For decades,Xu has been committed to fulfilling the duty and mission of a scientist and educator—diving into the laws of nature,caring deeply for the nation,and earnestly cultivating younger generations.
To fully utilize the resources provided by optical fiber networks,a cross-band quantum light source generating photon pairs,where one photon in a pair is at C band and the other is at O band,is proposed in this work.T...To fully utilize the resources provided by optical fiber networks,a cross-band quantum light source generating photon pairs,where one photon in a pair is at C band and the other is at O band,is proposed in this work.This source is based on spontaneous four-wave mixing(SFWM)in a piece of shallow-ridge silicon waveguide.Theoretical analysis shows that the waveguide dispersion could be tailored by adjusting the ridge width,enabling broadband photon pair generation by SFWM across C band and O band.The spontaneous Raman scattering(SpRS)in silicon waveguides is also investigated experimentally.It shows that there are two regions in the spectrum of generated photons from SpRS,which could be used to achieve cross-band photon pair generation.A chip of shallow-ridge silicon waveguide samples with different ridge widths has been fabricated,through which cross-band photon pair generation is demonstrated experimentally.The experimental results show that the source can be achieved using dispersion-optimized shallow-ridge silicon waveguides.This cross-band quantum light source provides a way to develop new fiber-based quantum communication functions utilizing both C band and O band and extends applications of quantum networks.展开更多
The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location re...The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location reidentification and correlation attacks.To address these challenges,privacy-preserving trajectory generation methods are critical for applications relying on sensitive location data.This paper introduces DPIL-Traj,an advanced framework designed to generate synthetic trajectories while achieving a superior balance between data utility and privacy preservation.Firstly,the framework incorporates Differential Privacy Clustering,which anonymizes trajectory data by applying differential privacy techniques that add noise,ensuring the protection of sensitive user information.Secondly,Imitation Learning is used to replicate decision-making behaviors observed in real-world trajectories.By learning from expert trajectories,this component generates synthetic data that closely mimics real-world decision-making processes while optimizing the quality of the generated trajectories.Finally,Markov-based Trajectory Generation is employed to capture and maintain the inherent temporal dynamics of movement patterns.Extensive experiments conducted on the GeoLife trajectory dataset show that DPIL-Traj improves utility performance by an average of 19.85%,and in terms of privacy performance by an average of 12.51%,compared to state-of-the-art approaches.Ablation studies further reveal that DP clustering effectively safeguards privacy,imitation learning enhances utility under noise,and the Markov module strengthens temporal coherence.展开更多
In 2021,the relatives of 16 international friends of China jointly sent a letter to Chinese President Xi Jinping,congratulating the Communist Party of China(CPC)on its 100th anniversary.These are the sons and daughter...In 2021,the relatives of 16 international friends of China jointly sent a letter to Chinese President Xi Jinping,congratulating the Communist Party of China(CPC)on its 100th anniversary.These are the sons and daughters and family members of those who helped China in its times of need.Eric Foster,nephew of renowned U.S.journalist Helen Foster-Snow,was one of them.展开更多
The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-lear...The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-learning(DL)-driven CV in four key areas of materials science:microstructure-based performance prediction,microstructure information generation,microstructure defect detection,and crystal structure-based property prediction.The CV has significantly reduced the cost of traditional experimental methods used in material performance prediction.Moreover,recent progress made in generating microstructure images and detecting microstructural defects using CV has led to increased efficiency and reliability in material performance assessments.The DL-driven CV models can accelerate the design of new materials with optimized performance by integrating predictions based on both crystal and microstructural data,thereby allowing for the discovery and innovation of next-generation materials.Finally,the review provides insights into the rapid interdisciplinary developments in the field of materials science and future prospects.展开更多
Al/NH_(4)CoF_(3)-Φ(Φ=0.5,1.0,1.5,2.0,and 3.0)binary composites and Al-NH_(4)CoF_(3)@P(VDF-HFP)ternary composites are fabricated via ultrasonication-assisted blending and electrostatic spraying.The effect of equivale...Al/NH_(4)CoF_(3)-Φ(Φ=0.5,1.0,1.5,2.0,and 3.0)binary composites and Al-NH_(4)CoF_(3)@P(VDF-HFP)ternary composites are fabricated via ultrasonication-assisted blending and electrostatic spraying.The effect of equivalence ratio(Φ)on the reaction properties is systematically investigated in the binary Al/NH_(4)CoF_(3)system.For ternary systems,electrostatic spraying allows both components to be efficiently encapsulated by P(VDF-HFP)and to achieve structural stabilization and enhanced reactivity through synergistic interfacial interactions.Morphological analysis using SEM/TEM revealed that P(VDF-HFP)formed a protective layer on Al and NH_(4)CoF_(3)particles,improving dispersion,hydrophobicity(water contact angle increased by 80.5%compared to physically mixed composites),and corrosion resistance.Thermal decomposition of NH_(4)CoF_(3)occurred at 265℃,releasing NH_(3)and HF,which triggered exothermic reactions with Al.The ternary composites exhibited a narrowed main reaction temperature range and concentrated heat release,attributed to improved interfacial contact and polymer decomposition.Combustion tests demonstrated that Al-NH_(4)CoF_(3)@P(VDF-HFP)achieved self-sustaining combustion.In addition,a simple validation was done by replacing the Al component in the aluminium-containing propellant,demonstrating its potential application in the propellant field.This work establishes a novel strategy for designing stable,high-energy composites with potential applications in advanced propulsion systems.展开更多
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
Wing design is a critical factor in the aerodynamic performance of flapping-wing(FW)robots.Inspired by the natural wing structures of insects,bats,and birds,we explored how bio-mimetic wing vein morphologies,combined ...Wing design is a critical factor in the aerodynamic performance of flapping-wing(FW)robots.Inspired by the natural wing structures of insects,bats,and birds,we explored how bio-mimetic wing vein morphologies,combined with a bio-inspired double wing clap-and-fling mechanism,affect thrust generation.This study focused on increasing vertical force and payload capacity.Through systematic experimentation with various vein configurations and structural designs,we developed innovative wings optimized for thrust production.Comprehensive tests were conducted to measure aerodynamic forces,power consumption,and wing kinematics across a range of flapping frequencies.Additionally,wings with different aspect ratios,a key factor in wing design,were fabricated and extensively evaluated.The study also examined the role of bio-inspired vein layouts on wing flexibility,a critical component in improving flight efficiency.Our findings demonstrate that the newly developed wing design led to a 20%increase in thrust,achieving up to 30 g-force(gf).This research sheds light on the clap-and-fling effect and establishes a promising framework for bio-inspired wing design,offering significant improvements in both performance and payload capacity for FW robots.展开更多
Laser-induced aerosols,predominantly submicron in size,pose significant environmental and health risks during the decommissioning of nuclear reactors.This study experimentally investigated the removal of laser-generat...Laser-induced aerosols,predominantly submicron in size,pose significant environmental and health risks during the decommissioning of nuclear reactors.This study experimentally investigated the removal of laser-generated aerosol particles using a water spray system integrated with an innovative system for pre-injecting electrically charged mist in our facility.To simulate aerosol generation in reactor decommissioning,a high-power laser was used to irradiate various materials(including stainless steel,carbon steel,and concrete),generating aerosol particles that were agglomerated with injected water mist and subsequently scavenged by water spray.Experimental results demonstrate enhanced aerosol removal via aerosol-mist agglomeration,with charged mist significantly improving particle capture by increasing wettability and size.The average improvements for the stainless steel,carbon steel,and concrete were 40%,44%,and 21%,respectively.The results of experiments using charged mist with different polarities(both positive and negative)and different surface coatings reveal that the dominant polarity of aerosols varies with the irradiated materials,influenced by their crystal structure and electron emission properties.Notably,surface coatings such as ZrO_(2)and CeO_(2)were found to possibly alter aerosol charging characteristics,thereby affecting aerosol removal efficiency with charged mist configurations.The innovative aerosol-mist agglomeration approach shows promise in mitigating radiation exposure,ensuring environmental safety,and reducing contaminated water during reactor dismantling.This study contributes critical knowledge for the development of advanced aerosol management strategies for nuclear reactor decommissioning.The understanding obtained in this work is also expected to be useful for various environmental and chemical engineering applications such as gas decontamination,air purification,and pollution control.展开更多
Due to the digital transformation tendency among cultural institutions and the substantial influence of the social media platform,the demands of visual communication keep increasing for promoting traditional cultural ...Due to the digital transformation tendency among cultural institutions and the substantial influence of the social media platform,the demands of visual communication keep increasing for promoting traditional cultural artifacts online.As an effective medium,posters serve to attract public attention and facilitate broader engagement with cultural artifacts.However,existing poster generation methods mainly rely on fixed templates and manual design,which limits their scalability and adaptability to the diverse visual and semantic features of the artifacts.Therefore,we propose CAPGen,an automated aesthetic Cultural Artifacts Poster Generation framework built on a Multimodal Large Language Model(MLLM)with integrated iterative optimization.During our research,we collaborated with designers to define principles of graphic design for cultural artifact posters,to guide the MLLM in generating layout parameters.Later,we generated these parameters into posters.Finally,we refined the posters using an MLLM integrated with a multi-round iterative optimization mechanism.Qualitative results show that CAPGen consistently outperforms baseline methods in both visual quality and aesthetic performance.Furthermore,ablation studies indicate that the prompt,iterative optimization mechanism,and design principles significantly enhance the effectiveness of poster generation.展开更多
Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frame...Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.展开更多
Standards are the common language that consolidates global consensus and builds the most solid foundation for international partnerships.They are the cornerstone for global sustainable and high-quality development.You...Standards are the common language that consolidates global consensus and builds the most solid foundation for international partnerships.They are the cornerstone for global sustainable and high-quality development.Young students,with their active and vibrant minds,represent the future and hope of standardization.展开更多
Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using d...Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using deep learning algorithms further enhances performance;nevertheless,it is challenging due to the nature of small-scale and imbalanced PD datasets.This paper proposed a convolutional neural network-based deep support vector machine(CNN-DSVM)to automate the feature extraction process using CNN and extend the conventional SVM to a DSVM for better classification performance in small-scale PD datasets.A customized kernel function reduces the impact of biased classification towards the majority class(healthy candidates in our consideration).An improved generative adversarial network(IGAN)was designed to generate additional training data to enhance the model’s performance.For performance evaluation,the proposed algorithm achieves a sensitivity of 97.6%and a specificity of 97.3%.The performance comparison is evaluated from five perspectives,including comparisons with different data generation algorithms,feature extraction techniques,kernel functions,and existing works.Results reveal the effectiveness of the IGAN algorithm,which improves the sensitivity and specificity by 4.05%–4.72%and 4.96%–5.86%,respectively;and the effectiveness of the CNN-DSVM algorithm,which improves the sensitivity by 1.24%–57.4%and specificity by 1.04%–163%and reduces biased detection towards the majority class.The ablation experiments confirm the effectiveness of individual components.Two future research directions have also been suggested.展开更多
The scratching mechanism of polycrystallineγ-TiAl alloy was investigated at the atomic scale using the molecular dynamics method,with a focus on the influence of different grain sizes.The analysis encompassed tribolo...The scratching mechanism of polycrystallineγ-TiAl alloy was investigated at the atomic scale using the molecular dynamics method,with a focus on the influence of different grain sizes.The analysis encompassed tribological characteristics,scratch morphology,subsurface defect distribution,temperature variations,and stress states during the scratching process.The findings indicate that the scratch force,number of recovered atoms,and pile-up height exhibit abrupt changes when the critical size is 9.41 nm due to the influence of the inverse Hall-Petch effect.Variations in the number of grain boundaries and randomness of grain orientation result in different accumulation patterns on the scratch surface.Notably,single crystal materials and those with 3.73 nm in grain size display more regular surface morphology.Furthermore,smaller grain size leads to an increase in average coefficient of friction,removed atoms number,and wear rate.While it also causes higher temperatures with a larger range of distributions.Due to the barrier effect of grain boundaries,smaller grains exhibit reduced microscopic defects.Additionally,average von Mises stress and hydrostatic compressive stress at the indenter tip decrease as grain size decreases owing to grain boundary obstruction.展开更多
Since the release of ChatGPT in late 2022,Generative Artificial Intelligence(GAI)has gained widespread attention because of its impressive capabilities in language comprehension,reasoning,and generation.GAI has been s...Since the release of ChatGPT in late 2022,Generative Artificial Intelligence(GAI)has gained widespread attention because of its impressive capabilities in language comprehension,reasoning,and generation.GAI has been successfully applied across various aspects(e.g.,creative writing,code generation,translation,and information retrieval).In cartography and GIS,researchers have employed GAI to handle some specific tasks,such as map generation,geographic question answering,and spatiotemporal data analysis,yielding a series of remarkable results.Although GAI-based techniques are developing rapidly,literature reviews of their applications in cartography and GIS remain relatively limited.This paper reviews recent GAI-related research in cartography and GIS,focusing on three aspects:①map generation,②geographical analysis,and③evaluation of GAI’s spatial cognition abilities.In addition,the paper analyzes current challenges and proposes future research directions.展开更多
Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationship...Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra,PSD,and random signal power spectra.The relationship was derived,validated through experiments and simulations,and subsequently applied to multi-objective optimization.Various optimization algorithms were compared to achieve optimal system power quality.The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model.An increase in the order of the AR model resulted in a 36%improvement in the number of optimal solutions.Regarding optimal solution distribution,NSGA-II demonstrated superior diversity,while MOEA/D exhibited better convergence.However,practical applications showed that while MOEA/D had higher convergence,NSGA-II produced superior optimal solutions,achieving the best power quality indices(THDi at 4.62%,d%at 3.51%,and cosφat 96%).These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.展开更多
Rice(Oryza sativa L.)plays a pivotal role in global food security,yet its breeding is constrained by its long generation time and seasonality.To enhance rice breeding efficiency and meet future food demands,we have de...Rice(Oryza sativa L.)plays a pivotal role in global food security,yet its breeding is constrained by its long generation time and seasonality.To enhance rice breeding efficiency and meet future food demands,we have developed a vertical hydroponic breeding system integrated with light-emitting diodes(LEDs)light-ing in a closed plant factory(PF),which significantly accelerates rice growth and generation advance-ment.The results show that indica rice can be harvested as early as after 63 days of cultivation,a 50%reduction compared with field cultivation,enabling the annual harvesting of 5-6 generations within the PF.A hyperspectral imaging(HSI)system and attenuated total reflectance infrared(ATR-IR)spec-troscopy were further employed to characterize the chemical composition of the PF-and field-cultivated rice.Metabolomics analysis with ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)and gas chromatography-mass spectrometry(GC-MS)revealed that,com-pared with the field-cultivated rice,the PF-cultivated rice exhibited an up-regulation of total phenolic acids along with 68 non-volatile and 19 volatile metabolites,such as isovitexin,succinic acid,and methylillicinone F.Overall,this study reveals the unique metabolic profile of PF-cultivated rice and high-lights the potential of PFs to accelerate the breeding of crops such as rice,offering an innovative agricul-tural strategy to support food security in the face of global population growth and climate change.展开更多
The future large-scale application of sodium-ion batteries(SIBs)is inseparable from their excellent electrochemical performance and reliable safety characteristics.At present,there are few studies focusing on their sa...The future large-scale application of sodium-ion batteries(SIBs)is inseparable from their excellent electrochemical performance and reliable safety characteristics.At present,there are few studies focusing on their safety performance.The analysis of thermal stability and structural changes within a single material cannot systematically describe the complex interplay of components within the battery system during the thermal runaway process.Furthermore,the reaction between the battery materials themselves and their counterparts within the system can stimulate more intense exothermic behavior,thereby affecting the safety of the entire battery system.Therefore,this study delved into the thermal generation and gas evolution characteristics of the positive electrode(Na_(x)Ni_(1/3)Fe_(1/3)Mn_(1/3)O_(2),NFM111)and the negative electrode(hard carbon,HC)in SIBs,utilizing various material combinations.Through the integration of microscopic and macroscopic characterization techniques,the underlying reaction mechanisms of the positive and negative electrode materials within the battery during the heating process were elucidated.Three important results are derived from this study:(Ⅰ)The instability of the solid electrolyte interphase(SEI)leads to its decomposition at temperatures below 100℃,followed by extensive decomposition within the range of 100-150℃,yielding heat and the formation of inorganic compounds,such as Na_(2)CO_(3)and Na_(2)O;(Ⅱ)The reaction between NFM111 and the electrolyte constitutes the primary exothermic event during thermal abuse,with a discernible reaction also occurring between sodium metal and the electrolyte throughout the heating process;(Ⅲ)The heat production and gas generation behaviors of multi-component reactions do not exhibit complete correlation,and the occurrence of gas production does not necessarily coincide with thermal behavior.The results presented in this study can provide useful guidance for the safety improvement of SIBs.展开更多
This study numerically examines the heat and mass transfer characteristics of two ternary nanofluids via converging and diverg-ing channels.Furthermore,the study aims to assess two ternary nanofluids combinations to d...This study numerically examines the heat and mass transfer characteristics of two ternary nanofluids via converging and diverg-ing channels.Furthermore,the study aims to assess two ternary nanofluids combinations to determine which configuration can provide better heat and mass transfer and lower entropy production,while ensuring cost efficiency.This work bridges the gap be-tween academic research and industrial feasibility by incorporating cost analysis,entropy generation,and thermal efficiency.To compare the velocity,temperature,and concentration profiles,we examine two ternary nanofluids,i.e.,TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O and TiO_(2)+SiO_(2)+Cu/H_(2)O,while considering the shape of nanoparticles.The velocity slip and Soret/Dufour effects are taken into consideration.Furthermore,regression analysis for Nusselt and Sherwood numbers of the model is carried out.The Runge-Kutta fourth-order method with shooting technique is employed to acquire the numerical solution of the governed system of ordinary differential equations.The flow pattern attributes of ternary nanofluids are meticulously examined and simulated with the fluc-tuation of flow-dominating parameters.Additionally,the influence of these parameters is demonstrated in the flow,temperature,and concentration fields.For variation in Eckert and Dufour numbers,TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O has a higher temperature than TiO_(2)+SiO_(2)+Cu/H_(2)O.The results obtained indicate that the ternary nanofluid TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O has a higher heat transfer rate,lesser entropy generation,greater mass transfer rate,and lower cost than that of TiO_(2)+SiO_(2)+Cu/H_(2)O ternary nanofluid.展开更多
Typhoons can cause large-area blackouts or partial outages of distribution networks.We define a partial outage state in the distribution network as a gray state and propose a gray-start strategy and two-stage distribu...Typhoons can cause large-area blackouts or partial outages of distribution networks.We define a partial outage state in the distribution network as a gray state and propose a gray-start strategy and two-stage distribution network emergency recovery framework.A phase-space reconstruction and stacked integrated model for predicting wind and photovoltaic generation during typhoon disasters is proposed in the first stage.This provides guidance for second-stage post-disaster emergency recovery scheduling.The emergency recovery scheduling model is established in the second stage,and this model is supported by a thermal power-generating unit,mobile emergency generators,and distributed generators.Distributed generation includes wind power generation,photovoltaics,fuel cells,etc.Simultaneously,we con-sider the gray-start based on the pumped storage unit to be an important first step in the emergency recovery strategy.This model is val-idated on the improved IEEE 33 node system,which utilizes data from the 2022 super typhoon“Muifa”in Zhoushan,Zhejiang,China.Simulations indicate the superiority of a gray start with a pumped storage unit and the proposed emergency recovery strategy.展开更多
文摘For decades,Xu has been committed to fulfilling the duty and mission of a scientist and educator—diving into the laws of nature,caring deeply for the nation,and earnestly cultivating younger generations.
基金supported by the Quantum Science and Technology-National Science and Technology Major Project (Grant No.2024ZD0302502 for WZ)the National Natural Science Foundation of China(Grant No.92365210 for WZ)+1 种基金Tsinghua Initiative Scientific Research Program (for WZ)the project of Tsinghua University-Zhuhai Huafa Industrial Share Company Joint Institute for Architecture Optoelectronic Technologies (JIAOT,for YH)。
文摘To fully utilize the resources provided by optical fiber networks,a cross-band quantum light source generating photon pairs,where one photon in a pair is at C band and the other is at O band,is proposed in this work.This source is based on spontaneous four-wave mixing(SFWM)in a piece of shallow-ridge silicon waveguide.Theoretical analysis shows that the waveguide dispersion could be tailored by adjusting the ridge width,enabling broadband photon pair generation by SFWM across C band and O band.The spontaneous Raman scattering(SpRS)in silicon waveguides is also investigated experimentally.It shows that there are two regions in the spectrum of generated photons from SpRS,which could be used to achieve cross-band photon pair generation.A chip of shallow-ridge silicon waveguide samples with different ridge widths has been fabricated,through which cross-band photon pair generation is demonstrated experimentally.The experimental results show that the source can be achieved using dispersion-optimized shallow-ridge silicon waveguides.This cross-band quantum light source provides a way to develop new fiber-based quantum communication functions utilizing both C band and O band and extends applications of quantum networks.
基金supported by the Natural Science Foundation of Fujian Province of China(2025J01380)National Natural Science Foundation of China(No.62471139)+3 种基金the Major Health Research Project of Fujian Province(2021ZD01001)Fujian Provincial Units Special Funds for Education and Research(2022639)Fujian University of Technology Research Start-up Fund(GY-S24002)Fujian Research and Training Grants for Young and Middle-aged Leaders in Healthcare(GY-H-24179).
文摘The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location reidentification and correlation attacks.To address these challenges,privacy-preserving trajectory generation methods are critical for applications relying on sensitive location data.This paper introduces DPIL-Traj,an advanced framework designed to generate synthetic trajectories while achieving a superior balance between data utility and privacy preservation.Firstly,the framework incorporates Differential Privacy Clustering,which anonymizes trajectory data by applying differential privacy techniques that add noise,ensuring the protection of sensitive user information.Secondly,Imitation Learning is used to replicate decision-making behaviors observed in real-world trajectories.By learning from expert trajectories,this component generates synthetic data that closely mimics real-world decision-making processes while optimizing the quality of the generated trajectories.Finally,Markov-based Trajectory Generation is employed to capture and maintain the inherent temporal dynamics of movement patterns.Extensive experiments conducted on the GeoLife trajectory dataset show that DPIL-Traj improves utility performance by an average of 19.85%,and in terms of privacy performance by an average of 12.51%,compared to state-of-the-art approaches.Ablation studies further reveal that DP clustering effectively safeguards privacy,imitation learning enhances utility under noise,and the Markov module strengthens temporal coherence.
文摘In 2021,the relatives of 16 international friends of China jointly sent a letter to Chinese President Xi Jinping,congratulating the Communist Party of China(CPC)on its 100th anniversary.These are the sons and daughters and family members of those who helped China in its times of need.Eric Foster,nephew of renowned U.S.journalist Helen Foster-Snow,was one of them.
基金financially supported by the National Science Fund for Distinguished Young Scholars,China(No.52025041)the National Natural Science Foundation of China(Nos.52450003,U2341267,and 52174294)+1 种基金the National Postdoctoral Program for Innovative Talents,China(No.BX20240437)the Fundamental Research Funds for the Central Universities,China(Nos.FRF-IDRY-23-037 and FRF-TP-20-02C2)。
文摘The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-learning(DL)-driven CV in four key areas of materials science:microstructure-based performance prediction,microstructure information generation,microstructure defect detection,and crystal structure-based property prediction.The CV has significantly reduced the cost of traditional experimental methods used in material performance prediction.Moreover,recent progress made in generating microstructure images and detecting microstructural defects using CV has led to increased efficiency and reliability in material performance assessments.The DL-driven CV models can accelerate the design of new materials with optimized performance by integrating predictions based on both crystal and microstructural data,thereby allowing for the discovery and innovation of next-generation materials.Finally,the review provides insights into the rapid interdisciplinary developments in the field of materials science and future prospects.
基金supported by the National Natural Science Foundation of China(No.51706105)。
文摘Al/NH_(4)CoF_(3)-Φ(Φ=0.5,1.0,1.5,2.0,and 3.0)binary composites and Al-NH_(4)CoF_(3)@P(VDF-HFP)ternary composites are fabricated via ultrasonication-assisted blending and electrostatic spraying.The effect of equivalence ratio(Φ)on the reaction properties is systematically investigated in the binary Al/NH_(4)CoF_(3)system.For ternary systems,electrostatic spraying allows both components to be efficiently encapsulated by P(VDF-HFP)and to achieve structural stabilization and enhanced reactivity through synergistic interfacial interactions.Morphological analysis using SEM/TEM revealed that P(VDF-HFP)formed a protective layer on Al and NH_(4)CoF_(3)particles,improving dispersion,hydrophobicity(water contact angle increased by 80.5%compared to physically mixed composites),and corrosion resistance.Thermal decomposition of NH_(4)CoF_(3)occurred at 265℃,releasing NH_(3)and HF,which triggered exothermic reactions with Al.The ternary composites exhibited a narrowed main reaction temperature range and concentrated heat release,attributed to improved interfacial contact and polymer decomposition.Combustion tests demonstrated that Al-NH_(4)CoF_(3)@P(VDF-HFP)achieved self-sustaining combustion.In addition,a simple validation was done by replacing the Al component in the aluminium-containing propellant,demonstrating its potential application in the propellant field.This work establishes a novel strategy for designing stable,high-energy composites with potential applications in advanced propulsion systems.
文摘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.
基金Nguyen Tat Thanh University,Ho Chi Minh City,Vietnam for supporting this study。
文摘Wing design is a critical factor in the aerodynamic performance of flapping-wing(FW)robots.Inspired by the natural wing structures of insects,bats,and birds,we explored how bio-mimetic wing vein morphologies,combined with a bio-inspired double wing clap-and-fling mechanism,affect thrust generation.This study focused on increasing vertical force and payload capacity.Through systematic experimentation with various vein configurations and structural designs,we developed innovative wings optimized for thrust production.Comprehensive tests were conducted to measure aerodynamic forces,power consumption,and wing kinematics across a range of flapping frequencies.Additionally,wings with different aspect ratios,a key factor in wing design,were fabricated and extensively evaluated.The study also examined the role of bio-inspired vein layouts on wing flexibility,a critical component in improving flight efficiency.Our findings demonstrate that the newly developed wing design led to a 20%increase in thrust,achieving up to 30 g-force(gf).This research sheds light on the clap-and-fling effect and establishes a promising framework for bio-inspired wing design,offering significant improvements in both performance and payload capacity for FW robots.
基金financial support from the Nuclear Energy Science&Technology and Human Resource Development Project of the Japan Atomic Energy Agency/Collaborative Laboratories for Advanced Decommissioning Science(No.R04I034)The author Ruicong Xu appreciates the scholarship(financial support)from the China Scholarship Council(CSC,No.202106380073).
文摘Laser-induced aerosols,predominantly submicron in size,pose significant environmental and health risks during the decommissioning of nuclear reactors.This study experimentally investigated the removal of laser-generated aerosol particles using a water spray system integrated with an innovative system for pre-injecting electrically charged mist in our facility.To simulate aerosol generation in reactor decommissioning,a high-power laser was used to irradiate various materials(including stainless steel,carbon steel,and concrete),generating aerosol particles that were agglomerated with injected water mist and subsequently scavenged by water spray.Experimental results demonstrate enhanced aerosol removal via aerosol-mist agglomeration,with charged mist significantly improving particle capture by increasing wettability and size.The average improvements for the stainless steel,carbon steel,and concrete were 40%,44%,and 21%,respectively.The results of experiments using charged mist with different polarities(both positive and negative)and different surface coatings reveal that the dominant polarity of aerosols varies with the irradiated materials,influenced by their crystal structure and electron emission properties.Notably,surface coatings such as ZrO_(2)and CeO_(2)were found to possibly alter aerosol charging characteristics,thereby affecting aerosol removal efficiency with charged mist configurations.The innovative aerosol-mist agglomeration approach shows promise in mitigating radiation exposure,ensuring environmental safety,and reducing contaminated water during reactor dismantling.This study contributes critical knowledge for the development of advanced aerosol management strategies for nuclear reactor decommissioning.The understanding obtained in this work is also expected to be useful for various environmental and chemical engineering applications such as gas decontamination,air purification,and pollution control.
基金supported by the National Key Research and Development Program of China(2023YFF0906502)the Postgraduate Research and Innovation Project of Hunan Province under Grant(CX20240473).
文摘Due to the digital transformation tendency among cultural institutions and the substantial influence of the social media platform,the demands of visual communication keep increasing for promoting traditional cultural artifacts online.As an effective medium,posters serve to attract public attention and facilitate broader engagement with cultural artifacts.However,existing poster generation methods mainly rely on fixed templates and manual design,which limits their scalability and adaptability to the diverse visual and semantic features of the artifacts.Therefore,we propose CAPGen,an automated aesthetic Cultural Artifacts Poster Generation framework built on a Multimodal Large Language Model(MLLM)with integrated iterative optimization.During our research,we collaborated with designers to define principles of graphic design for cultural artifact posters,to guide the MLLM in generating layout parameters.Later,we generated these parameters into posters.Finally,we refined the posters using an MLLM integrated with a multi-round iterative optimization mechanism.Qualitative results show that CAPGen consistently outperforms baseline methods in both visual quality and aesthetic performance.Furthermore,ablation studies indicate that the prompt,iterative optimization mechanism,and design principles significantly enhance the effectiveness of poster generation.
基金supported by the National Natural Science Foundation of China(Grant No.72161034).
文摘Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.
文摘Standards are the common language that consolidates global consensus and builds the most solid foundation for international partnerships.They are the cornerstone for global sustainable and high-quality development.Young students,with their active and vibrant minds,represent the future and hope of standardization.
基金The work described in this paper was fully supported by a grant from Hong Kong Metropolitan University(RIF/2021/05).
文摘Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using deep learning algorithms further enhances performance;nevertheless,it is challenging due to the nature of small-scale and imbalanced PD datasets.This paper proposed a convolutional neural network-based deep support vector machine(CNN-DSVM)to automate the feature extraction process using CNN and extend the conventional SVM to a DSVM for better classification performance in small-scale PD datasets.A customized kernel function reduces the impact of biased classification towards the majority class(healthy candidates in our consideration).An improved generative adversarial network(IGAN)was designed to generate additional training data to enhance the model’s performance.For performance evaluation,the proposed algorithm achieves a sensitivity of 97.6%and a specificity of 97.3%.The performance comparison is evaluated from five perspectives,including comparisons with different data generation algorithms,feature extraction techniques,kernel functions,and existing works.Results reveal the effectiveness of the IGAN algorithm,which improves the sensitivity and specificity by 4.05%–4.72%and 4.96%–5.86%,respectively;and the effectiveness of the CNN-DSVM algorithm,which improves the sensitivity by 1.24%–57.4%and specificity by 1.04%–163%and reduces biased detection towards the majority class.The ablation experiments confirm the effectiveness of individual components.Two future research directions have also been suggested.
基金National Natural Science Foundation of China(52065036,52365018)Natural Science Foundation of Gansu(23JRRA760)+1 种基金Hongliu Outstanding Youth Foundation of Lanzhou University of TechnologyChina Postdoctoral Science Foundation(2023M733583)。
文摘The scratching mechanism of polycrystallineγ-TiAl alloy was investigated at the atomic scale using the molecular dynamics method,with a focus on the influence of different grain sizes.The analysis encompassed tribological characteristics,scratch morphology,subsurface defect distribution,temperature variations,and stress states during the scratching process.The findings indicate that the scratch force,number of recovered atoms,and pile-up height exhibit abrupt changes when the critical size is 9.41 nm due to the influence of the inverse Hall-Petch effect.Variations in the number of grain boundaries and randomness of grain orientation result in different accumulation patterns on the scratch surface.Notably,single crystal materials and those with 3.73 nm in grain size display more regular surface morphology.Furthermore,smaller grain size leads to an increase in average coefficient of friction,removed atoms number,and wear rate.While it also causes higher temperatures with a larger range of distributions.Due to the barrier effect of grain boundaries,smaller grains exhibit reduced microscopic defects.Additionally,average von Mises stress and hydrostatic compressive stress at the indenter tip decrease as grain size decreases owing to grain boundary obstruction.
基金National Natural Science Foundation of China(Nos.4210144242394063).
文摘Since the release of ChatGPT in late 2022,Generative Artificial Intelligence(GAI)has gained widespread attention because of its impressive capabilities in language comprehension,reasoning,and generation.GAI has been successfully applied across various aspects(e.g.,creative writing,code generation,translation,and information retrieval).In cartography and GIS,researchers have employed GAI to handle some specific tasks,such as map generation,geographic question answering,and spatiotemporal data analysis,yielding a series of remarkable results.Although GAI-based techniques are developing rapidly,literature reviews of their applications in cartography and GIS remain relatively limited.This paper reviews recent GAI-related research in cartography and GIS,focusing on three aspects:①map generation,②geographical analysis,and③evaluation of GAI’s spatial cognition abilities.In addition,the paper analyzes current challenges and proposes future research directions.
基金funded by the Inner Mongolia Nature Foundation Project,Project number:2023JQ04.
文摘Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra,PSD,and random signal power spectra.The relationship was derived,validated through experiments and simulations,and subsequently applied to multi-objective optimization.Various optimization algorithms were compared to achieve optimal system power quality.The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model.An increase in the order of the AR model resulted in a 36%improvement in the number of optimal solutions.Regarding optimal solution distribution,NSGA-II demonstrated superior diversity,while MOEA/D exhibited better convergence.However,practical applications showed that while MOEA/D had higher convergence,NSGA-II produced superior optimal solutions,achieving the best power quality indices(THDi at 4.62%,d%at 3.51%,and cosφat 96%).These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.
基金supported by the National Key Research and Development Program(2023YFF1001500)the Local Financial Funds of National Agricultural Science and Technology Center,Chengdu(NASC2022KR02,NASC2023TD08,NASC2021ST08,NASC2021PC04,NASC2022KR07,NASC2022KR06,and NASC2023ST04)+2 种基金the Agricultural Science and Technology Innova-tion Program(ASTIP-34-IUA-01,ASTIP-34-IUA-02,ASTIP-IUA-2023003,and ASTIP2024-34-IUA-09)the Central Public-interest Scientific Institution Basal Research Fund(Y2023YJ07 and SZ202403)the Sichuan Science and Technology Program(2023YFN003,2024NSFC1261,2023YFQ0100,and 2023ZYD0089).
文摘Rice(Oryza sativa L.)plays a pivotal role in global food security,yet its breeding is constrained by its long generation time and seasonality.To enhance rice breeding efficiency and meet future food demands,we have developed a vertical hydroponic breeding system integrated with light-emitting diodes(LEDs)light-ing in a closed plant factory(PF),which significantly accelerates rice growth and generation advance-ment.The results show that indica rice can be harvested as early as after 63 days of cultivation,a 50%reduction compared with field cultivation,enabling the annual harvesting of 5-6 generations within the PF.A hyperspectral imaging(HSI)system and attenuated total reflectance infrared(ATR-IR)spec-troscopy were further employed to characterize the chemical composition of the PF-and field-cultivated rice.Metabolomics analysis with ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)and gas chromatography-mass spectrometry(GC-MS)revealed that,com-pared with the field-cultivated rice,the PF-cultivated rice exhibited an up-regulation of total phenolic acids along with 68 non-volatile and 19 volatile metabolites,such as isovitexin,succinic acid,and methylillicinone F.Overall,this study reveals the unique metabolic profile of PF-cultivated rice and high-lights the potential of PFs to accelerate the breeding of crops such as rice,offering an innovative agricul-tural strategy to support food security in the face of global population growth and climate change.
基金supported by the National Natural Science Foundation of China(52404259)supported by Youth Innovation Promotion Association CAS(Y201768)。
文摘The future large-scale application of sodium-ion batteries(SIBs)is inseparable from their excellent electrochemical performance and reliable safety characteristics.At present,there are few studies focusing on their safety performance.The analysis of thermal stability and structural changes within a single material cannot systematically describe the complex interplay of components within the battery system during the thermal runaway process.Furthermore,the reaction between the battery materials themselves and their counterparts within the system can stimulate more intense exothermic behavior,thereby affecting the safety of the entire battery system.Therefore,this study delved into the thermal generation and gas evolution characteristics of the positive electrode(Na_(x)Ni_(1/3)Fe_(1/3)Mn_(1/3)O_(2),NFM111)and the negative electrode(hard carbon,HC)in SIBs,utilizing various material combinations.Through the integration of microscopic and macroscopic characterization techniques,the underlying reaction mechanisms of the positive and negative electrode materials within the battery during the heating process were elucidated.Three important results are derived from this study:(Ⅰ)The instability of the solid electrolyte interphase(SEI)leads to its decomposition at temperatures below 100℃,followed by extensive decomposition within the range of 100-150℃,yielding heat and the formation of inorganic compounds,such as Na_(2)CO_(3)and Na_(2)O;(Ⅱ)The reaction between NFM111 and the electrolyte constitutes the primary exothermic event during thermal abuse,with a discernible reaction also occurring between sodium metal and the electrolyte throughout the heating process;(Ⅲ)The heat production and gas generation behaviors of multi-component reactions do not exhibit complete correlation,and the occurrence of gas production does not necessarily coincide with thermal behavior.The results presented in this study can provide useful guidance for the safety improvement of SIBs.
基金supported by DST-FIST(Government of India)(Grant No.SR/FIST/MS-1/2017/13)and Seed Money Project(Grant No.DoRDC/733).
文摘This study numerically examines the heat and mass transfer characteristics of two ternary nanofluids via converging and diverg-ing channels.Furthermore,the study aims to assess two ternary nanofluids combinations to determine which configuration can provide better heat and mass transfer and lower entropy production,while ensuring cost efficiency.This work bridges the gap be-tween academic research and industrial feasibility by incorporating cost analysis,entropy generation,and thermal efficiency.To compare the velocity,temperature,and concentration profiles,we examine two ternary nanofluids,i.e.,TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O and TiO_(2)+SiO_(2)+Cu/H_(2)O,while considering the shape of nanoparticles.The velocity slip and Soret/Dufour effects are taken into consideration.Furthermore,regression analysis for Nusselt and Sherwood numbers of the model is carried out.The Runge-Kutta fourth-order method with shooting technique is employed to acquire the numerical solution of the governed system of ordinary differential equations.The flow pattern attributes of ternary nanofluids are meticulously examined and simulated with the fluc-tuation of flow-dominating parameters.Additionally,the influence of these parameters is demonstrated in the flow,temperature,and concentration fields.For variation in Eckert and Dufour numbers,TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O has a higher temperature than TiO_(2)+SiO_(2)+Cu/H_(2)O.The results obtained indicate that the ternary nanofluid TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O has a higher heat transfer rate,lesser entropy generation,greater mass transfer rate,and lower cost than that of TiO_(2)+SiO_(2)+Cu/H_(2)O ternary nanofluid.
基金supported in part by the National Nat-ural Science Foundation of China(52177110)Key Pro-gram of the National Natural Science Foundation of China(U22B20106,U2142206)+2 种基金Shenzhen Science and Technology Program(JCYJ20210324131409026)the Science and Technology Project of the State Grid Corpo-ration of China(5200-202319382A-2-3-XG)State Grid Zhejiang Elctric Power Co.,Ltd.Science and Tech-nology Project(B311DS24001A).
文摘Typhoons can cause large-area blackouts or partial outages of distribution networks.We define a partial outage state in the distribution network as a gray state and propose a gray-start strategy and two-stage distribution network emergency recovery framework.A phase-space reconstruction and stacked integrated model for predicting wind and photovoltaic generation during typhoon disasters is proposed in the first stage.This provides guidance for second-stage post-disaster emergency recovery scheduling.The emergency recovery scheduling model is established in the second stage,and this model is supported by a thermal power-generating unit,mobile emergency generators,and distributed generators.Distributed generation includes wind power generation,photovoltaics,fuel cells,etc.Simultaneously,we con-sider the gray-start based on the pumped storage unit to be an important first step in the emergency recovery strategy.This model is val-idated on the improved IEEE 33 node system,which utilizes data from the 2022 super typhoon“Muifa”in Zhoushan,Zhejiang,China.Simulations indicate the superiority of a gray start with a pumped storage unit and the proposed emergency recovery strategy.
