According to the deficiency of the strain accumulating and releasing curves and the previous models, the strain-accumulating rate of the strain accumulating and releasing model has been deduced based on the G-R relati...According to the deficiency of the strain accumulating and releasing curves and the previous models, the strain-accumulating rate of the strain accumulating and releasing model has been deduced based on the G-R relation and the empirical formula between energy release and earthquake magnitude, where the strain-accumulating rate is relative independent of the strain-releasing rate. Five typical areas in Chinese mainland are selected on the basis of the hypothesis on active tectonic block, and small earthquakes from 1970 are imported to calculate the annual strain-accumulating rates considering the completeness of historical seismic data. Having introduced the strain-accumulating rates into the amended model, present strain phases are got. According to the present stages in their own cycles, the future earthquake tendency of each sub-region is discussed.展开更多
On the occasion of the 65th anniversary of the establishment of diplomatic relations between China and Laos,I wish to express,on behalf of the Embassy of the People's Republic of China in the Lao People's Demo...On the occasion of the 65th anniversary of the establishment of diplomatic relations between China and Laos,I wish to express,on behalf of the Embassy of the People's Republic of China in the Lao People's Democratic Republic,our sincere gratitude and highest respect to all friends and personages from various sectors in both countries who have long cared about and supported the development of our bilateral relations.展开更多
The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects,radiative transfer,and microphysical processes.However,previous studies have been mostly concerned with clouds,with...The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects,radiative transfer,and microphysical processes.However,previous studies have been mostly concerned with clouds,with limited studies on fog,particularly those that examine the combined influences of all key physical processes and their roles during fog evolution.As such,this study aims to conduct a comprehensive investigation by examining the relationships between relative dispersion and other microphysical variables,as well as the underlying microphysical and dynamic processes,based on field fog campaigns in polluted and clean conditions.In polluted fog,droplet concentrations are higher,leading to smaller droplets and increased dispersion.The correlation between dispersion and droplet volume-mean radius is positive in the polluted fog,but shifts to negative in clean fog.We attribute the difference to various microphysical processes like aerosol activation,condensation,collision-coalescence,and entrainment-mixing.In polluted fog,high aerosol concentrations,low supersaturations,and strong turbulence(entrainment-mixing)provide suitable conditions for the simultaneous occurrence of droplet condensation and aerosol activation,resulting in a positive correlation between dispersion and volume-mean radius,especially during the fog formation stage.In contrast,during the mature stage in clean fog,condensation is dominant with weak aerosol activation leading to a negative correlation between relative dispersion and volume-mean radius.The collision-coalescence process is more active in the mature stage,increasing radii and leading to the negative correlation between dispersion and volume-mean radius.This result sheds new light on understanding the relative dispersion and mechanisms in fog under different aerosol backgrounds.展开更多
As an ordinary Yunnan local,I never imagined becoming so closely connected to the exotic land of Laos.The luckiest event of my life was probably my choice to tick a box on a 2007 college entrance examination applicati...As an ordinary Yunnan local,I never imagined becoming so closely connected to the exotic land of Laos.The luckiest event of my life was probably my choice to tick a box on a 2007 college entrance examination application form,indicating my willingness to enrollin a major other than my preference,which led me into the world of the Lao language.展开更多
On the threshold of 55 years of diplomatic relations,Cyprus and China stand to gain significantly by deepening their cooperation in trade,tourism,and green technology,guided by mutual respect and shared principles.WIT...On the threshold of 55 years of diplomatic relations,Cyprus and China stand to gain significantly by deepening their cooperation in trade,tourism,and green technology,guided by mutual respect and shared principles.WITH a population of approximately one million,Cyprus is a small country compared to China,which is home to more than 1.4 billion people.展开更多
Backgrounds:Somatization and eating-related problems in adolescents living in residential care may be shaped by the interplay of risk and protective factors,including gender,relational trauma,attachment patterns,emoti...Backgrounds:Somatization and eating-related problems in adolescents living in residential care may be shaped by the interplay of risk and protective factors,including gender,relational trauma,attachment patterns,emotional intelligence,and perceived social support.This study examined how gender,relational trauma,attachment dimensions,resilience,and emotional intelligence contribute to the presence of somatic and eating difficulties in this population.Methods:The sample included 46 adolescents(63%female;ages 12–17,Mean=14.85,Standard Deviation(SD)=1.49)residing in child protection institutions in Uruguay.Participants completed self-report measures assessing childhood relational trauma(CaMir),attachment dimensions(anxiety and avoidance),resilience,emotional intelligence(adaptability and stress management),social support(MOS),and psychosocial adjustment(SENA subscales of somatization and eating problems).Using a fuzzy-set Qualitative Comparative Analysis(fsQCA)approach,distinct configurations of risk and protective factors associated with elevated levels of somatization and eating problems were identified.Results:Relational trauma and attachment anxiety showed moderate associations with both somatization and eating problems(r=0.52–0.57,p<0.01),whereas stress management was negatively associated with both outcomes(r=−0.37 to−0.47,p<0.05).FsQCA revealed multiple configurations of risk and protective factors explaining 81–90%of cases,with solution consistencies ranging from 0.83 to 0.87.Results suggest that relational trauma and attachment anxiety are key risk conditions,whereas resilience,emotional regulation,and perceived social support function as protective factors.Conclusions:Findings highlight the importance of considering multifactorial patterns of vulnerability and protection rather than single predictors and underscore the need for tailored interventions that strengthen resilience and emotional skills while addressing the impact of early relational trauma.展开更多
Robust cooperative unmanned aerial vehicle(UAV)formation in complex 3D environments is hampered by reward sparsity and inefficient collaboration.To address this,we propose context-aware relational agent learning(CORAL...Robust cooperative unmanned aerial vehicle(UAV)formation in complex 3D environments is hampered by reward sparsity and inefficient collaboration.To address this,we propose context-aware relational agent learning(CORAL),a novel multi-agent deep reinforcement learning framework.CORAL synergistically integrates two modules:(1)a novelty-based intrinsic reward module to drive efficient exploration and(2)an explicit relational learning module that allows agents to predict peer intentions and enhance coordination.Built on a multi-agent Actor-Critic architecture,CORAL enables agents to balance self-interest with group objectives.Comprehensive evaluations in a high-fidelity simulation show that our method significantly outperforms state-of-theart baselines like multi-agent deep deterministic policy gradient(MADDPG)and monotonic value function factorisation for deep multi-agent reinforcement learning(QMIX)in path planning efficiency,collision avoidance,and scalability.展开更多
British Prime Minister Keir Starmer’s visit to China underscores economic cooperation and strategic stability amid global uncertainties.U.K.Prime Minister Keir Starmer’s visit to China in January marks a significant...British Prime Minister Keir Starmer’s visit to China underscores economic cooperation and strategic stability amid global uncertainties.U.K.Prime Minister Keir Starmer’s visit to China in January marks a significant shift of Britain toward a more pragmatic and stability-oriented approach in Sino-British relations.After years of political tensions and limited high-level engagement,this trip underscores London’s intent to rebuild ties based on mutual economic and strategic interests.展开更多
Vaginal delivery is a fascinating physiological process,but also a high-risk process.Up to 85%–90%of vaginal deliveries lead to perineal trauma,with nearly 11%of severe perineal tearing.It is a common occurrence,espe...Vaginal delivery is a fascinating physiological process,but also a high-risk process.Up to 85%–90%of vaginal deliveries lead to perineal trauma,with nearly 11%of severe perineal tearing.It is a common occurrence,especially for first-time mothers.Computational childbirth plays an essential role in the prediction and prevention of these traumas,but fast personalization of the pelvis and floor muscles is challenging due to their anatomical complexity.This study introduces a novel shape-prediction-based personalization of the pelvis and floor muscles for perineal tearing management and childbirth simulation.300 subjects were selected from public Computed Tomography(CT)databases.The pelvic bone nmjmeshes were generated using a coarse-to-fine non-rigid mesh alignment procedure.The floor muscle meshes were personalized using the bone mesh deformation information.A feature-to-pelvic structure reconstruction pipeline was proposed,incorporating various strategies.Ten-fold cross-validation helped determine the optimal reconstruction strategy,regression method,and feature sizes.The mesh-to-mesh distance metric was employed for evaluating.The statistical shape relation-based strategy,coupled with multi-output ridge regression,was the optimal approach for pelvic structure reconstruction.With a feature set ranging from 3 to 38,the mean errors were 2.672 to 1.613 mm,and 3.237 to 1.415 mm in muscle attachment regions.The best-and worst-case predictions had errors of 1.227±0.959 mm and 2.900±2.309 mm,respectively.This study provides a novel approach to achieving fast personalized childbirth modeling and simulation for perineal tearing management.展开更多
Background: This study focuses on the fabrication and optimization of Ti6Al4V alloy latticestructures produced by the Selective Laser Melting (SLM) process. Such structures areincreasingly used in biomedical implants ...Background: This study focuses on the fabrication and optimization of Ti6Al4V alloy latticestructures produced by the Selective Laser Melting (SLM) process. Such structures areincreasingly used in biomedical implants due to their potential to match the mechanicalproperties of human bone. Key features influencing their performance include porosity ratio,surface roughness, elastic modulus, and yield strength. Achieving a balance between theseparameters is essential for ensuring both mechanical integrity and biological compatibility.Methods: The Taguchi method integrated with Grey Relational Analysis (GRA) wasemployed to optimize the SLM process parameters—laser power (160-240 J), scanningspeed (1000-1500 mm/min), and hatch spacing (0.06-0.12 mm). The optimization aimed toproduce lattice structures with properties closely resembling human bone. Experimentaltrials were conducted to evaluate the effects of these parameters on porosity, surfaceroughness, elastic modulus, and yield strength, followed by statistical and relational analysisto determine the optimal configuration. Results: The results revealed that higher scanningspeed, wider hatch spacing, and lower laser power increased the porosity ratio compared toCAD models. A strong inverse relationship was observed between porosity and both yieldstrength and elastic modulus. Increasing laser power substantially reduced surfaceroughness. Through Taguchi-GRA optimization, the optimal parameter combination wasdetermined as laser power of 240 J, scanning speed of 1250 mm/min, and hatch spacing of0.06 mm. Under these conditions, the obtained values were: modulus of elasticity (0°) = 20GPa, modulus of elasticity (90°) = 18.874 GPa, yield strength (0°) = 265 MPa, yieldstrength (90°) = 260 MPa, porosity = 48.565%, and surface roughness = 6.223 μm.Conclusion: The optimized SLM parameters successfully produced Ti6Al4V latticestructures with mechanical and morphological characteristics compatible with human bone.The study highlights the critical balance between process parameters and structuralfeatures, providing a systematic approach for tailoring lattice structures for biomedicalapplications through Taguchi and GRA-based optimization.展开更多
Given the scarcity of Satellite Frequency and Orbit(SFO)resources,it holds paramount importance to establish a comprehensive knowledge graph of SFO field(SFO-KG)and employ knowledge reasoning technology to automatical...Given the scarcity of Satellite Frequency and Orbit(SFO)resources,it holds paramount importance to establish a comprehensive knowledge graph of SFO field(SFO-KG)and employ knowledge reasoning technology to automatically mine available SFO resources.An essential aspect of constructing SFO-KG is the extraction of Chinese entity relations.Unfortunately,there is currently no publicly available Chinese SFO entity Relation Extraction(RE)dataset.Moreover,publicly available SFO text data contain numerous NA(representing for“No Answer”)relation category sentences that resemble other relation sentences and pose challenges in accurate classification,resulting in low recall and precision for the NA relation category in entity RE.Consequently,this issue adversely affects both the accuracy of constructing the knowledge graph and the efficiency of RE processes.To address these challenges,this paper proposes a method for extracting Chinese SFO text entity relations based on dynamic integrated learning.This method includes the construction of a manually annotated Chinese SFO entity RE dataset and a classifier combining features of SFO resource data.The proposed approach combines integrated learning and pre-training models,specifically utilizing Bidirectional Encoder Representation from Transformers(BERT).In addition,it incorporates one-class classification,attention mechanisms,and dynamic feedback mechanisms to improve the performance of the RE model.Experimental results show that the proposed method outperforms the traditional methods in terms of F1 value when extracting entity relations from both balanced and long-tailed datasets.展开更多
Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be so...Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be solved. A comprehensive evaluation method is proposed, which combines grey relational analysis (GRA) and cloud model, to evaluate the anti-jamming performances of Link-16. Firstly, on the basis of establishing the anti-jamming performance evaluation indicator system of Link-16, the linear combination of analytic hierarchy process(AHP) and entropy weight method (EWM) are used to calculate the combined weight. Secondly, the qualitative and quantitative concept transformation model, i.e., the cloud model, is introduced to evaluate the anti-jamming abilities of Link-16 under each jamming scheme. In addition, GRA calculates the correlation degree between evaluation indicators and the anti-jamming performance of Link-16, and assesses the best anti-jamming technology. Finally, simulation results prove that the proposed evaluation model can achieve the objective of feasible and practical evaluation, which opens up a novel way for the research of anti-jamming performance evaluations of Link-16.展开更多
Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex,high-dimensional data that single-view methods cannot capture.Traditional fuzzy cl...Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex,high-dimensional data that single-view methods cannot capture.Traditional fuzzy clustering techniques,such as Fuzzy C-Means(FCM),face significant challenges in handling uncertainty and the dependencies between different views.To overcome these limitations,we introduce a new multi-view fuzzy clustering approach that integrates picture fuzzy sets with a dual-anchor graph method for multi-view data,aiming to enhance clustering accuracy and robustness,termed Multi-view Picture Fuzzy Clustering(MPFC).In particular,the picture fuzzy set theory extends the capability to represent uncertainty by modeling three membership levels:membership degrees,neutral degrees,and refusal degrees.This allows for a more flexible representation of uncertain and conflicting data than traditional fuzzy models.Meanwhile,dual-anchor graphs exploit the similarity relationships between data points and integrate information across views.This combination improves stability,scalability,and robustness when handling noisy and heterogeneous data.Experimental results on several benchmark datasets demonstrate significant improvements in clustering accuracy and efficiency,outperforming traditional methods.Specifically,the MPFC algorithm demonstrates outstanding clustering performance on a variety of datasets,attaining a Purity(PUR)score of 0.6440 and an Accuracy(ACC)score of 0.6213 for the 3 Sources dataset,underscoring its robustness and efficiency.The proposed approach significantly contributes to fields such as pattern recognition,multi-view relational data analysis,and large-scale clustering problems.Future work will focus on extending the method for semi-supervised multi-view clustering,aiming to enhance adaptability,scalability,and performance in real-world applications.展开更多
During Donald Trump’s first term,the“Trump Shock”brought world politics into an era of uncertainties and pulled the transatlantic alliance down to its lowest point in history.The Trump 2.0 tsunami brewed by the 202...During Donald Trump’s first term,the“Trump Shock”brought world politics into an era of uncertainties and pulled the transatlantic alliance down to its lowest point in history.The Trump 2.0 tsunami brewed by the 2024 presidential election of the United States has plunged the U.S.-Europe relations into more gloomy waters,ushering in a more complex and turbulent period of adjustment.展开更多
Collecting amounts of distorted/clean image pairs in the real world is non-trivial,which severely limits the practical application of these supervised learning-based methods to real-world image super-resolution(RealSR...Collecting amounts of distorted/clean image pairs in the real world is non-trivial,which severely limits the practical application of these supervised learning-based methods to real-world image super-resolution(RealSR).Previous works usually address this problem by leveraging unsupervised learning-based technologies to alleviate the dependency on paired training samples.However,these methods typically suffer from unsatisfactory texture synthesis due to the lack of supervision of clean images.To overcome this problem,we are the first to take a close look at the under-explored direction for RealSR,i.e.,few-shot real-world image super-resolution,which aims to tackle the challenging RealSR problem with few-shot distorted/clean image pairs.Under this brand-new scenario,we propose distortion relation guided transfer learning(DRTL)for the few-shot RealSR by transferring the rich restoration knowledge from auxiliary distortions(i.e.,synthetic distortions)to the target RealSR under the guidance of the distortion relation.Concretely,DRTL builds a knowledge graph to capture the distortion relation between auxiliary distortions and target distortion(i.e.,real distortions in RealSR).Based on the distortion relation,DRTL adopts a gradient reweighting strategy to guide the knowledge transfer process between auxiliary distortions and target distortions.In this way,DRTL is able to quickly learn the most relevant knowledge from the synthetic distortions for the target distortion.We instantiate DRTL with two commonly-used transfer learning paradigms,including pretraining and meta-learning pipelines,to realize a distortion relation-aware few-shot RealSR.Extensive experiments on multiple benchmarks and thorough ablation studies demonstrate the effectiveness of our DRTL.展开更多
基金State Key Basic Research Development and Programming Project of China (G19980407) and Social Commonweal Research Project of the Ministry of Science and Technology (2002DIA10001).
文摘According to the deficiency of the strain accumulating and releasing curves and the previous models, the strain-accumulating rate of the strain accumulating and releasing model has been deduced based on the G-R relation and the empirical formula between energy release and earthquake magnitude, where the strain-accumulating rate is relative independent of the strain-releasing rate. Five typical areas in Chinese mainland are selected on the basis of the hypothesis on active tectonic block, and small earthquakes from 1970 are imported to calculate the annual strain-accumulating rates considering the completeness of historical seismic data. Having introduced the strain-accumulating rates into the amended model, present strain phases are got. According to the present stages in their own cycles, the future earthquake tendency of each sub-region is discussed.
文摘On the occasion of the 65th anniversary of the establishment of diplomatic relations between China and Laos,I wish to express,on behalf of the Embassy of the People's Republic of China in the Lao People's Democratic Republic,our sincere gratitude and highest respect to all friends and personages from various sectors in both countries who have long cared about and supported the development of our bilateral relations.
基金supported by the Chinese National Natural Science Foundation under Grant Nos.(41975181,42325503,42375197,42575207,42205090)Y.LIU is supported by the U.S.Department of Energy’s Atmospheric System Research(ASR)program.
文摘The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects,radiative transfer,and microphysical processes.However,previous studies have been mostly concerned with clouds,with limited studies on fog,particularly those that examine the combined influences of all key physical processes and their roles during fog evolution.As such,this study aims to conduct a comprehensive investigation by examining the relationships between relative dispersion and other microphysical variables,as well as the underlying microphysical and dynamic processes,based on field fog campaigns in polluted and clean conditions.In polluted fog,droplet concentrations are higher,leading to smaller droplets and increased dispersion.The correlation between dispersion and droplet volume-mean radius is positive in the polluted fog,but shifts to negative in clean fog.We attribute the difference to various microphysical processes like aerosol activation,condensation,collision-coalescence,and entrainment-mixing.In polluted fog,high aerosol concentrations,low supersaturations,and strong turbulence(entrainment-mixing)provide suitable conditions for the simultaneous occurrence of droplet condensation and aerosol activation,resulting in a positive correlation between dispersion and volume-mean radius,especially during the fog formation stage.In contrast,during the mature stage in clean fog,condensation is dominant with weak aerosol activation leading to a negative correlation between relative dispersion and volume-mean radius.The collision-coalescence process is more active in the mature stage,increasing radii and leading to the negative correlation between dispersion and volume-mean radius.This result sheds new light on understanding the relative dispersion and mechanisms in fog under different aerosol backgrounds.
文摘As an ordinary Yunnan local,I never imagined becoming so closely connected to the exotic land of Laos.The luckiest event of my life was probably my choice to tick a box on a 2007 college entrance examination application form,indicating my willingness to enrollin a major other than my preference,which led me into the world of the Lao language.
文摘On the threshold of 55 years of diplomatic relations,Cyprus and China stand to gain significantly by deepening their cooperation in trade,tourism,and green technology,guided by mutual respect and shared principles.WITH a population of approximately one million,Cyprus is a small country compared to China,which is home to more than 1.4 billion people.
文摘Backgrounds:Somatization and eating-related problems in adolescents living in residential care may be shaped by the interplay of risk and protective factors,including gender,relational trauma,attachment patterns,emotional intelligence,and perceived social support.This study examined how gender,relational trauma,attachment dimensions,resilience,and emotional intelligence contribute to the presence of somatic and eating difficulties in this population.Methods:The sample included 46 adolescents(63%female;ages 12–17,Mean=14.85,Standard Deviation(SD)=1.49)residing in child protection institutions in Uruguay.Participants completed self-report measures assessing childhood relational trauma(CaMir),attachment dimensions(anxiety and avoidance),resilience,emotional intelligence(adaptability and stress management),social support(MOS),and psychosocial adjustment(SENA subscales of somatization and eating problems).Using a fuzzy-set Qualitative Comparative Analysis(fsQCA)approach,distinct configurations of risk and protective factors associated with elevated levels of somatization and eating problems were identified.Results:Relational trauma and attachment anxiety showed moderate associations with both somatization and eating problems(r=0.52–0.57,p<0.01),whereas stress management was negatively associated with both outcomes(r=−0.37 to−0.47,p<0.05).FsQCA revealed multiple configurations of risk and protective factors explaining 81–90%of cases,with solution consistencies ranging from 0.83 to 0.87.Results suggest that relational trauma and attachment anxiety are key risk conditions,whereas resilience,emotional regulation,and perceived social support function as protective factors.Conclusions:Findings highlight the importance of considering multifactorial patterns of vulnerability and protection rather than single predictors and underscore the need for tailored interventions that strengthen resilience and emotional skills while addressing the impact of early relational trauma.
基金supported by the STI 2030 Major Projects(No.2022ZD0208804)the National Natural Science Foundation of China(No.62473017)。
文摘Robust cooperative unmanned aerial vehicle(UAV)formation in complex 3D environments is hampered by reward sparsity and inefficient collaboration.To address this,we propose context-aware relational agent learning(CORAL),a novel multi-agent deep reinforcement learning framework.CORAL synergistically integrates two modules:(1)a novelty-based intrinsic reward module to drive efficient exploration and(2)an explicit relational learning module that allows agents to predict peer intentions and enhance coordination.Built on a multi-agent Actor-Critic architecture,CORAL enables agents to balance self-interest with group objectives.Comprehensive evaluations in a high-fidelity simulation show that our method significantly outperforms state-of-theart baselines like multi-agent deep deterministic policy gradient(MADDPG)and monotonic value function factorisation for deep multi-agent reinforcement learning(QMIX)in path planning efficiency,collision avoidance,and scalability.
文摘British Prime Minister Keir Starmer’s visit to China underscores economic cooperation and strategic stability amid global uncertainties.U.K.Prime Minister Keir Starmer’s visit to China in January marks a significant shift of Britain toward a more pragmatic and stability-oriented approach in Sino-British relations.After years of political tensions and limited high-level engagement,this trip underscores London’s intent to rebuild ties based on mutual economic and strategic interests.
基金funded by Vietnam National University Ho Chi Minh City(VNU-HCM)under grant number DS.C2025-28-06.
文摘Vaginal delivery is a fascinating physiological process,but also a high-risk process.Up to 85%–90%of vaginal deliveries lead to perineal trauma,with nearly 11%of severe perineal tearing.It is a common occurrence,especially for first-time mothers.Computational childbirth plays an essential role in the prediction and prevention of these traumas,but fast personalization of the pelvis and floor muscles is challenging due to their anatomical complexity.This study introduces a novel shape-prediction-based personalization of the pelvis and floor muscles for perineal tearing management and childbirth simulation.300 subjects were selected from public Computed Tomography(CT)databases.The pelvic bone nmjmeshes were generated using a coarse-to-fine non-rigid mesh alignment procedure.The floor muscle meshes were personalized using the bone mesh deformation information.A feature-to-pelvic structure reconstruction pipeline was proposed,incorporating various strategies.Ten-fold cross-validation helped determine the optimal reconstruction strategy,regression method,and feature sizes.The mesh-to-mesh distance metric was employed for evaluating.The statistical shape relation-based strategy,coupled with multi-output ridge regression,was the optimal approach for pelvic structure reconstruction.With a feature set ranging from 3 to 38,the mean errors were 2.672 to 1.613 mm,and 3.237 to 1.415 mm in muscle attachment regions.The best-and worst-case predictions had errors of 1.227±0.959 mm and 2.900±2.309 mm,respectively.This study provides a novel approach to achieving fast personalized childbirth modeling and simulation for perineal tearing management.
文摘Background: This study focuses on the fabrication and optimization of Ti6Al4V alloy latticestructures produced by the Selective Laser Melting (SLM) process. Such structures areincreasingly used in biomedical implants due to their potential to match the mechanicalproperties of human bone. Key features influencing their performance include porosity ratio,surface roughness, elastic modulus, and yield strength. Achieving a balance between theseparameters is essential for ensuring both mechanical integrity and biological compatibility.Methods: The Taguchi method integrated with Grey Relational Analysis (GRA) wasemployed to optimize the SLM process parameters—laser power (160-240 J), scanningspeed (1000-1500 mm/min), and hatch spacing (0.06-0.12 mm). The optimization aimed toproduce lattice structures with properties closely resembling human bone. Experimentaltrials were conducted to evaluate the effects of these parameters on porosity, surfaceroughness, elastic modulus, and yield strength, followed by statistical and relational analysisto determine the optimal configuration. Results: The results revealed that higher scanningspeed, wider hatch spacing, and lower laser power increased the porosity ratio compared toCAD models. A strong inverse relationship was observed between porosity and both yieldstrength and elastic modulus. Increasing laser power substantially reduced surfaceroughness. Through Taguchi-GRA optimization, the optimal parameter combination wasdetermined as laser power of 240 J, scanning speed of 1250 mm/min, and hatch spacing of0.06 mm. Under these conditions, the obtained values were: modulus of elasticity (0°) = 20GPa, modulus of elasticity (90°) = 18.874 GPa, yield strength (0°) = 265 MPa, yieldstrength (90°) = 260 MPa, porosity = 48.565%, and surface roughness = 6.223 μm.Conclusion: The optimized SLM parameters successfully produced Ti6Al4V latticestructures with mechanical and morphological characteristics compatible with human bone.The study highlights the critical balance between process parameters and structuralfeatures, providing a systematic approach for tailoring lattice structures for biomedicalapplications through Taguchi and GRA-based optimization.
文摘Given the scarcity of Satellite Frequency and Orbit(SFO)resources,it holds paramount importance to establish a comprehensive knowledge graph of SFO field(SFO-KG)and employ knowledge reasoning technology to automatically mine available SFO resources.An essential aspect of constructing SFO-KG is the extraction of Chinese entity relations.Unfortunately,there is currently no publicly available Chinese SFO entity Relation Extraction(RE)dataset.Moreover,publicly available SFO text data contain numerous NA(representing for“No Answer”)relation category sentences that resemble other relation sentences and pose challenges in accurate classification,resulting in low recall and precision for the NA relation category in entity RE.Consequently,this issue adversely affects both the accuracy of constructing the knowledge graph and the efficiency of RE processes.To address these challenges,this paper proposes a method for extracting Chinese SFO text entity relations based on dynamic integrated learning.This method includes the construction of a manually annotated Chinese SFO entity RE dataset and a classifier combining features of SFO resource data.The proposed approach combines integrated learning and pre-training models,specifically utilizing Bidirectional Encoder Representation from Transformers(BERT).In addition,it incorporates one-class classification,attention mechanisms,and dynamic feedback mechanisms to improve the performance of the RE model.Experimental results show that the proposed method outperforms the traditional methods in terms of F1 value when extracting entity relations from both balanced and long-tailed datasets.
基金Heilongjiang Provincial Natural Science Foundation of China (LH2021F009)。
文摘Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be solved. A comprehensive evaluation method is proposed, which combines grey relational analysis (GRA) and cloud model, to evaluate the anti-jamming performances of Link-16. Firstly, on the basis of establishing the anti-jamming performance evaluation indicator system of Link-16, the linear combination of analytic hierarchy process(AHP) and entropy weight method (EWM) are used to calculate the combined weight. Secondly, the qualitative and quantitative concept transformation model, i.e., the cloud model, is introduced to evaluate the anti-jamming abilities of Link-16 under each jamming scheme. In addition, GRA calculates the correlation degree between evaluation indicators and the anti-jamming performance of Link-16, and assesses the best anti-jamming technology. Finally, simulation results prove that the proposed evaluation model can achieve the objective of feasible and practical evaluation, which opens up a novel way for the research of anti-jamming performance evaluations of Link-16.
基金funded by the Research Project:THTETN.05/24-25,VietnamAcademy of Science and Technology.
文摘Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex,high-dimensional data that single-view methods cannot capture.Traditional fuzzy clustering techniques,such as Fuzzy C-Means(FCM),face significant challenges in handling uncertainty and the dependencies between different views.To overcome these limitations,we introduce a new multi-view fuzzy clustering approach that integrates picture fuzzy sets with a dual-anchor graph method for multi-view data,aiming to enhance clustering accuracy and robustness,termed Multi-view Picture Fuzzy Clustering(MPFC).In particular,the picture fuzzy set theory extends the capability to represent uncertainty by modeling three membership levels:membership degrees,neutral degrees,and refusal degrees.This allows for a more flexible representation of uncertain and conflicting data than traditional fuzzy models.Meanwhile,dual-anchor graphs exploit the similarity relationships between data points and integrate information across views.This combination improves stability,scalability,and robustness when handling noisy and heterogeneous data.Experimental results on several benchmark datasets demonstrate significant improvements in clustering accuracy and efficiency,outperforming traditional methods.Specifically,the MPFC algorithm demonstrates outstanding clustering performance on a variety of datasets,attaining a Purity(PUR)score of 0.6440 and an Accuracy(ACC)score of 0.6213 for the 3 Sources dataset,underscoring its robustness and efficiency.The proposed approach significantly contributes to fields such as pattern recognition,multi-view relational data analysis,and large-scale clustering problems.Future work will focus on extending the method for semi-supervised multi-view clustering,aiming to enhance adaptability,scalability,and performance in real-world applications.
文摘During Donald Trump’s first term,the“Trump Shock”brought world politics into an era of uncertainties and pulled the transatlantic alliance down to its lowest point in history.The Trump 2.0 tsunami brewed by the 2024 presidential election of the United States has plunged the U.S.-Europe relations into more gloomy waters,ushering in a more complex and turbulent period of adjustment.
基金supported by the National Natural Science Foundation of China(623B2098,62021001,62371434)the Postdoctoral Fellowship Program of CPSF(GZC20252293)+1 种基金the China Postdoctoral Science Foundation–Anhui Joint Support Program(2024T017AH)Anhui Postdoctoral Scientific Research Program Foundation(2025A1015).
文摘Collecting amounts of distorted/clean image pairs in the real world is non-trivial,which severely limits the practical application of these supervised learning-based methods to real-world image super-resolution(RealSR).Previous works usually address this problem by leveraging unsupervised learning-based technologies to alleviate the dependency on paired training samples.However,these methods typically suffer from unsatisfactory texture synthesis due to the lack of supervision of clean images.To overcome this problem,we are the first to take a close look at the under-explored direction for RealSR,i.e.,few-shot real-world image super-resolution,which aims to tackle the challenging RealSR problem with few-shot distorted/clean image pairs.Under this brand-new scenario,we propose distortion relation guided transfer learning(DRTL)for the few-shot RealSR by transferring the rich restoration knowledge from auxiliary distortions(i.e.,synthetic distortions)to the target RealSR under the guidance of the distortion relation.Concretely,DRTL builds a knowledge graph to capture the distortion relation between auxiliary distortions and target distortion(i.e.,real distortions in RealSR).Based on the distortion relation,DRTL adopts a gradient reweighting strategy to guide the knowledge transfer process between auxiliary distortions and target distortions.In this way,DRTL is able to quickly learn the most relevant knowledge from the synthetic distortions for the target distortion.We instantiate DRTL with two commonly-used transfer learning paradigms,including pretraining and meta-learning pipelines,to realize a distortion relation-aware few-shot RealSR.Extensive experiments on multiple benchmarks and thorough ablation studies demonstrate the effectiveness of our DRTL.
