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 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
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
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
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
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
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
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
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
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
The year 2025 marks the historic juncture of the 75th anniversary of the establishment of diplomatic relations between China and India.Looking back,though China-India ties have experienced twists and frictions,dialogu...The year 2025 marks the historic juncture of the 75th anniversary of the establishment of diplomatic relations between China and India.Looking back,though China-India ties have experienced twists and frictions,dialogue and cooperation have been the dominant theme,guiding the bilateral relations forward along a healthy and stable track.展开更多
I am delighted to join my Thai and Chinese friends in celebrating the 50th anniversary of the establishment of diplomatic relations between our two great nations.It is the“Golden Jubilee”of Thailand-China friendship...I am delighted to join my Thai and Chinese friends in celebrating the 50th anniversary of the establishment of diplomatic relations between our two great nations.It is the“Golden Jubilee”of Thailand-China friendship.Half a century ago when Thailand’s then Prime Minister M.R.Kukrit Pramoj and China’s Premier Zhou Enlai signed a Joint Communique on the Establishment of Diplomatic Relations on July 1,1975,the foundation for a profound and mutually beneficial partnership was laid,fostering enduring friendship,cooperation,and understanding between our two nations.This bond has stood the test of time amidst the ever-changing international landscape and been further enhanced by both countries’commitment to advancing the Comprehensive Strategic Cooperative Partnership and building a Thailand-China community with a shared future for enhanced stability,prosperity,and sustainability through a forwardlooking and people-centered vision.展开更多
In recent years,with the rapid development of deep learning technology,relational triplet extraction techniques have also achieved groundbreaking progress.Traditional pipeline models have certain limitations due to er...In recent years,with the rapid development of deep learning technology,relational triplet extraction techniques have also achieved groundbreaking progress.Traditional pipeline models have certain limitations due to error propagation.To overcome the limitations of traditional pipeline models,recent research has focused on jointly modeling the two key subtasks-named entity recognition and relation extraction-within a unified framework.To support future research,this paper provides a comprehensive review of recently published studies in the field of relational triplet extraction.The review examines commonly used public datasets for relational triplet extraction techniques and systematically reviews current mainstream joint extraction methods,including joint decoding methods and parameter sharing methods,with joint decoding methods further divided into table filling,tagging,and sequence-to-sequence approaches.In addition,this paper also conducts small-scale replication experiments on models that have performed well in recent years for each method to verify the reproducibility of the code and to compare the performance of different models under uniform conditions.Each method has its own advantages in terms of model design,task handling,and application scenarios,but also faces challenges such as processing complex sentence structures,cross-sentence relation extraction,and adaptability in low-resource environments.Finally,this paper systematically summarizes each method and discusses the future development prospects of joint extraction of relational triples.展开更多
The year 2025 marks the 50th anniversary of diplomatic relations between China and the Philippines.Over the past half century,despite ups and downs,China-Philippines relations have maintained a steady momentum of deve...The year 2025 marks the 50th anniversary of diplomatic relations between China and the Philippines.Over the past half century,despite ups and downs,China-Philippines relations have maintained a steady momentum of development with continuous progress in political,economic,and cultural exchanges.Since the second half of 2023,the Philippines’freguent provocations in the South China Sea have negatively impacted bilateral relations.展开更多
Metastable β titanium alloy is an ideal material for lightweight and high strength due to its excellent comprehensive mechanical properties.However,overcoming the trade-off relation between strength and ductility rem...Metastable β titanium alloy is an ideal material for lightweight and high strength due to its excellent comprehensive mechanical properties.However,overcoming the trade-off relation between strength and ductility remains a significant challenge.In this study,the mechanical properties of Ti-38644 alloy were optimized by introducing a heterogeneous bi-grain bi-lamella(BG-BL)structure through a well-designed combination of rolling,drawing and heat treatment.The results demonstrate that the present BG-BL Ti-38644 alloy shows a tensile strength of~1500 MPa and a total elongation of 18%.In particular,the high strength-elongation combination of the BG-BL Ti-38644 alloy breakthroughs the trade-off relation in all the titanium alloys available.The recrystallized grains with low dislocation enhance the ductility of the Ti-38644 alloy,while the highly distorted elongated grains mainly contribute to the high strength.The present study provides a new principle for designing Ti alloys with superior strength and ductility.展开更多
If there were any doubts about the Trump administration’s inherent obsession with decoupling,polarization and jolting of global trade,they can be laid to rest.A series of statements and measures have been made by the...If there were any doubts about the Trump administration’s inherent obsession with decoupling,polarization and jolting of global trade,they can be laid to rest.A series of statements and measures have been made by the U.S.government on economic relations with China including administrative decision to hit Chinese goods with additional tariffs despite China.展开更多
Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to vari...Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.展开更多
Understanding the relationship between sediment and discharge is crucial for effective river management and water-sediment modeling,especially in the Brahmaputra River,one of the large transboundary rivers with high s...Understanding the relationship between sediment and discharge is crucial for effective river management and water-sediment modeling,especially in the Brahmaputra River,one of the large transboundary rivers with high sediment and discharge variability in South Asia.Current knowledge of sediment-water relations is constrained by limited data,hindering effective transboundary river management.Using multivariate linear regression,climate elasticity coefficient,and traditional sediment rating curve,this study is designed to compare the sediment-water relations of the upstream(Nuxia)and the downstream(Bahadurabad).The results reveal significant variability between the two stations.In the upstream Nuxia,the simulation strongly correlates with observed suspended sediment load(SSL)and discharge(Q)(Pearson's r of 0.62 and 0.68,respectively).Conversely,at downstream Bahadurabad,weaker correlations(r=0.31 for sediment and r=0.51 for discharge simulation)indicate a reduced relation.This contrast reflects the non-linear nature of sediment-discharge coupling along the river continuum,shaped by both climatic and anthropogenic influences.Elasticity(ε)analysis highlights the dominant role of precipitation in shaping sediment-water dynamics(εP-SSL=2.53,εP-Q=1.01)at Nuxia,while Bahadurabad(εP-SSL=0.41,εP-Q=0.82)reflects a reduced sensitivity,possibly due to sediment retention along the floodplain.Air temperature elasticity(εT-SSL,-0.15&-3.06 at Nuxia and Bahadurabad,respectively)reveals contrasting impacts,strongly negatively influencing sediment transport at Bahadurabad.These findings highlight the significance of spatial variability and climatic influences on sediment dynamics,underscoring the necessity for site-specific management strategies.The sediment rating curve(SRC)analysis reveals a strong relationship between sediment and discharge(R^(2)=0.88)at Nuxia and a relatively weaker relationship(R^(2)=0.14)at Bahadurabad,which demonstrates a lower sedimentdischarge coupling that could be affected by downstream factors such as sediment deposition,channel morphology,and anthropogenic activities.This study offers valuable insights into sediment-water dynamics,highlighting the importance of understanding nonlinear relationships in the Brahmaputra River.展开更多
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 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.
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.
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.
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.
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.
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.
文摘The year 2025 marks the historic juncture of the 75th anniversary of the establishment of diplomatic relations between China and India.Looking back,though China-India ties have experienced twists and frictions,dialogue and cooperation have been the dominant theme,guiding the bilateral relations forward along a healthy and stable track.
文摘I am delighted to join my Thai and Chinese friends in celebrating the 50th anniversary of the establishment of diplomatic relations between our two great nations.It is the“Golden Jubilee”of Thailand-China friendship.Half a century ago when Thailand’s then Prime Minister M.R.Kukrit Pramoj and China’s Premier Zhou Enlai signed a Joint Communique on the Establishment of Diplomatic Relations on July 1,1975,the foundation for a profound and mutually beneficial partnership was laid,fostering enduring friendship,cooperation,and understanding between our two nations.This bond has stood the test of time amidst the ever-changing international landscape and been further enhanced by both countries’commitment to advancing the Comprehensive Strategic Cooperative Partnership and building a Thailand-China community with a shared future for enhanced stability,prosperity,and sustainability through a forwardlooking and people-centered vision.
基金funding from Key Areas Science and Technology Research Plan of Xinjiang Production And Construction Corps Financial Science and Technology Plan Project under Grant Agreement No.2023AB048 for the project:Research and Application Demonstration of Data-driven Elderly Care System.
文摘In recent years,with the rapid development of deep learning technology,relational triplet extraction techniques have also achieved groundbreaking progress.Traditional pipeline models have certain limitations due to error propagation.To overcome the limitations of traditional pipeline models,recent research has focused on jointly modeling the two key subtasks-named entity recognition and relation extraction-within a unified framework.To support future research,this paper provides a comprehensive review of recently published studies in the field of relational triplet extraction.The review examines commonly used public datasets for relational triplet extraction techniques and systematically reviews current mainstream joint extraction methods,including joint decoding methods and parameter sharing methods,with joint decoding methods further divided into table filling,tagging,and sequence-to-sequence approaches.In addition,this paper also conducts small-scale replication experiments on models that have performed well in recent years for each method to verify the reproducibility of the code and to compare the performance of different models under uniform conditions.Each method has its own advantages in terms of model design,task handling,and application scenarios,but also faces challenges such as processing complex sentence structures,cross-sentence relation extraction,and adaptability in low-resource environments.Finally,this paper systematically summarizes each method and discusses the future development prospects of joint extraction of relational triples.
文摘The year 2025 marks the 50th anniversary of diplomatic relations between China and the Philippines.Over the past half century,despite ups and downs,China-Philippines relations have maintained a steady momentum of development with continuous progress in political,economic,and cultural exchanges.Since the second half of 2023,the Philippines’freguent provocations in the South China Sea have negatively impacted bilateral relations.
基金financially supported by the National Natural Science Foundation of China(Nos.52321001,52322105,52130002,U2241245,52261135634 and 52371084)the Youth Innovation Promotion Association(CAS,No.2021192)the IMR Innovation Fund(No.2023-ZD01).
文摘Metastable β titanium alloy is an ideal material for lightweight and high strength due to its excellent comprehensive mechanical properties.However,overcoming the trade-off relation between strength and ductility remains a significant challenge.In this study,the mechanical properties of Ti-38644 alloy were optimized by introducing a heterogeneous bi-grain bi-lamella(BG-BL)structure through a well-designed combination of rolling,drawing and heat treatment.The results demonstrate that the present BG-BL Ti-38644 alloy shows a tensile strength of~1500 MPa and a total elongation of 18%.In particular,the high strength-elongation combination of the BG-BL Ti-38644 alloy breakthroughs the trade-off relation in all the titanium alloys available.The recrystallized grains with low dislocation enhance the ductility of the Ti-38644 alloy,while the highly distorted elongated grains mainly contribute to the high strength.The present study provides a new principle for designing Ti alloys with superior strength and ductility.
文摘If there were any doubts about the Trump administration’s inherent obsession with decoupling,polarization and jolting of global trade,they can be laid to rest.A series of statements and measures have been made by the U.S.government on economic relations with China including administrative decision to hit Chinese goods with additional tariffs despite China.
文摘Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.
基金jointly supported by the Second Tibetan Plateau Scientific Expedition and Research Program(Grant No.2019QZKK0902)National Natural Science Foundation of China(NSFC)project(Grant No.42305178)+1 种基金the Key R&D Program of Tibet Autonomous Region(Grant No.XZ202301ZY0039G)the Science and Technology Research Program of Institute of Mountain Hazards and Environment,Chinese Academy of Sciences(Grant No.IMHEZDRW-01)。
文摘Understanding the relationship between sediment and discharge is crucial for effective river management and water-sediment modeling,especially in the Brahmaputra River,one of the large transboundary rivers with high sediment and discharge variability in South Asia.Current knowledge of sediment-water relations is constrained by limited data,hindering effective transboundary river management.Using multivariate linear regression,climate elasticity coefficient,and traditional sediment rating curve,this study is designed to compare the sediment-water relations of the upstream(Nuxia)and the downstream(Bahadurabad).The results reveal significant variability between the two stations.In the upstream Nuxia,the simulation strongly correlates with observed suspended sediment load(SSL)and discharge(Q)(Pearson's r of 0.62 and 0.68,respectively).Conversely,at downstream Bahadurabad,weaker correlations(r=0.31 for sediment and r=0.51 for discharge simulation)indicate a reduced relation.This contrast reflects the non-linear nature of sediment-discharge coupling along the river continuum,shaped by both climatic and anthropogenic influences.Elasticity(ε)analysis highlights the dominant role of precipitation in shaping sediment-water dynamics(εP-SSL=2.53,εP-Q=1.01)at Nuxia,while Bahadurabad(εP-SSL=0.41,εP-Q=0.82)reflects a reduced sensitivity,possibly due to sediment retention along the floodplain.Air temperature elasticity(εT-SSL,-0.15&-3.06 at Nuxia and Bahadurabad,respectively)reveals contrasting impacts,strongly negatively influencing sediment transport at Bahadurabad.These findings highlight the significance of spatial variability and climatic influences on sediment dynamics,underscoring the necessity for site-specific management strategies.The sediment rating curve(SRC)analysis reveals a strong relationship between sediment and discharge(R^(2)=0.88)at Nuxia and a relatively weaker relationship(R^(2)=0.14)at Bahadurabad,which demonstrates a lower sedimentdischarge coupling that could be affected by downstream factors such as sediment deposition,channel morphology,and anthropogenic activities.This study offers valuable insights into sediment-water dynamics,highlighting the importance of understanding nonlinear relationships in the Brahmaputra River.
