated at solidification rates ranging from 100 to 3000μm/*** results showed that the solidification rate significantly affects the phase distribution of the as-cast Cu-15Ni-8Sn *** primary and secondary dendritic spacing reduces and eventually becomes stable as the solidification rate ***,the size of the primary phase decreases,and its distribution becomes more *** most severe segregation problem of this alloy has been greatly *** solidification at 100μm/s,the as-cast Cu-15Ni-8Sn alloy consists of the α-Cu matrix,γ-CuNi_(2)Sn phase,discontinuous precipitation structure,modulated structure,and DO_(22) ordered ***,as the solidification rate increases,the discontinuous precipitation structure,modulated structures,and DO_(22) ordered phases decrease and even disappear,reducing *** the solidification rate increases,after homogenization treatment,the composition and microhardness distributions of Cu-15Ni-8Sn alloy become more *** time for homogenization is also *** reduces production energy usage and facilitates further mechanical processing.

关键词： Cu-15Ni-8Sn alloy Dendrite segregation Directional solidification Discontinuous precipitation structure DO_(22)ordered phase

Significant spatiotemporal pattern of nitrous oxide emission and its influencing factors from a shallow eutropic lake in Inner Mongolia,China

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Journal of Environmental Sciences 2025年第3期149卷 488-499页

作者： Guohua Li Sheng Zhang Xiaohong shi Shengnan Zhao Liyang Zhan Xueru Pan fan Zhang Haifeng yu yue Sun Lauri Arvola Jussi Huotari Water Conservancy and Civil Engineering College Inner Mongolia Agricultural UniversityHohhot 010018China Inner Mongolia Water Resource Protection and Utilization Key Laboratory Hohhot 010018China State Gauge and Research Station of Wetland Ecosystem Wuliangsuhai LakeBayan Nur 014404China Key Laboratory of Global Change and Marine-Atmospheric Chemistry Third Institute of OceanographyMinistry of Natural ResourcesXiamen 361005China Faculty of Biological and Environmental Sciences Ecosystems and Environment Research ProgrammeLammi Biological StationUniversity of HelsinkiLammi FI-16900Finland Masinotek Oy Ensimmainen Savu 2Vantaa FI-01510Finland

Eutrophic shallow lakes are generally considered as a contributor to the emission of nitrous oxide(N_(2)O),while regional and global estimates have remained *** due to a lack of data and insufficient understanding of the multiple contributing *** study characterized the spatiotemporal variability in N_(2)O concentrations and N_(2)O diffusive fluxes and the contributing factors in LakeWuliangsuhai,a typical shallow eutrophic and seasonally frozen lake in Inner Mongolia with cold and arid *** N_(2)O concentrations of the lake exhibited a range of 4.5 to 101.2 nmol/L,displaying significant spatiotemporal *** lowest and highest concentrations were measured in summer and winter,*** spatial distribution of N_(2)Ofluxwas consistent with that of N_(2)O ***,the hotspots of N_(2)O emissions were detected within close to the main inflow of *** wide spatial and temporal variation in N_(2)O emissions indicate the complexity and its relative importance of factors influencing emissions.N_(2)O emissions in different lake zones and seasons were regulated by diverse *** influencing the spatial and temporal distribution of N_(2)O concentrations and fluxes were identified as WT,WD,DO,Chl-a,SD and ***,the same factor demonstrated opposing effects on N_(2)O emission in various seasons or *** research improves our understanding of N_(2)O emissions in shallow eutrophic lakes in cold and arid areas.

关键词： Nitrous oxide Spatial and temporal variation Controlling factors Shallow lakes

Endoscopy-assisted lightweight diagnosis system based on transformers for colon polyp detection

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Optoelectronics Letters 2025年第1期21卷 57-64页

作者： fan Weiming yu Jiahui JU Zhaojie School of Automation and Electrical Engineering Shenyang Ligong UniversityShenyang 110159China Department of Biomedical Engineering Zhejiang UniversityHangzhou 310058China School of Computing University of PortsmouthPO13HEUK

The integration of endoscopy has significantly propelled the diagnosis and treatment of gastrointestinal diseases,with colonoscopy establishing itself as the primary method for early diagnosis and preventive care in colorectal cancer(CRC).Although deep learning holds promise in mitigating missed polyp rates,modern endoscopy examinations pose additional challenges,such as image blurring and *** study explores lightweight yet powerful attention mechanisms,introducing the spatial-channel transformer(SCT),an innovative approach that leverages spatial channel relationships for attention weight *** method utilizes rotation operations for inter-dimensional dependencies,followed by residual transformation,encoding inter-channel and spatial information with minimal computational *** experiments on the CVC-Clinic DB polyp detection dataset,addressing endoscopy pitfalls,underscore the superiority of our SCT over other state-of-the-art *** proposed model maintains high performance,even in challenging scenarios.

关键词： diagnosis utilize holds

维普期刊数据库

RE-SEGNN:recurrent semantic evidence-aware graph neural network for temporal knowledge graph forecasting

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Science China(Information Sciences) 2025年第2期68卷 103-119页

作者： Wenyu CAI Mengfan LI Xuanhua shi yuanxin fan Quntao ZHU Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and Technology

Temporal knowledge graph(TKG) reasoning, has seen widespread use for modeling real-world events, particularly in extrapolation settings. Nevertheless, most previous studies are embedded models, which require both entity and relation embedding to make predictions, ignoring the semantic correlations among different entities and relations within the same timestamp. This can lead to random and nonsensical predictions when unseen entities or relations occur. Furthermore, many existing models exhibit limitations in handling highly correlated historical facts with extensive temporal depth. They often either overlook such facts or overly accentuate the relationships between recurring past occurrences and their current counterparts. Due to the dynamic nature of TKG, effectively capturing the evolving semantics between different timestamps can be *** address these shortcomings, we propose the recurrent semantic evidenceaware graph neural network(RE-SEGNN), a novel graph neural network that can learn the semantics of entities and relations simultaneously. For the former challenge, our model can predict a possible answer to missing quadruples based on semantics when facing unseen entities or relations. For the latter problem, based on an obvious established force, both the recency and frequency of semantic history tend to confer a higher reference value for the current. We use the Hawkes process to compute the semantic trend, which allows the semantics of recent facts to gain more attention than those of distant facts. Experimental results show that RE-SEGNN outperforms all SOTA models in entity prediction on 6 widely used datasets, and 5 datasets in relation prediction. Furthermore, the case study shows how our model can deal with unseen entities and relations.

关键词： knowledge graph reasoning temporal knowledge graph Hawkes process semantic evidence

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Single-cell technologies: current and near future

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Science China(Life Sciences) 2025年第1期68卷 1-4页

作者： Chenfei Wang Qi Liu Xiaohui fan Tieliu shi KeyLaboratory of Spine and Spinal CordInjury Repairand Regeneration Ministry of EducationOrthopedics DepartmentTongji HospitalBioinformatics DepartmentSchoolofLifeSciencesandTechnologyTongji UniversityShanghai 200082China Frontier Science Center for Stem Cells School of Life Sciences and TechnologyTongji UniversityShanghai 200092China Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine Shanghai East HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji UniversityShanghai 200082China Research Institute of Intelligent Computing Zhejiang LabHangzhou 311121China Pharmaceutical Informatics Institute College of Pharmaceutical SciencesZhejiang UniversityHangzhou 310058China National Key Laboratory of Chinese Medicine Modernization Innovation Center of Yangtze River DeltaZhejiang UniversityJiaxing 314103China Center for Bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biologythe Institute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghai 200241China Key Laboratory of Advanced Theory and Application in Statistics and Data Science(MOE) School of StatisticsEast China Normal UniversityShanghai 200062China

Single-cell technologies enable the indepth exploration of multiple biological hierarchies at the scale of individual cells,which have deepened our knowledge of cellular diversity,tissue organization,and overall organism function(Sun et al.,2024).In 2009,single-cell RNA sequencing(scRNA-seq)was first developed as a powerful tool to dissect gene expression and uncover transcriptional *** the rapid advancement of technology,single-cell approaches have expanded to encompass other omics,such as genomics,epigenomics,proteomics,and ***,multimodal technologies including spatially resolved transcriptomics and clustered regularly interspaced short palindromic repeats(CRISPR)screening at the single-cell level further advanced our ability to comprehensively understand cellular ***-cell methods provide deeper insights into disease mechanisms across various conditions,including cancer,developmental disorders,and aging-associated *** this issue,we focus on topics related to single-cell methods,covering the following four aspects:(i)single-cell multi-omic sequencing technology;(ii)single-cell spatial technology;(iii)singlecell CRISPR screening technology;(iv)applications of single-cell technology.

关键词： expanded enable insight

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Deep Synchronization Control of Grid-Forming Converters:A Reinforcement Learning Approach

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 273-275页

作者： Zhuorui Wu Meng Zhang Bo fan Yang shi Xiaohong Guan the School of Cyber Science and Engineering Xi'an Jiaotong University the Department of Mechanical Engineering University of Victoria

Dear Editor,This letter proposes a deep synchronization control(DSC) method to synchronize grid-forming converters with power grids. The method involves constructing a novel controller for grid-forming converters based on the stable deep dynamics model. To enhance the performance of the controller, the dynamics model is optimized within the deep reinforcement learning(DRL) framework. Simulation results verify that the proposed method can reduce frequency deviation and improve active power responses.

关键词： Deep reinforcement learning

Stability and Stabilization of Sampled-Data Based LFC for Power Systems:A Data-Driven Method

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 291-293页

作者： yu-Long fan Chuan-Ke Zhang Yong He the School of Automation China University of Geosciences the Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems the Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education IEEE

Dear Editor,This letter is concerned with stability analysis and stabilization design for sampled-data based load frequency control(LFC) systems via a data-driven method. By describing the dynamic behavior of LFC systems based on a data-based representation, a stability criterion is derived to obtain the admissible maximum sampling interval(MSI) for a given controller and a design condition of the PI-type controller is further developed to meet the required MSI. Finally, the effectiveness of the proposed methods is verified by a case study.

关键词： Sampled data control systems

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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Adaptive VDI Session Placement via User Logoff Prediction

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Machine Intelligence Research 2025年第1期22卷 189-200页

作者： Wenping fan Puhui Meng yu Tian Min-Ling Zhang Yao Zhang School of Computer Science and Engineering Southeast UniversityNanjing210096China VMware Information Technology(China)Limited Beijing100190China Key Laboratory of Computer Network and Information Integration(Southeast University) Ministry of EducationNanjing210096China

After the global pandemic,DaaS(desktop as a service)has become the first choice of many companies’remote working *** the desktops are usually deployed in the public cloud when using DaaS,customers are more cost-sensitive which boosts the requirement of proactive power *** researches in this area focus on virtual desktop infrastructure(VDI)session logon behavior modeling,but for the remote desktop service host(RDSH)-shared desktop pools,logoff optimization is also *** systems place sessions by round-robin or in a pre-defined order without considering their logoff ***,these approaches usually suffer from the situation that few left sessions prevent RDSH servers from being powered-off which introduces cost *** this paper,we propose session placement via adaptive user logoff prediction(SODA),an innovative compound model towards proactive RDSH session ***,an ensemble machine learning model that can predict session logoff time is combined with a statistical session placement bucket model to place RDSH sessions with similar logoff time in a more centralized manner on RDSH ***,the infrastructure cost-saving can be improved by reducing the resource waste introduced by those RDSH hosts with very few hanging sessions left for a long *** on real RDSH pool data demonstrate the effectiveness of the proposed proactive session placement approach against existing static placement techniques.

关键词： Virtual desktop infrastructure(VDI)resource management remote desktop service logoff prediction adaptive modeling session placement