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Optimal Allocation of Distributed Generation and Energy Storage Considering Line Vulnerability under Extreme Weather in Distribution Networks 认领 引用
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作者 Yangjun Zhou Chenying Yi +10 位作者 Wei Zhang Juntao Pan Ke Zhou Weixiang Huang Like Gao Shan Li Yuanchao Zhou Ling Li Liwen Qin Hongwen Wu Lijuan Yan 《Energy Engineering》 EI 2026年第6期567-583,共17页
The increasing integration of distributed generation(DG)and energy storage systems(ESS)has significantly enhanced the flexibility and efficiency of distribution networks.However,the growing frequency of extreme weathe... The increasing integration of distributed generation(DG)and energy storage systems(ESS)has significantly enhanced the flexibility and efficiency of distribution networks.However,the growing frequency of extreme weather events has exposed the vulnerability of distribution lines,posing serious challenges to the reliability and resilience of such systems.Existing DG and ESS planning models often neglect this vulnerability dimension,leading to suboptimal siting decisions and reduced system robustness.To address this issue,this paper proposes a comprehensive multi-objective optimization framework that coordinates the allocation of DG and ESS and explicitly incorporates line vulnerability under extreme weather conditions.The vulnerability index of each distribution line is first evaluated through Monte Carlo simulations that capture the probabilistic influence of micro-climatic and terrain factors.This assessment serves as a pre-processing stage that screens out high-risk lines and thereby constrains the optimization decision space to more reliable nodes for DG and ESS deployment.Building upon this filtered network,a multi-objective optimization model is established to determine the optimal siting and capacities of DG and ESS.The optimization simultaneously minimizes the total annual cost,which includes investment,operation,and maintenance expenses,as well as network power losses,while improving overall system resilience.A case study on a modified IEEE 33-bus distribution system verifies the effectiveness of the proposed method.The results demonstrate that vulnerability-aware planning achieves a better balance between cost and reliability compared with conventional approaches.Specifically,the proposed strategy reduces annual network losses and outage durations while maintaining voltage stability with respect to climate-adjusted line failure rates.Furthermore,the integration of ESS enables effective peak shaving and valley filling,improving system efficiency and operational flexibility.These findings confirm that incorporating line vulnerability into DG and ESS planning provides a practical and scalable pathway for enhancing the resilience and economy of distribution networks. 展开更多
关键词 Distributed generation energy storage systems distribution networks extreme weather line vulnerability multi-objective optimization
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Structure-Based Virtual Sample Generation Using Average-Linkage Clustering for Small Dataset Problems 认领 引用
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作者 Chih-Chieh Chang Khairul Izyan Bin Anuar Yu-Hwa Liu 《Computers, Materials & Continua》 SCIE EI 2026年第4期896-908,共13页
Small datasets are often challenging due to their limited sample size.This research introduces a novel solution to these problems:average linkage virtual sample generation(ALVSG).ALVSG leverages the underlying data st... Small datasets are often challenging due to their limited sample size.This research introduces a novel solution to these problems:average linkage virtual sample generation(ALVSG).ALVSG leverages the underlying data structure to create virtual samples,which can be used to augment the original dataset.The ALVSG process consists of two steps.First,an average-linkage clustering technique is applied to the dataset to create a dendrogram.The dendrogram represents the hierarchical structure of the dataset,with each merging operation regarded as a linkage.Next,the linkages are combined into an average-based dataset,which serves as a new representation of the dataset.The second step in the ALVSG process involves generating virtual samples using the average-based dataset.The research project generates a set of 100 virtual samples by uniformly distributing them within the provided boundary.These virtual samples are then added to the original dataset,creating a more extensive dataset with improved generalization performance.The efficacy of the ALVSG approach is validated through resampling experiments and t-tests conducted on two small real-world datasets.The experiments are conducted on three forecasting models:the support vector machine for regression(SVR),the deep learning model(DL),and XGBoost.The results show that the ALVSG approach outperforms the baseline methods in terms of mean square error(MSE),root mean square error(RMSE),and mean absolute error(MAE). 展开更多
关键词 Small datasets average linkage virtual sample generation forecasting accuracy improvements
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Optimized design and energy management of a hybrid electric traction substation integrating photovoltaic generation and storage systems:case study of the Moroccan railway network 认领 引用
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作者 Mohamed Amine Ouaid Mohammed Ouassaid 《Global Energy Interconnection》 EI CSCD 2026年第2期356-371,共16页
The integration of renewable energy sources into railway traction substations has become a strategic priority to reduce operational costs and CO2 emissions.This paper presents a novel optimization framework specifi... The integration of renewable energy sources into railway traction substations has become a strategic priority to reduce operational costs and CO2 emissions.This paper presents a novel optimization framework specifically designed for Hybrid Traction Substations(HTS),which differ from conventional microgrids due to their traction-specific load dynamics,bidirectional energy flows,and grid-integration constraints.A stochastic multi-objective optimization model is developed to jointly minimize total system cost and maximize renewable energy utilization,while accounting for Moroccan grid code restrictions,including the prohibition of reverse power injection and the absence of braking energy recovery.Solar irradiance uncertainty is captured via historical data clustering with K-means,enabling efficient computation and robust sizing.The optimization is solved with a Multi-Objective Particle Swarm Optimization(MOPSO)algorithm,demonstrating reliable performance.Seasonal load and irradiance profiles are incorporated to ensure representative results,and a sensitivity analysis on key economic and operational parameters confirms the robustness of the optimized solutions.A case study of the Asilah substation highlights Pareto trade-offs between investment cost,operational cost,and renewable penetration,confirming the framework’s effectiveness,scalability,and practical relevance for decarbonizing railway electrification. 展开更多
关键词 Hybrid traction substation Photovoltaic generation Energy storage systems Multi-objective optimization Energy management Railway electrification Moroccan railway network
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Staggered Nonlinear Spin Generations in Centrosymmetric Altermagnets under Electric Current 认领 引用
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作者 Jie Zhang Ruijing Fang +1 位作者 Zhichao Zhou Xiao Li 《Chinese Physics Letters》 SCIE EI CAS CSCD 2026年第2期217-227,共11页
Current-induced spin generations are of significant importance for electrically controllable magnetization.Due to symmetry constraints,linear spin generation is absent in centrosymmetric magnets and nonlinear contribu... Current-induced spin generations are of significant importance for electrically controllable magnetization.Due to symmetry constraints,linear spin generation is absent in centrosymmetric magnets and nonlinear contributions become crucial.However,nonlinear spin generations have few examples in centrosymmetric compensated magnets with opposite-spin sublattices,which hinders electric control of associated magnetization.Here,we study nonlinear spin generations in altermagnets,a new type of compensated magnets.In a square altermagnetic model,both staggered and uniform nonlinear spin generations appear at opposite-spin sublattices.They vary as the magnetization direction rotates,with emerging out-of-plane components that can be utilized in perpendicular magnetization switching of high-density storage devices.By first-principles calculations,out-of-plane,staggered nonlinear spin generations are found to be considerable in a typical altermagnet,Fe2Se2O monolayer.Our findings provide opportunities for electrically manipulating magnetization and designing energy-efficient magnetic devices based on compensated magnets. 展开更多
关键词 electric current induced spin generations compensated magnetsin centrosymmetric compensated magnets staggered nonlinear spin generations centrosymmetric magnets spin generations electric control centrosymmetric altermagnets
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High efficiency of thalassemia prevention by next-generation sequencing:a real-world cohort study in two centers of China 认领 引用 被引量：3
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作者 Jinman Zhang Wenqian Zhang +18 位作者 Haoqing Zhang Aiqi Cai Caiyun Li Ling Liu Jufang Tan Yang Yang Wen Yuan Jing He Shiping Chen Yingli Cao Yan Zhang Jie Zhang Rui Zhou Shuai Hou Dongqun Huang Danjing Chen Zhiyu Peng Dongzhu Lei Baosheng Zhu 《Journal of Genetics and Genomics》 SCIE CAS CSCD 2026年第1期87-96,共10页
The occurrence of severe thalassemia,an inherited blood disorder that is either blood-transfusiondependent or fatal,can be mitigated through carrier screening.Here,we aim to evaluate the effectiveness and outcomes of ... The occurrence of severe thalassemia,an inherited blood disorder that is either blood-transfusiondependent or fatal,can be mitigated through carrier screening.Here,we aim to evaluate the effectiveness and outcomes of pre-conceptional and early pregnancy screening initiatives for severe thalassemia prevention in a diverse population of 28,043 women.Using next-generation sequencing(NGS),we identify 4,226(15.07%)thalassemia carriers across 29 ethnic groups and categorize them into high-(0.75%),low-(25.86%),and unknown-risk(69.19%)groups based on their spouses'screening results.Post-screening follow-up reveals 59 fetuses with severe thalassemia exclusively in high-risk couples,underscoring the efficacy of risk classification.Among 25,053 live births over 6 months of age,two severe thalassemia infants were born to unknown-risk couples,which was attributed to incomplete screening and late NGS-based testing for a rare variant.Notably,64 rare variants are identified in 287 individuals,highlighting the genetic heterogeneity of thalassemia.We also observe that migrant flow significantly impacts carrier rates,with 93.90%of migrants to Chenzhou originating from high-prevalence regions in southern China.Our study demonstrates that NGS-based screening during pre-conception and early pregnancy is effective for severe thalassemia prevention,emphasizing the need for continuous screening efforts in areas with high and underestimated prevalence. 展开更多
关键词 Thalassemia Carrier screening Next generation sequencing Rare thalassemia Clinical effectiveness Blood-transfusion-dependent
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The Agentic-AI Core:An AI-Empowered,Mission-Oriented Core Network for Next-Generation Mobile Telecommunications 认领 引用 被引量：1
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作者 Xu Li Weisen Shi +3 位作者 Hang Zhang Chenghui Peng Shaoyun Wu Wen Tong 《Engineering》 SCIE EI CSCD 2026年第1期104-119,共16页
While the complexity of fifth-generation wireless networks is being widely commented upon,there is great anticipation for the arrival of the sixth generation(6G),with its enriched capabilities and features.It can easi... While the complexity of fifth-generation wireless networks is being widely commented upon,there is great anticipation for the arrival of the sixth generation(6G),with its enriched capabilities and features.It can easily be imagined that,without proper design,the enrichment of 6G will further increase system complexity.To address this issue,we propose the Agentic-AI Core(A-Core),an artificial intelligence(AI)-empowered,mission-oriented core network architecture for next-generation mobile telecommunications.In A-Core,network capabilities can be added and updated on the fly and further programmed into missions for enabling and offering diverse services to customers.These missions are created and executed by autonomous network agents according to the customer's intent,which may be expressed in natural language.The agents resolve intents from customers into workflows of network capabilities by leveraging a large-scale network AI model and follow the workflows to execute the mission.As an open,agile system architecture,A-Core holds promise for accelerating innovation and greatly reducing standard release times.The advantages of A-Core are demonstrated through two use cases. 展开更多
关键词 Sixth generation Core network Generative artificial intelligence Artificial intelligence agent
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Design of rare earth borate short-wave UV nonlinear optical crystals with strengthened second harmonic generation activities via cationic modification strategy 认领 引用 被引量：1
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作者 Huijian Zhao Jie Song +4 位作者 Shuaifeng Li Xianghao Kong Conggang Li Ning Ye Zhanggui Hu 《Chinese Chemical Letters》 SCIE CAS CSCD 2026年第6期662-666,共5页
Ultraviolet(UV)nonlinear optical(NLO)crystals have received substantial interest in advanced laser technology.However,tailoring a UV NLO material with a large second harmonic generation(SHG)response and good UV transp... Ultraviolet(UV)nonlinear optical(NLO)crystals have received substantial interest in advanced laser technology.However,tailoring a UV NLO material with a large second harmonic generation(SHG)response and good UV transparency remains a challenge.Here,inspired by the classic A3-RE2-[BO3]3 parent template,two new rare-earth borate NLO crystals,RbNa2La2(BO3)3(RNLBO-Ⅰ)and Rb0.681Na2.319La2(BO3)3(RNLBO-Ⅱ),were extracted by merging larger ionic radius cations Rb+and La3+simultaneously using a chemical substitution-oriented strategy.As expected,both compounds achieve significant enhancements in SHG activities,reaching 4.5×and 4.3×KDP,respectively,exceeding three times that of the isomorphic Na3Gd2B3O9.Notably,RNLBO-Ⅰdisplayed the highest SHG response among alkali metal RE-borate NLO crystals containing isolated[BO3]groups in the short-wave UV region.Moreover,RNLBO-Ⅰand-Ⅱdemonstrated short UV cutoff edges at 213 and 207 nm,corresponding to wide bandgaps of 5.3 and 5.6 eV,respectively.Additionally,theoretical calculations and dipole moment analysis were conducted to clarify the origin of the enhanced SHG activities of RNLBO-Ⅰand-Ⅱ.The optimal balance between SHG intensity and UV transparency in RNLBO-Ⅰand-Ⅱunderscores their potential as UV NLO candidates and offers valuable insights for fabricating new advanced UV NLO materials. 展开更多
关键词 Rare-earth borates Second harmonic generation Chemical substitution strategy Microscopic polarizability UV nonlinear optical crystals
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Multimodal Trajectory Generation for Robotic Motion Planning Using Transformer-Based Fusion and Adversarial Learning 认领 引用 被引量：1
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作者 Shtwai Alsubai Ahmad Almadhor +3 位作者 Abdullah Al Hejaili Najib Ben Aoun Tahani Alsubait Vincent Karovic 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第2期848-869,共22页
In Human–Robot Interaction(HRI),generating robot trajectories that accurately reflect user intentions while ensuring physical realism remains challenging,especially in unstructured environments.In this study,we devel... In Human–Robot Interaction(HRI),generating robot trajectories that accurately reflect user intentions while ensuring physical realism remains challenging,especially in unstructured environments.In this study,we develop a multimodal framework that integrates symbolic task reasoning with continuous trajectory generation.The approach employs transformer models and adversarial training to map high-level intent to robotic motion.Information from multiple data sources,such as voice traits,hand and body keypoints,visual observations,and recorded paths,is integrated simultaneously.These signals are mapped into a shared representation that supports interpretable reasoning while enabling smooth and realistic motion generation.Based on this design,two different learning strategies are investigated.In the first step,grammar-constrained Linear Temporal Logic(LTL)expressions are created from multimodal human inputs.These expressions are subsequently decoded into robot trajectories.The second method generates trajectories directly from symbolic intent and linguistic data,bypassing an intermediate logical representation.Transformer encoders combine multiple types of information,and autoregressive transformer decoders generate motion sequences.Adding smoothness and speed limits during training increases the likelihood of physical feasibility.To improve the realism and stability of the generated trajectories during training,an adversarial discriminator is also included to guide them toward the distribution of actual robot motion.Tests on the NATSGLD dataset indicate that the complete system exhibits stable training behaviour and performance.In normalised coordinates,the logic-based pipeline has an Average Displacement Error(ADE)of 0.040 and a Final Displacement Error(FDE)of 0.036.The adversarial generator makes substantially more progress,reducing ADE to 0.021 and FDE to 0.018.Visual examination confirms that the generated trajectories closely align with observed motion patterns while preserving smooth temporal dynamics. 展开更多
关键词 Multimodal trajectory generation robotic motion planning transformer networks sensor fusion reinforcement learning generative adversarial networks
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Knowledge Graph-Driven Training Data Construction for Urban Flood-Traffic Scenario Generation Using Small Language Models 认领 引用
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作者 Geunhwi Park Juneyoung Park +1 位作者 Chunjoo Yoon Jaehong Park 《Computers, Materials & Continua》 SCIE EI 2026年第8期2128-2151,共24页
Urban flooding caused by extreme rainfall events disrupts transportation systems,yet generating realistic flood-traffic scenarios for disaster preparedness remains a labor-intensive manual process.This study proposes ... Urban flooding caused by extreme rainfall events disrupts transportation systems,yet generating realistic flood-traffic scenarios for disaster preparedness remains a labor-intensive manual process.This study proposes a Knowledge Graph(KG)-driven pipeline that automatically generates domain-specific training data for fine-tuning small language models(sLLMs)to synthesize urban flood-traffic scenarios.A domain KG comprising 58 entities and 285 relationships was constructed for Jinju City,South Korea,integrating empirical flood data from 112 local documents with quantitative rainfall-traffic impact values from 14 international studies.Nine domain constraint rules,including a novel spatial consistency rule,ensure the physical plausibility of generated scenarios.Through constrained weighted graph walks,800 semi-structured English narrative scenarios were automatically generated in approximately 5 min,substantially reducing the labor required compared to manual creation.Three sLLMs spanning different architectures and parameter scales—Flan-T5-Large(770M),Qwen2.5-3B-Instruct(3B),and Qwen2.5-7B-Instruct(7B)—were fine-tuned using QLoRA on a single GPU with 16 GB VRAM.Evaluation on 78 test samples demonstrated consistent performance improvements with increasing model scale:Qwen2.5-7B achieved BLEU-4 of 0.5524,ROUGE-L of 0.6883,BERTScore F1 of 0.9662,and KG Fact Consistency of 1.0000,representing a 33.8%BLEU-4 improvement over Flan-T5-Large.Both Qwen models achieved KG Fact Consistency of 1.0000.The 3B model achieved 98.6%of the 7B model’s BLEU-4 at 53%of the VRAM cost with identical factual consistency,representing the most cost-effective configuration.All models were trained for 10 epochs on the same GPU,demonstrating practical feasibility for municipal disaster response deployment. 展开更多
关键词 Knowledge graph training data generation urban flood traffic scenario small language model fine-tuning text generation QLoRA
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Role of trajectory symmetry in solid high-order harmonic generation 认领 引用
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作者 Shuang Wang Yu Zhao +3 位作者 Hui-Rong Wang Yun-He Xing Xiao-Xin Huo Jun Zhang 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第4期425-431,共7页
High-order harmonic generation(HHG)from a ZnO crystal has been investigated theoretically using a two-band model driven by a few-cycle laser pulse.We observe that harmonics in the cut-off region exhibit periodic frequ... High-order harmonic generation(HHG)from a ZnO crystal has been investigated theoretically using a two-band model driven by a few-cycle laser pulse.We observe that harmonics in the cut-off region exhibit periodic frequency shifts with changes in the carrier envelope phase(CEP)of the laser field.When the CEP of the laser pulse is an integer multiple of π,the cut-off region is dominated by even-order harmonics rather than odd-order harmonics.To illustrate the physical mechanism behind the even-order harmonics,we track the trajectories of electrons and holes between two successive halfcycles by performing time-frequency analysis and applying the recollision model.The results show that the maximum electron displacement is symmetric between successive half-cycles for odd-order harmonics.In contrast,the half-cycle symmetry of the maximum displacement is broken in the case of even-order harmonics. 展开更多
关键词 high-order harmonic generation recollision model trajectory analyses
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Data-driven intelligent analysis of hydrocarbon generation kinetics and differential characteristics during pyrolysis of coal macerals 认领 引用
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作者 Yijie Wen Zongsen Yao +5 位作者 Fan Yang Yi Cui Shouqing Yan Bin Yu Zijian Zhang Shu Tao 《International Journal of Coal Science & Technology》 SCIE EI CAS CSCD 2026年第2期427-447,共21页
The heterogeneity of macerals represents a key challenge to accurately evaluating the hydrocarbon generation potential of coal.Conventional methods often overlook these differences,leading to biased understanding of i... The heterogeneity of macerals represents a key challenge to accurately evaluating the hydrocarbon generation potential of coal.Conventional methods often overlook these differences,leading to biased understanding of its hydrocarbon generation characteristics.Therefore,this study integrates maceral identification,thermal simulation experiments,and machine learning algorithms to develop the extreme gradient boosting(XGBoost)prediction models for the yields of gaseous and liquid hydrocarbons.This approach enables enabling quantitative characterization of the hydrocarbon generation behavior of different macerals and identification of their primary controlling factors of coal in Xishanyao(J2x)Formation of Taibei Sag,China.The results indicate that the correlation coefficients of the prediction models for gaseous and liquid hydrocarbon yields are 0.98 and 0.78,respectively,and the difference in prediction accuracy between the two productions arises from differences in the primary controlling factors of hydrocarbon generation.SHAP and ANOVA analyses indicate that temperature is the primary controlling factor for gaseous hydrocarbon generation,whereas liquid hydrocarbon yields are synergistically controlled by temperature and macerals type.Among the macerals,sporinite is the favorable oil-prone component,while cutinite is characterized by“early oil and late gas.”Collotelinite is the principal gas-prone component,whereas collodetrinite and corpogelinite display relatively balanced potential for oil and gas.The differentiated hydrocarbon generation characteristics of the various macerals is essentially governed by differences in their molecular structures.The aliphatic chain structures primarily control oil generation,aromaticity governs gas generation,and bond types determine the distribution of the hydrocarbon generation window.Based on the above results,the study further delineates three types of favorable hydrocarbon-generating zones,namely Class Ⅰ and Class Ⅱ oil-gas co-generation zones and Class Ⅱ oil-generating zones. 展开更多
关键词 Taibei Sag Maceral Hydrocarbon generation kinetics Machine learning
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Investigating the gas generation during Li plating in fast-charging Li-ion batteries 认领 引用
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作者 Yuanmao Chen Luoyi Ding +7 位作者 Qinghui Zeng Yongteng Dong Xinyang Yue Xianping Si Donglin Zhang Qingtuan Qu Zheng Liang Wei Hao 《Chinese Chemical Letters》 SCIE CAS CSCD 2026年第7期696-701,共6页
Lithium plating and gas evolution during fast charging of graphite-based lithium-ion batteries(LIBs)are among the pivotal challenges contributing to rapid capacity loss.However,the mechanisms underlying gas generation... Lithium plating and gas evolution during fast charging of graphite-based lithium-ion batteries(LIBs)are among the pivotal challenges contributing to rapid capacity loss.However,the mechanisms underlying gas generation and corresponding mitigation strategies in electrolytes comprising mixed organic molecules and Li salts remain underexplored.Herein,we employed first-principles studies to simulate the lithiation process of electrolytes and predicted gas formation at anode interfaces with Li plating.Our results emphasize the critical role of Li salts in initiating solvent molecule decomposition and the exacerbation of interfacial degradation under conditions of elevated temperature and prolonged annealing,giving rise to the production of CO,C2H4,CH4,and H2,along with a significant increase in SEI's electronic conductivity.Moreover,our computations highlight that ethylene carbonate(EC)in commercial electrolytes is the overarching cause of interface instability and gas evolution.Experimental validations demonstrate that reducing the EC content in electrolytes results in an enhancement of the specific capacity of LiNi0.8Co0.1Mn0.1O2|graphite full cells from 158.13 m Ah/g to 182.53 m Ah/g,and an improvement in capacity retention from 72.0%to 80.4%over 130 cycling at 3 C.This research provides a theoretical framework for designing fast-charging electrolytes with stable interfaces and minimal gas generation. 展开更多
关键词 Li-ion battery Gas generation Fast charging Li plating Electrolyte engineering
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High harmonic generation in solids driven by optical skyrmions 认领 引用
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作者 Jianing Zhang Zijian Lyu +4 位作者 Xiulan Liu Guanglu Yuan Zhengliang Li Yunquan Liu Liang-You Peng 《Advanced Photonics Nexus》 CSCD 2026年第1期224-235,共12页
With their intricate vectorial structures in space,optical skyrmions have significantly expanded the landscape of topological optics and light-matter interactions.We theoretically investigate high harmonic generation ... With their intricate vectorial structures in space,optical skyrmions have significantly expanded the landscape of topological optics and light-matter interactions.We theoretically investigate high harmonic generation in crystals driven by optical skyrmions.We find that although the skyrmion number is not conserved,the resulting high-order harmonics can exhibit a distinctive multi-vortex structure,whose features are shaped by both the topology of the optical skyrmions and the rotational symmetry of the crystal.The position of the vortex centers can be effectively tuned by employing different types of optical skyrmions.To elucidate the underlying physics,we develop a multi-absorption channel model based on the conservation laws of spin and orbital angular momentum.Our work explores the role of optical topology in extreme nonlinear light-matter interactions,offering new opportunities for the formation and manipulation of optical vortices and novel structured light fields in the visible and ultraviolet regimes. 展开更多
关键词 skyrmions high harmonic generation optical vortex spin conservation law
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Logic-Aware Security Playbook Generation for SOAR Using Adversarial Representation Learning 认领 引用
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作者 Hangyu Hu Liangrui Zhang +4 位作者 Xiaowei Huang Xingmiao Yao Youyang Qu Xia Wu Guangmin Hu 《Computers, Materials & Continua》 SCIE EI 2026年第9期1219-1237,共19页
With the evolution of information technology toward more advanced intelligence and automation,Security Orchestration,Automation,and Response(SOAR)has become a critical foundation for security incident handling,owing t... With the evolution of information technology toward more advanced intelligence and automation,Security Orchestration,Automation,and Response(SOAR)has become a critical foundation for security incident handling,owing to its intelligent orchestration capabilities.Security playbooks,as the core mechanism for automated response in SOAR,require well-designed workflows and precise action matching to ensure efficient and accurate alert handling.However,with the rising sophistication of attacks and the expanding scale of security alerts,traditional expert-driven playbook recommendation approaches often degrade in recommendation quality or completely fail when existing playbook repositories cannot adequately cover unknown or novel alert scenarios.Generative Adversarial Network(GAN)offers a promising solution by capturing feature associations from existing playbooks and autonomously generating validated new playbooks tailored to previously unseen alert characteristics.Motivated by this,we propose a logic-aware,two-stage GAN-based playbook generation method in this paper.In the first stage,alert features are projected into a modeled playbook feature space to perform preliminary similarity matching.In the second stage,a hybrid strategy combining similarity-based recommendation and GAN-driven generation is used to produce and refine playbooks while preserving logical workflow integrity.Experimental results demonstrate that the proposed approach not only delivers high-precision playbook recommendations for known alert scenarios but also efficiently generates reliable playbooks for unseen alerts,achieving an average alert handling success rate of 86.55%,and thereby fulfilling response requirements in previously uncovered scenarios. 展开更多
关键词 SOAR security intelligent recommendation playbook generation generative adversarial network
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Measuring the Coulomb time shift in high-order harmonic generation 认领 引用
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作者 Shengjun Yue Siqi Song +3 位作者 Ruofeng Zhong Jiangkun Li Haiyuan Yu Hongchuan Du 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第4期61-70,共10页
High-order harmonic generation(HHG),a key nonlinear phenomenon in strong-field physics,enables ultrafast detection on the attosecond timescale.Quantifying ionizationecombination times is essential for trajectory-resol... High-order harmonic generation(HHG),a key nonlinear phenomenon in strong-field physics,enables ultrafast detection on the attosecond timescale.Quantifying ionizationecombination times is essential for trajectory-resolved highharmonic spectroscopy and for benchmarking its temporal resolution.In this review,we summarize our recent studies[Phys.Rev.A 105 L041103(2022),Phys.Rev.A 106023117(2022),Phys.Rev.A 107063102(2023),Phys.Rev.A111039902(2025)]on the role of electron-core interactions in HHG.Employing the classical trajectory model,analytical R-matrix theory,and numerical solutions of time-dependent Schrodinger equations for helium,we reveal how Coulomb attraction induces subtle shifts in ionization and recombination times.Such effects emerge as observable signatures under orthogonally polarized bichromatic fields at high probe frequencies.Because of the direct experimental relevance of these findings,this review seeks to stimulate further experimental efforts to control and resolve electron dynamics in HHG.In the future,it will be of great interest to(i)refine retrieval methods by incorporating Coulomb corrections beyond the staticfield approximation,and(ii)advance two-color detection techniques with the capability to reconstruct complete quantum trajectories in HHG. 展开更多
关键词 high-order harmonic generation ultrafast electron dynamics Coulomb effects attosecond science
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Autonomous driving scenario generation based on neural radiance fields or 3D Gaussian splatting:State-of-the-art investigations,reviews,and perspectives 认领 引用
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作者 Wei Zhou Wenbo Chu +4 位作者 Yue Tian Tianyang Fei Yulong Ding Xiaolin Tang Keqiang Li 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2026年第2期226-240,共15页
Reconstruction of autonomous driving scenarios plays a pivotal role in vehicle testing.In recent years,approaches based on Neural Radiance Fields(NeRF) and 3D Gaussian Splatting(3D GS) have opened new avenues for enha... Reconstruction of autonomous driving scenarios plays a pivotal role in vehicle testing.In recent years,approaches based on Neural Radiance Fields(NeRF) and 3D Gaussian Splatting(3D GS) have opened new avenues for enhancing the performance of vehicle testing systems.This paper provides a systematic review of the latest research progress on NeRF and 3D GS in the context of autonomous driving scene reconstruction and explores their potential for future applications in the development of autonomous driving test systems.First,the paper briefly reviews the development trajectories of NeRF and 3D GS,presenting a concise timeline of representative works based on major databases such as Web of Science,IEEE Xplore,and arXiv,thereby offering essential background for the subsequent discussion.Next,the current state of research is comprehensively analyzed,with a particular focus on advancements in model architecture,scene editing,and the reconstruction of challenging autonomous driving scenarios.Finally,the paper outlines a research outlook on an integrated test system centered on NeRF or 3D GS,encompassing modules for large-scale dynamic scene reconstruction,autonomous scene editing,and perception-decision algorithms.This integrated framework aims to provide a valuable reference for building efficient and scalable testing platforms for autonomous driving. 展开更多
关键词 Autonomous driving Scenario generation Neural radiance fields 3D Gaussian splatting
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Electroosmotic Transport and Entropy Generation in ZnO-Williamson Nanoblood Flow through a Converging/Diverging Tapered Stenosed Artery 认领 引用
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作者 Noor Fadiya Mohd Noor Noreen Sher Akbar +1 位作者 Rashid Mehmood Muhammad Bilal Habib 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第3期663-691,共29页
Electroosmotic transport and entropy generation play a decisive role in regulating efficiency,stability,and energy cost of non-Newtonian nanoblood flows in stenosed arteries,particularly with tapered geometries.Thisst... Electroosmotic transport and entropy generation play a decisive role in regulating efficiency,stability,and energy cost of non-Newtonian nanoblood flows in stenosed arteries,particularly with tapered geometries.Thisstudy develops a unified model to analyze ZnO-Williamson nanoblood flow through a stenosed artery with converging,diverging,and non-tapered configurations,incorporating electroosmosis,viscous dissipation,and entropy production.The arterial walls are assumed to be electrically charged with a no-slip condition to induce electroosmotic propulsionalong the endothelial surface.The partial differential equations are nondimensionalized to a coupled system ofnonlinear ordinary differential equations,which are solved numerically using a MATLAB-based shooting technique.Parametric investigation is conducted for Brinkman,Grashof,and Weissenberg numbers,ZnO fractional volume,volumetric flow rate,and Helmholtz-Smoluchowski velocity to quantify their influences on axial velocity,wall shearstress,impedance resistance,temperature distribution,entropy generation,Bejan number,and streamline topology.The axial velocity decreases radially with increasing Brinkman number for all arterial geometries.Increasing ZnOnanoparticles improves thermal transport owing to enhanced effective thermal conductivity but simultaneously elevatesentropy generation due to increased viscous dissipation.Higher Weissenberg numbers suppress entropy production bypromoting elastic stress redistribution and lowering shear-induced irreversibility.Impedance resistance decreases withincreasing stenosis height but increases with stenosis shape parameter and ZnO fractional volume.Streamline analysisshows that buoyancy and viscoelasticity significantly distort flow near the stenosis,while increasing electroosmoticvelocity stabilizes streamlines,suppresses recirculation,and reduces local shear stress and pressure fluctuations.Inconclusion,electroosmotic actuation is most effective in reducing flow resistance in the converging tapered artery,particularly at lower ZnO volume fractions.Overall,the findings highlight the potential of optimized electroosmoticactuation and controlled nanoparticle loading to minimize thermodynamic losses,regulate shear stress,and improveflow uniformity in stenosed vessels,with promising implications for electro-assisted drug delivery,nanotherapeutics,and bio-inspired vascular microfluidic systems. 展开更多
关键词 Electroosmosis entropy generation Williamson ZnO-blood stenosis tapered artery
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High-performance thermomagnetic generation in low-grade waste heat recovery 认领 引用
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作者 Haodong Chen Hu Zhang +4 位作者 Mingze Liu Kaiming Qiao Lichen Wang Fengxia Hu Baogen Shen 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第2期25-41,共17页
Thermomagnetic generation(TMG),a heat-to-electricity conversion technology based on the thermomagnetic effect,offers high reliability and broad adaptability to diverse heat sources.By exploiting the temperature-depend... Thermomagnetic generation(TMG),a heat-to-electricity conversion technology based on the thermomagnetic effect,offers high reliability and broad adaptability to diverse heat sources.By exploiting the temperature-dependent magnetization of thermomagnetic materials,TMG converts thermal energy into electrical energy through cyclic changes in magnetic flux based on Faraday's law.The performance of TMG systems is largely governed by the intrinsic properties of the working materials and the design of device architecture.Ideal TMG materials exhibit sharp and reversible magnetization transitions near the operating temperature,low thermal hysteresis,and high thermal conductivity.Device configurations can be broadly categorized into active and passive systems:active TMG devices rely on controlled thermal cycling and optimized magnetic circuits for enhanced output,whereas passive devices utilize self-actuated mechanical motion to generate electricity.In this topical review,we provide a comprehensive overview of recent advances in TMG materials and device configurations.Furthermore,we discuss future development trends and offer perspectives on experimental strategies to advance this field. 展开更多
关键词 low grade waste heat thermal energy recovery thermomagnetic generation
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From architecture to evaluation:A comprehensive review of video generation techniques 认领 引用
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作者 Rong ZHANG Chi WANG +1 位作者 Guojun LEI Weiwei XU 《虚拟现实与智能硬件（中英文）》 EI CSCD 2026年第2期172-201,共30页
The rapid developments of artificial intelligence have significantly impacted daily life and content production modes.In the field of video generation,researchers are now exploring this emerging technique with innovat... The rapid developments of artificial intelligence have significantly impacted daily life and content production modes.In the field of video generation,researchers are now exploring this emerging technique with innovative approaches,aiming to produce videos of higher quality,longer duration,and greater diversity.Currently,numerous video generation algorithms have been developed using different architecture designs.Unlike image generation,video generation requires maintaining consistency across both spatial and temporal dimensions while ensuring aesthetic quality and dynamic coherence,making it a more challenging task.In this survey,we provide a systematic review of existing video generation methods,tracing their evolution across different architectural paradigms.We further categorize recent models by their control conditions(e.g.,text-to-video,image to-video,multi-modal guidance)and summarize their unique theoretical foundations,architectural designs,and algorithmic innovations.In the meantime,we review the commonly used video datasets and analyze their applicability to different tasks.We also present evaluations of representative models to offer a more comprehensive perspective.Our goal is to provide a clear and concise overview of these algorithms,offering insights to support future breakthroughs in video generation. 展开更多
关键词 Video generation AIGC Video diffusion model Architecture design
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CAFE-GAN: CLIP-Projected GAN with Attention-Aware Generation and Multi-Scale Discrimination 认领 引用
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作者 Xuanhong Wang Hongyu Guo +3 位作者 Jiazhen Li Mingchen Wang Xian Wang Yijun Zhang 《Computers, Materials & Continua》 SCIE EI 2026年第1期1742-1760,共19页
Over the past decade,large-scale pre-trained autoregressive and diffusion models rejuvenated the field of text-guided image generation.However,these models require enormous datasets and parameters,and their multi-step... Over the past decade,large-scale pre-trained autoregressive and diffusion models rejuvenated the field of text-guided image generation.However,these models require enormous datasets and parameters,and their multi-step generation processes are often inefficient and difficult to control.To address these challenges,we propose CAFE-GAN,a CLIP-Projected GAN with Attention-Aware Generation and Multi-Scale Discrimination,which incorporates a pretrained CLIP model along with several key architectural innovations.First,we embed a coordinate attention mechanism into the generator to capture long-range dependencies and enhance feature representation.Second,we introduce a trainable linear projection layer after the CLIP text encoder,which aligns textual embeddings with the generator’s semantic space.Third,we design a multi-scale discriminator that leverages pre-trained visual features and integrates a feature regularization strategy,thereby improving training stability and discrimination performance.Experiments on the CUB and COCO datasets demonstrate that CAFE-GAN outperforms existing text-to-image generation methods,achieving lower Fréchet Inception Distance(FID)scores and generating images with superior visual quality and semantic fidelity,with FID scores of 9.84 and 5.62 on the CUB and COCO datasets,respectively,surpassing current state-of-the-art text-to-image models by varying degrees.These findings offer valuable insights for future research on efficient,controllable text-to-image synthesis. 展开更多
关键词 Large vision language models deep learning computer vision text-to-image generation
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