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
This study explores the impact of intergenerational differences on farmers' terrace abandonment in response to increasing intergenerational differentiation among rural households and the practical issue of terrace...This study explores the impact of intergenerational differences on farmers' terrace abandonment in response to increasing intergenerational differentiation among rural households and the practical issue of terrace abandonment. Logit and Tobit models are employed to conduct empirical analysis and it is found that terrace abandonment increases sequentially among the new, middle, and old generations, confirming that intergenerational differences significantly influence whether farmers abandon terraces and the terrace abandonment scale. Village characteristics and government subsidies significantly influence farmers' terrace abandonment. An increase in the number of migrant workers in the village increases terrace abandonment among new and middle generation farmers, whereas an increase in the distance from the village to the county significantly increases terrace abandonment among old generation farmers. An increase in the village's total population significantly reduces terrace abandonment among new generation farmers. An increase in government subsidies significantly reduces terrace abandonment among middle and old generation farmers. The impact of intergenerational differences on terrace abandonment is more pronounced in low-altitude areas. To reduce terrace abandonment, it is necessary to promote terrace transfer, develop characteristic agriculture, improve terrace farming subsidies, and propose targeted strategies for the different generations of farmers.展开更多
This study investigates the complex heat transfer dynamics inmultilayer bifacial photovoltaic(bPV)solar modules under spectrally resolved solar irradiation.A novel numericalmodel is developed to incorporate internal h...This study investigates the complex heat transfer dynamics inmultilayer bifacial photovoltaic(bPV)solar modules under spectrally resolved solar irradiation.A novel numericalmodel is developed to incorporate internal heat generation resulting from optical absorption,grounded in the physical equations governing light-matter interactions within the module’smultilayer structure.The model accounts for reflection and transmission at each interface between adjacent layers,as well as absorption within individual layers,using the wavelength-dependent dielectric properties of constituent materials.These properties are used to calculate the spectral reflectance,transmittance,and absorption coefficients,enabling precise quantification of internal heat sources from irradiance incidents on both the front and rear surfaces of the module.The study further examines the influence of irradiance reflection on thermal behavior,evaluates the thermal impact of various supporting materials placed beneath the module,and analyzes the role of albedo in modifying heat distribution.By incorporating spectrally resolved heat generation across each layer often simplified or omitted in conventional models,the proposed approach enhances physical accuracy.The transient heat equation is solved using a one-dimensional finite difference(FD)method to produce detailed temperature profiles under multiple operating scenarios,including Standard Test Conditions(STC),Bifacial Standard Test Conditions(BSTC),Normal Operating Cell Temperature(NOCT),and Bifacial NOCT(BNOCT).The results offer valuable insights into the interplay between optical and thermal phenomena in bifacial systems,informing the design and optimization of more efficient photovoltaic technologies.展开更多
In this paper,the growth characteristic of meromorphic solutions for the following difference equation An(z)f(z+n)+…+A1(z)f(z+1)+A0(z)f(z)=0 with no dominating coefficient is studied.By imposing certain restriction o...In this paper,the growth characteristic of meromorphic solutions for the following difference equation An(z)f(z+n)+…+A1(z)f(z+1)+A0(z)f(z)=0 with no dominating coefficient is studied.By imposing certain restriction on the entire coefficients associated with Petrenko's deviation of the above equation,we obtain some results and partially address a question posed byⅠ.Laine and C.C.Yang.Furthermore,for the entire solutions f(z)of the difference equation An(z)f(z+n)+…+A1(z)f(z+1)+A0(z)f(z)=F(z),where Aj(z)(j=0,…,n),F(z)are entire functions,we discover a close relationship between the measure of common transcendental directions associated with classical difference operators of f(z)and Petrenko's deviations of the coefficients.展开更多
The global energy crisis and electricity shortage pose unprecedented challenges.Bio-based solar-driven ionic power generation devices with flexibility,photothermal self-healing and scalability hold great promise for s...The global energy crisis and electricity shortage pose unprecedented challenges.Bio-based solar-driven ionic power generation devices with flexibility,photothermal self-healing and scalability hold great promise for sustainable electricity and alleviating energy crisis.Here,inspired by plant transpiration,a multifunctional bio-based ion conductive elastomer with solar power generation capability was designed by engineered synergy among epoxy natural rubber,cellulose nanofibrils,lithium bis(trifluoromethane)sulfonimide and eumelanin.The film exhibits an outstanding stretchability(1072%)and toughness(22.7 MJ m^(-3)).The favorable synergy of low thermal conductivity,high hygroscopicity and photothermal conversion performance endowed the film with a large thermal gradient under light illumination,driving efficient water transpiration.Furthermore,the excellent interfacial compatibility between eumelanin and matrix facilitates the formation of space charge regions,which further enhances Li^(+)transport.The film demonstrates excellent evaporation rate(2.83 kg m^(-2)h^(-1)),output voltage(0.47 V)and conductivity(5.11×10^(-2)S m^(-1)).Notably,the film exhibits remarkable photothermal self-healing performance even in saline environment,achieving 99.6%healing efficiency of output voltage.Therefore,the film demonstrates significant prospects for applications in photo-thermoelectric generation and solar-driven ionic power generation.展开更多
Electroosmotic transport and entropy generation play a decisive role in regulating efficiency,stability,and energy cost of non-Newtonian nanoblood flows in stenosed arteries,particularly with tapered geometries.Thisst...Electroosmotic transport and entropy generation play a decisive role in regulating efficiency,stability,and energy cost of non-Newtonian nanoblood flows in stenosed arteries,particularly with tapered geometries.Thisstudy develops a unified model to analyze ZnO-Williamson nanoblood flow through a stenosed artery with converging,diverging,and non-tapered configurations,incorporating electroosmosis,viscous dissipation,and entropy production.The arterial walls are assumed to be electrically charged with a no-slip condition to induce electroosmotic propulsionalong the endothelial surface.The partial differential equations are nondimensionalized to a coupled system ofnonlinear ordinary differential equations,which are solved numerically using a MATLAB-based shooting technique.Parametric investigation is conducted for Brinkman,Grashof,and Weissenberg numbers,ZnO fractional volume,volumetric flow rate,and Helmholtz-Smoluchowski velocity to quantify their influences on axial velocity,wall shearstress,impedance resistance,temperature distribution,entropy generation,Bejan number,and streamline topology.The axial velocity decreases radially with increasing Brinkman number for all arterial geometries.Increasing ZnOnanoparticles improves thermal transport owing to enhanced effective thermal conductivity but simultaneously elevatesentropy generation due to increased viscous dissipation.Higher Weissenberg numbers suppress entropy production bypromoting elastic stress redistribution and lowering shear-induced irreversibility.Impedance resistance decreases withincreasing stenosis height but increases with stenosis shape parameter and ZnO fractional volume.Streamline analysisshows that buoyancy and viscoelasticity significantly distort flow near the stenosis,while increasing electroosmoticvelocity stabilizes streamlines,suppresses recirculation,and reduces local shear stress and pressure fluctuations.Inconclusion,electroosmotic actuation is most effective in reducing flow resistance in the converging tapered artery,particularly at lower ZnO volume fractions.Overall,the findings highlight the potential of optimized electroosmoticactuation and controlled nanoparticle loading to minimize thermodynamic losses,regulate shear stress,and improveflow uniformity in stenosed vessels,with promising implications for electro-assisted drug delivery,nanotherapeutics,and bio-inspired vascular microfluidic systems.展开更多
With their intricate vectorial structures in space,optical skyrmions have significantly expanded the landscape of topological optics and light-matter interactions.We theoretically investigate high harmonic generation ...With their intricate vectorial structures in space,optical skyrmions have significantly expanded the landscape of topological optics and light-matter interactions.We theoretically investigate high harmonic generation in crystals driven by optical skyrmions.We find that although the skyrmion number is not conserved,the resulting high-order harmonics can exhibit a distinctive multi-vortex structure,whose features are shaped by both the topology of the optical skyrmions and the rotational symmetry of the crystal.The position of the vortex centers can be effectively tuned by employing different types of optical skyrmions.To elucidate the underlying physics,we develop a multi-absorption channel model based on the conservation laws of spin and orbital angular momentum.Our work explores the role of optical topology in extreme nonlinear light-matter interactions,offering new opportunities for the formation and manipulation of optical vortices and novel structured light fields in the visible and ultraviolet regimes.展开更多
With the rapid development of image-generative AI (artificial intelligence) technology, its application in undergraduate Landscape Architecture education has demonstrated significant potential. Based on this, the pres...With the rapid development of image-generative AI (artificial intelligence) technology, its application in undergraduate Landscape Architecture education has demonstrated significant potential. Based on this, the present study explores the implications of integrating image-generative AI into Landscape Architecture courses from three perspectives: stimulating students creative design potential, expanding approaches to form and concept generation, and enhancing the visualization of spatial scenes. Furthermore, it discusses application strategies from three dimensions: AI-assisted conceptual generation, human-machine collaboration for design refinement, and optimization of scheme presentation and evaluation. This paper aims to provide relevant educators with insights and references.展开更多
With the rise of AI-assisted education,many instructors and engineers seek to deliver high-quality programming courses online.However,crafting effective programming lectures remains a challenge,particularly for instru...With the rise of AI-assisted education,many instructors and engineers seek to deliver high-quality programming courses online.However,crafting effective programming lectures remains a challenge,particularly for instructors lacking pedagogical training or multilingual fluency.We present CourseAgent,a prompt-driven framework that leverages large language models(LLMs)to automatically generate Python tutorials,structured lecture scripts,and accompanying audio narrations.CourseAgent accepts raw code as input and transforms it into segmented,well-commented code blocks,adapting content to different difficulty levels and languages via prompt customization.Our system supports multilingual instruction(e.g.,Chinese,English),fine-grained control of pedagogical depth,and auto-generation of lecture videos.We evaluate the output generated by CourseAgent using real student feedback and feedback from in-service teachers,alongside automated assessments from LLMs.These evaluations demonstrate that the materials produced by CourseAgent are coherent,pedagogically sound,and comparable in quality to those created by experienced instructors.CourseAgent lowers the barrier to quality programming education and shows promise for scalable,personalized,and language-adaptive content generation.展开更多
High-precision optical frequency measurement serves as a cornerstone of modern science and technology,enabling advancements in fields ranging from fundamental physics to quantum information technologies.Obtaining prec...High-precision optical frequency measurement serves as a cornerstone of modern science and technology,enabling advancements in fields ranging from fundamental physics to quantum information technologies.Obtaining precise photon frequencies,especially in the ultraviolet or even extreme ultraviolet regimes,is a key goal in both light–matter interaction experiments and engineering applications.High-order harmonic generation(HHG)is an ideal light source for producing such photons.In this work,we propose an optical temporal interference model(OTIM)that establishes an analogy with multi-slit Fraunhofer diffraction(MSFD)to manipulate fine-frequency photon generation by exploiting the temporal coherence of HHG processes.Our model provides a unified physical framework for three distinct non-integer HHG generation schemes:single-pulse,shaped-pulse,and laser pulse train approaches,which correspond to single-MSFD-like,double-MSFD-like,and multi-MSFD-like processes,respectively.Arbitrary non-integer HHG photons can be obtained using our scheme.Our approach provides a new perspective for accurately measuring and controlling photon frequencies in fields such as frequency comb technology,interferometry,and atomic clocks.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
The occurrence of severe thalassemia,an inherited blood disorder that is either blood-transfusiondependent or fatal,can be mitigated through carrier screening.Here,we aim to evaluate the effectiveness and outcomes of ...The occurrence of severe thalassemia,an inherited blood disorder that is either blood-transfusiondependent or fatal,can be mitigated through carrier screening.Here,we aim to evaluate the effectiveness and outcomes of pre-conceptional and early pregnancy screening initiatives for severe thalassemia prevention in a diverse population of 28,043 women.Using next-generation sequencing(NGS),we identify 4,226(15.07%)thalassemia carriers across 29 ethnic groups and categorize them into high-(0.75%),low-(25.86%),and unknown-risk(69.19%)groups based on their spouses'screening results.Post-screening follow-up reveals 59 fetuses with severe thalassemia exclusively in high-risk couples,underscoring the efficacy of risk classification.Among 25,053 live births over 6 months of age,two severe thalassemia infants were born to unknown-risk couples,which was attributed to incomplete screening and late NGS-based testing for a rare variant.Notably,64 rare variants are identified in 287 individuals,highlighting the genetic heterogeneity of thalassemia.We also observe that migrant flow significantly impacts carrier rates,with 93.90%of migrants to Chenzhou originating from high-prevalence regions in southern China.Our study demonstrates that NGS-based screening during pre-conception and early pregnancy is effective for severe thalassemia prevention,emphasizing the need for continuous screening efforts in areas with high and underestimated prevalence.展开更多
Thermomagnetic generation(TMG),a heat-to-electricity conversion technology based on the thermomagnetic effect,offers high reliability and broad adaptability to diverse heat sources.By exploiting the temperature-depend...Thermomagnetic generation(TMG),a heat-to-electricity conversion technology based on the thermomagnetic effect,offers high reliability and broad adaptability to diverse heat sources.By exploiting the temperature-dependent magnetization of thermomagnetic materials,TMG converts thermal energy into electrical energy through cyclic changes in magnetic flux based on Faraday's law.The performance of TMG systems is largely governed by the intrinsic properties of the working materials and the design of device architecture.Ideal TMG materials exhibit sharp and reversible magnetization transitions near the operating temperature,low thermal hysteresis,and high thermal conductivity.Device configurations can be broadly categorized into active and passive systems:active TMG devices rely on controlled thermal cycling and optimized magnetic circuits for enhanced output,whereas passive devices utilize self-actuated mechanical motion to generate electricity.In this topical review,we provide a comprehensive overview of recent advances in TMG materials and device configurations.Furthermore,we discuss future development trends and offer perspectives on experimental strategies to advance this field.展开更多
Urban populations are increasingly exposed to extreme heat due to climate change and rapid urbanization,heightening health risks in cities worldwide.Accurate heat exposure assessment is essential for public health pla...Urban populations are increasingly exposed to extreme heat due to climate change and rapid urbanization,heightening health risks in cities worldwide.Accurate heat exposure assessment is essential for public health planning and risk reduction.Most existing approaches rely on a single threshold temperature(e.g.,35℃of daily max temperature),applied uniformly to the entire population.However,this one-size-fits-all assumption overlooks substantial differences in heat sensitivity across population subgroups.In this study,we address this limitation by quantifying subgroup-specific temperature-mortality relationships and using corresponding minimum mortality temperatures(MMTs)to assess heat exposure.Results show that the population-wide MMT was 27.5℃,but it varied greatly across population subgroups.The elderly population(≥65)had an MMT of 24.6℃,much lower than the 28.6℃observed in younger individuals(<65).Females also exhibited a lower MMT that males(25℃versus 28.2℃).However,educational attainment did not significantly affect MMT.Using a uniform MMT resulted in substantial underestimation of heat exposure,ranging from 25.3%in 1990 to 13.9%in 2020,reflecting demographic shifts over time.Spatially,nearly half of the city experienced underestimated heat risk,especially in central and northeastern regions where heat-vulnerable populations are concentrated.These findings underscore the need for more nuanced heat exposure assessments that account for demographic and spatial variability,paving the way for targeted public health interventions to protect the most vulnerable urban populations.展开更多
It remains difficult to automate the creation and validation of Unified Modeling Language(UML)dia-grams due to unstructured requirements,limited automated pipelines,and the lack of reliable evaluation methods.This stu...It remains difficult to automate the creation and validation of Unified Modeling Language(UML)dia-grams due to unstructured requirements,limited automated pipelines,and the lack of reliable evaluation methods.This study introduces a cohesive architecture that amalgamates requirement development,UML synthesis,and multimodal validation.First,LLaMA-3.2-1B-Instruct was utilized to generate user-focused requirements.Then,DeepSeek-R1-Distill-Qwen-32B applies its reasoning skills to transform these requirements into PlantUML code.Using this dual-LLM pipeline,we constructed a synthetic dataset of 11,997 UML diagrams spanning six major diagram families.Rendering analysis showed that 89.5%of the generated diagrams compile correctly,while invalid cases were detected automatically.To assess quality,we employed a multimodal scoring method that combines Qwen2.5-VL-3B,LLaMA-3.2-11B-Vision-Instruct and Aya-Vision-8B,with weights based on MMMU performance.A study with 94 experts revealed strong alignment between automatic and manual evaluations,yielding a Pearson correlation of r=0.82 and a Fleiss’Kappa of 0.78.This indicates a high degree of concordance between automated metrics and human judgment.Overall,the results demonstrated that our scoring system is effective and that the proposed generation pipeline produces UML diagrams that are both syntactically correct and semantically coherent.More broadly,the system provides a scalable and reproducible foundation for future work in AI-driven software modeling and multimodal verification.展开更多
The annual compliance cycle of the carbon trading system allows generation companies(GenCos)to decouple the timing of carbon allowance purchases from their actual emissions.However,trading a large volume of allowances...The annual compliance cycle of the carbon trading system allows generation companies(GenCos)to decouple the timing of carbon allowance purchases from their actual emissions.However,trading a large volume of allowances within a single day can significantly impact on carbon prices.Faced with uncertain future carbon and electricity prices,GenCos must address a challenging multistage stochastic optimization problem to coordinate their carbon trading strategies with daily power generation decisions.In this paper,a two-layered hybrid mathematical-deep reinforcement learning(DRL)optimization framework is proposed.The upper DRL layer tackles the stochastic,year-long carbon trading and allowance usage optimization problem,aiming for long-term optimality and providing guidance for short-term decisions in the lower layer.The lower mathematical optimization layer addresses the deterministic daily power generation schedule problem while enforcing strict technical constraints.To accelerate learning of the annual compliance cycle,a decision timeline transfer learning method is proposed,enabling the DRL agent to progressively refine its policy through sequentially training on monthly,weekly and daily decision environments.Case studies demonstrate that,with these methods,a GenCo can reduce emission costs and increase profits by effectively leveraging carbon price fluctuations within the compliance cycle.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
AIM:To investigate the sex-specific correlation between systemic factors and retinal neurovascular alterations in individuals with type 1 diabetes mellitus(T1DM)who do not exhibit signs of diabetic retinopathy(DR).MET...AIM:To investigate the sex-specific correlation between systemic factors and retinal neurovascular alterations in individuals with type 1 diabetes mellitus(T1DM)who do not exhibit signs of diabetic retinopathy(DR).METHODS:A cohort participant without DR diagnosed with T1DM,underwent comprehensive ophthalmologic evaluation,optical coherence tomography angiography retinal structural and microvascular density analysis,and systemic parameter assessment.Multiple linear regression analysis was used to investigate the impact of systemic parameters on retinal alterations in distinct gender groups.RESULTS:A total of 182 individuals were included,consisting of 85 males(mean age 23.28±12.75y)and 97 females(mean age 22.98±13.68y).Males exhibited significantly greater thickness in both the internal retinal layer and the entire retina compared to females(P<0.01),whereas females had higher densities of deep retinal vessels and choroidal capillaries(P<0.05).Additionally,glycemic control was found to have a notable influence on retinal thickness in males(P<0.05),while insulin function had a more pronounced impact on retinal structure in females(P<0.01).Furthermore,a significant correlation was observed between thyroid function markers and retinal parameters in both male and female(P<0.05).CONCLUSION:Sex differences in alterations in retinal structure and microcirculation are observed in individuals with T1DM prior to the development of clinical DR,with a noted association between these changes and systemic parameters.展开更多
China's requisition-compensation balance strategy has dramatically reshaped cropland spatial patterns,drawing multidisciplinary research attention.However,existing studies predominantly emphasize horizontal distri...China's requisition-compensation balance strategy has dramatically reshaped cropland spatial patterns,drawing multidisciplinary research attention.However,existing studies predominantly emphasize horizontal distribution,overlooking the significant influence of slope gradient on cropland spatial patterns.This paper proposes a slope location quotient(SLQ)index that reflects the relative advantage of cropland distribution and explores the slope grade difference of cropland spatial patterns in China at the county scale.The analysis adopts 30-m resolution digital elevation model with land cover data,taking 2672 counties with cropland ratio>1%as study units.The temporal scope covers 1990 and 2020,with slope gradients categorized into five grades:0°~2°,2°~6°,6°~15°,15°~25°,and 25°~90°.Results show that:1)The inverse correlation between cropland area and slope gradient remained stable throughout the study period,with the variation in cropland area frequency across slope grades being less than 1%.2)The spatial patterns of SLQ in 1990 and 2020 both transited stepwise with slope gradient,while≤2°and>6°slopes exhibited opposing patterns.3)The mean absolute variation of SLQ during 1990-2020 increased with slope gradient(R2=0.926,p<0.01).Particularly for slope grades>15°,the mean absolute variation reached 0.26(for 15°~25°)and 0.43(for 25°~90°),respectively,and displayed a distinct southward-increasing and northwarddecreasing pattern.This study offers novel slopegradient perspectives for analyzing cropland spatial patterns.To enhance cropland protection benefits,reversing the steep cropland SLQ surge in southern China is recommended.展开更多
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.
基金Key Program of National Natural Science Foundation of China,No.41930757National Natural Science Foundation of China,No.42371285。
文摘This study explores the impact of intergenerational differences on farmers' terrace abandonment in response to increasing intergenerational differentiation among rural households and the practical issue of terrace abandonment. Logit and Tobit models are employed to conduct empirical analysis and it is found that terrace abandonment increases sequentially among the new, middle, and old generations, confirming that intergenerational differences significantly influence whether farmers abandon terraces and the terrace abandonment scale. Village characteristics and government subsidies significantly influence farmers' terrace abandonment. An increase in the number of migrant workers in the village increases terrace abandonment among new and middle generation farmers, whereas an increase in the distance from the village to the county significantly increases terrace abandonment among old generation farmers. An increase in the village's total population significantly reduces terrace abandonment among new generation farmers. An increase in government subsidies significantly reduces terrace abandonment among middle and old generation farmers. The impact of intergenerational differences on terrace abandonment is more pronounced in low-altitude areas. To reduce terrace abandonment, it is necessary to promote terrace transfer, develop characteristic agriculture, improve terrace farming subsidies, and propose targeted strategies for the different generations of farmers.
文摘This study investigates the complex heat transfer dynamics inmultilayer bifacial photovoltaic(bPV)solar modules under spectrally resolved solar irradiation.A novel numericalmodel is developed to incorporate internal heat generation resulting from optical absorption,grounded in the physical equations governing light-matter interactions within the module’smultilayer structure.The model accounts for reflection and transmission at each interface between adjacent layers,as well as absorption within individual layers,using the wavelength-dependent dielectric properties of constituent materials.These properties are used to calculate the spectral reflectance,transmittance,and absorption coefficients,enabling precise quantification of internal heat sources from irradiance incidents on both the front and rear surfaces of the module.The study further examines the influence of irradiance reflection on thermal behavior,evaluates the thermal impact of various supporting materials placed beneath the module,and analyzes the role of albedo in modifying heat distribution.By incorporating spectrally resolved heat generation across each layer often simplified or omitted in conventional models,the proposed approach enhances physical accuracy.The transient heat equation is solved using a one-dimensional finite difference(FD)method to produce detailed temperature profiles under multiple operating scenarios,including Standard Test Conditions(STC),Bifacial Standard Test Conditions(BSTC),Normal Operating Cell Temperature(NOCT),and Bifacial NOCT(BNOCT).The results offer valuable insights into the interplay between optical and thermal phenomena in bifacial systems,informing the design and optimization of more efficient photovoltaic technologies.
基金Supported by the National Natural Science Foundation of China(Grant No.11661043)and the ScienceTechnology Research Project of Jiangxi Provincial Department of Education(Grant No.GJJ2200320).
文摘In this paper,the growth characteristic of meromorphic solutions for the following difference equation An(z)f(z+n)+…+A1(z)f(z+1)+A0(z)f(z)=0 with no dominating coefficient is studied.By imposing certain restriction on the entire coefficients associated with Petrenko's deviation of the above equation,we obtain some results and partially address a question posed byⅠ.Laine and C.C.Yang.Furthermore,for the entire solutions f(z)of the difference equation An(z)f(z+n)+…+A1(z)f(z+1)+A0(z)f(z)=F(z),where Aj(z)(j=0,…,n),F(z)are entire functions,we discover a close relationship between the measure of common transcendental directions associated with classical difference operators of f(z)and Petrenko's deviations of the coefficients.
基金financially supported by the National Natural Science Foundation of China(22175044)the Guangxi Natural Science Foundation(2023GXNSFDA026049)the Guangxi Major Talents Program(GXR-1BGQ2424023)。
文摘The global energy crisis and electricity shortage pose unprecedented challenges.Bio-based solar-driven ionic power generation devices with flexibility,photothermal self-healing and scalability hold great promise for sustainable electricity and alleviating energy crisis.Here,inspired by plant transpiration,a multifunctional bio-based ion conductive elastomer with solar power generation capability was designed by engineered synergy among epoxy natural rubber,cellulose nanofibrils,lithium bis(trifluoromethane)sulfonimide and eumelanin.The film exhibits an outstanding stretchability(1072%)and toughness(22.7 MJ m^(-3)).The favorable synergy of low thermal conductivity,high hygroscopicity and photothermal conversion performance endowed the film with a large thermal gradient under light illumination,driving efficient water transpiration.Furthermore,the excellent interfacial compatibility between eumelanin and matrix facilitates the formation of space charge regions,which further enhances Li^(+)transport.The film demonstrates excellent evaporation rate(2.83 kg m^(-2)h^(-1)),output voltage(0.47 V)and conductivity(5.11×10^(-2)S m^(-1)).Notably,the film exhibits remarkable photothermal self-healing performance even in saline environment,achieving 99.6%healing efficiency of output voltage.Therefore,the film demonstrates significant prospects for applications in photo-thermoelectric generation and solar-driven ionic power generation.
基金funded by the Ministry of Higher Education,Malaysia,under the Fundamental Research Grant Scheme FRGS/1/2023/STG06/UM/02/4(Project FP069-2023)。
文摘Electroosmotic transport and entropy generation play a decisive role in regulating efficiency,stability,and energy cost of non-Newtonian nanoblood flows in stenosed arteries,particularly with tapered geometries.Thisstudy develops a unified model to analyze ZnO-Williamson nanoblood flow through a stenosed artery with converging,diverging,and non-tapered configurations,incorporating electroosmosis,viscous dissipation,and entropy production.The arterial walls are assumed to be electrically charged with a no-slip condition to induce electroosmotic propulsionalong the endothelial surface.The partial differential equations are nondimensionalized to a coupled system ofnonlinear ordinary differential equations,which are solved numerically using a MATLAB-based shooting technique.Parametric investigation is conducted for Brinkman,Grashof,and Weissenberg numbers,ZnO fractional volume,volumetric flow rate,and Helmholtz-Smoluchowski velocity to quantify their influences on axial velocity,wall shearstress,impedance resistance,temperature distribution,entropy generation,Bejan number,and streamline topology.The axial velocity decreases radially with increasing Brinkman number for all arterial geometries.Increasing ZnOnanoparticles improves thermal transport owing to enhanced effective thermal conductivity but simultaneously elevatesentropy generation due to increased viscous dissipation.Higher Weissenberg numbers suppress entropy production bypromoting elastic stress redistribution and lowering shear-induced irreversibility.Impedance resistance decreases withincreasing stenosis height but increases with stenosis shape parameter and ZnO fractional volume.Streamline analysisshows that buoyancy and viscoelasticity significantly distort flow near the stenosis,while increasing electroosmoticvelocity stabilizes streamlines,suppresses recirculation,and reduces local shear stress and pressure fluctuations.Inconclusion,electroosmotic actuation is most effective in reducing flow resistance in the converging tapered artery,particularly at lower ZnO volume fractions.Overall,the findings highlight the potential of optimized electroosmoticactuation and controlled nanoparticle loading to minimize thermodynamic losses,regulate shear stress,and improveflow uniformity in stenosed vessels,with promising implications for electro-assisted drug delivery,nanotherapeutics,and bio-inspired vascular microfluidic systems.
基金supported by the National Natural Science Foundation of China (Grant Nos. 12234002, 92250303, 12474486, 12504301, and 12504396)the National Key Research and Development Program of China (Grant No. 2024YFA1612101)。
文摘With their intricate vectorial structures in space,optical skyrmions have significantly expanded the landscape of topological optics and light-matter interactions.We theoretically investigate high harmonic generation in crystals driven by optical skyrmions.We find that although the skyrmion number is not conserved,the resulting high-order harmonics can exhibit a distinctive multi-vortex structure,whose features are shaped by both the topology of the optical skyrmions and the rotational symmetry of the crystal.The position of the vortex centers can be effectively tuned by employing different types of optical skyrmions.To elucidate the underlying physics,we develop a multi-absorption channel model based on the conservation laws of spin and orbital angular momentum.Our work explores the role of optical topology in extreme nonlinear light-matter interactions,offering new opportunities for the formation and manipulation of optical vortices and novel structured light fields in the visible and ultraviolet regimes.
基金Supported by Applied Brand Course of Mianyang Teacher's College(Investigation and Monitoring of Natural Resources).
文摘With the rapid development of image-generative AI (artificial intelligence) technology, its application in undergraduate Landscape Architecture education has demonstrated significant potential. Based on this, the present study explores the implications of integrating image-generative AI into Landscape Architecture courses from three perspectives: stimulating students creative design potential, expanding approaches to form and concept generation, and enhancing the visualization of spatial scenes. Furthermore, it discusses application strategies from three dimensions: AI-assisted conceptual generation, human-machine collaboration for design refinement, and optimization of scheme presentation and evaluation. This paper aims to provide relevant educators with insights and references.
基金supported by the Zhejiang Province Leading Geese Plan(Grant No.2025C02025)the Guangdong Province Primary and Secondary School Teachers’Digital Literacy Enhancement Project 2025(Grant No.GDSZSYKT2025244).
文摘With the rise of AI-assisted education,many instructors and engineers seek to deliver high-quality programming courses online.However,crafting effective programming lectures remains a challenge,particularly for instructors lacking pedagogical training or multilingual fluency.We present CourseAgent,a prompt-driven framework that leverages large language models(LLMs)to automatically generate Python tutorials,structured lecture scripts,and accompanying audio narrations.CourseAgent accepts raw code as input and transforms it into segmented,well-commented code blocks,adapting content to different difficulty levels and languages via prompt customization.Our system supports multilingual instruction(e.g.,Chinese,English),fine-grained control of pedagogical depth,and auto-generation of lecture videos.We evaluate the output generated by CourseAgent using real student feedback and feedback from in-service teachers,alongside automated assessments from LLMs.These evaluations demonstrate that the materials produced by CourseAgent are coherent,pedagogically sound,and comparable in quality to those created by experienced instructors.CourseAgent lowers the barrier to quality programming education and shows promise for scalable,personalized,and language-adaptive content generation.
基金supported by the National Natural Science Foundation of China(Grant No.12304379)the Natural Science Foundation of Liaoning Province(Grant No.2024BS-269)the Guangdong Basic and Applied Basic Research Foundation(Grant No.025A1515011117)。
文摘High-precision optical frequency measurement serves as a cornerstone of modern science and technology,enabling advancements in fields ranging from fundamental physics to quantum information technologies.Obtaining precise photon frequencies,especially in the ultraviolet or even extreme ultraviolet regimes,is a key goal in both light–matter interaction experiments and engineering applications.High-order harmonic generation(HHG)is an ideal light source for producing such photons.In this work,we propose an optical temporal interference model(OTIM)that establishes an analogy with multi-slit Fraunhofer diffraction(MSFD)to manipulate fine-frequency photon generation by exploiting the temporal coherence of HHG processes.Our model provides a unified physical framework for three distinct non-integer HHG generation schemes:single-pulse,shaped-pulse,and laser pulse train approaches,which correspond to single-MSFD-like,double-MSFD-like,and multi-MSFD-like processes,respectively.Arbitrary non-integer HHG photons can be obtained using our scheme.Our approach provides a new perspective for accurately measuring and controlling photon frequencies in fields such as frequency comb technology,interferometry,and atomic clocks.
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supported by the National Natural Science Foundation of China(81760037)Yunling Scholar Project of Yunnan Province(YNWR-YLXZ-2019-0005)+1 种基金Hunan Provincial Innovation Platform and Talent Program(2018SK4004)Hunan Provincial Natural Science Foundation(2019JJ80048).
文摘The occurrence of severe thalassemia,an inherited blood disorder that is either blood-transfusiondependent or fatal,can be mitigated through carrier screening.Here,we aim to evaluate the effectiveness and outcomes of pre-conceptional and early pregnancy screening initiatives for severe thalassemia prevention in a diverse population of 28,043 women.Using next-generation sequencing(NGS),we identify 4,226(15.07%)thalassemia carriers across 29 ethnic groups and categorize them into high-(0.75%),low-(25.86%),and unknown-risk(69.19%)groups based on their spouses'screening results.Post-screening follow-up reveals 59 fetuses with severe thalassemia exclusively in high-risk couples,underscoring the efficacy of risk classification.Among 25,053 live births over 6 months of age,two severe thalassemia infants were born to unknown-risk couples,which was attributed to incomplete screening and late NGS-based testing for a rare variant.Notably,64 rare variants are identified in 287 individuals,highlighting the genetic heterogeneity of thalassemia.We also observe that migrant flow significantly impacts carrier rates,with 93.90%of migrants to Chenzhou originating from high-prevalence regions in southern China.Our study demonstrates that NGS-based screening during pre-conception and early pregnancy is effective for severe thalassemia prevention,emphasizing the need for continuous screening efforts in areas with high and underestimated prevalence.
基金supported by the National Natural Science Foundation of China(Grant Nos.52171169 and 52101210)the National Key Research and Development Program of China(Grant No.2021YFB3501204)+3 种基金the State Key Laboratory for Advanced Metals and Materials(Grant No.2023-ZD01)USTB Concept Verification Funding Project(Grant No.GNYZ-2024-6)Fundamental Research Funds for the Central Universities(Grant No.FRF-TP-24-004A)USTB Research Center for International People-to-people Exchange in Science,Technology and Civilization(Grant Nos.2024KFZD001 and 2024KFYB004)。
文摘Thermomagnetic generation(TMG),a heat-to-electricity conversion technology based on the thermomagnetic effect,offers high reliability and broad adaptability to diverse heat sources.By exploiting the temperature-dependent magnetization of thermomagnetic materials,TMG converts thermal energy into electrical energy through cyclic changes in magnetic flux based on Faraday's law.The performance of TMG systems is largely governed by the intrinsic properties of the working materials and the design of device architecture.Ideal TMG materials exhibit sharp and reversible magnetization transitions near the operating temperature,low thermal hysteresis,and high thermal conductivity.Device configurations can be broadly categorized into active and passive systems:active TMG devices rely on controlled thermal cycling and optimized magnetic circuits for enhanced output,whereas passive devices utilize self-actuated mechanical motion to generate electricity.In this topical review,we provide a comprehensive overview of recent advances in TMG materials and device configurations.Furthermore,we discuss future development trends and offer perspectives on experimental strategies to advance this field.
基金supported by the National Natural Science Foundation of China(Grant No.42225104)CAS Project for Young Scientists in Basic Research(Grant No.YSBR-086).
文摘Urban populations are increasingly exposed to extreme heat due to climate change and rapid urbanization,heightening health risks in cities worldwide.Accurate heat exposure assessment is essential for public health planning and risk reduction.Most existing approaches rely on a single threshold temperature(e.g.,35℃of daily max temperature),applied uniformly to the entire population.However,this one-size-fits-all assumption overlooks substantial differences in heat sensitivity across population subgroups.In this study,we address this limitation by quantifying subgroup-specific temperature-mortality relationships and using corresponding minimum mortality temperatures(MMTs)to assess heat exposure.Results show that the population-wide MMT was 27.5℃,but it varied greatly across population subgroups.The elderly population(≥65)had an MMT of 24.6℃,much lower than the 28.6℃observed in younger individuals(<65).Females also exhibited a lower MMT that males(25℃versus 28.2℃).However,educational attainment did not significantly affect MMT.Using a uniform MMT resulted in substantial underestimation of heat exposure,ranging from 25.3%in 1990 to 13.9%in 2020,reflecting demographic shifts over time.Spatially,nearly half of the city experienced underestimated heat risk,especially in central and northeastern regions where heat-vulnerable populations are concentrated.These findings underscore the need for more nuanced heat exposure assessments that account for demographic and spatial variability,paving the way for targeted public health interventions to protect the most vulnerable urban populations.
基金supported by the DH2025-TN07-07 project conducted at the Thai Nguyen University of Information and Communication Technology,Thai Nguyen,Vietnam,with additional support from the AI in Software Engineering Lab.
文摘It remains difficult to automate the creation and validation of Unified Modeling Language(UML)dia-grams due to unstructured requirements,limited automated pipelines,and the lack of reliable evaluation methods.This study introduces a cohesive architecture that amalgamates requirement development,UML synthesis,and multimodal validation.First,LLaMA-3.2-1B-Instruct was utilized to generate user-focused requirements.Then,DeepSeek-R1-Distill-Qwen-32B applies its reasoning skills to transform these requirements into PlantUML code.Using this dual-LLM pipeline,we constructed a synthetic dataset of 11,997 UML diagrams spanning six major diagram families.Rendering analysis showed that 89.5%of the generated diagrams compile correctly,while invalid cases were detected automatically.To assess quality,we employed a multimodal scoring method that combines Qwen2.5-VL-3B,LLaMA-3.2-11B-Vision-Instruct and Aya-Vision-8B,with weights based on MMMU performance.A study with 94 experts revealed strong alignment between automatic and manual evaluations,yielding a Pearson correlation of r=0.82 and a Fleiss’Kappa of 0.78.This indicates a high degree of concordance between automated metrics and human judgment.Overall,the results demonstrated that our scoring system is effective and that the proposed generation pipeline produces UML diagrams that are both syntactically correct and semantically coherent.More broadly,the system provides a scalable and reproducible foundation for future work in AI-driven software modeling and multimodal verification.
基金supported by the Natural Science Foundation of China-Smart Grid Joint Fund of State Grid Corporation of China(No.U2066212)the Na-tional Natural Science Foundation of China(No.52207105)the Key Science and Technology Pro-jects of China Southern Power Grid Corporation(No.066600KK52222023).
文摘The annual compliance cycle of the carbon trading system allows generation companies(GenCos)to decouple the timing of carbon allowance purchases from their actual emissions.However,trading a large volume of allowances within a single day can significantly impact on carbon prices.Faced with uncertain future carbon and electricity prices,GenCos must address a challenging multistage stochastic optimization problem to coordinate their carbon trading strategies with daily power generation decisions.In this paper,a two-layered hybrid mathematical-deep reinforcement learning(DRL)optimization framework is proposed.The upper DRL layer tackles the stochastic,year-long carbon trading and allowance usage optimization problem,aiming for long-term optimality and providing guidance for short-term decisions in the lower layer.The lower mathematical optimization layer addresses the deterministic daily power generation schedule problem while enforcing strict technical constraints.To accelerate learning of the annual compliance cycle,a decision timeline transfer learning method is proposed,enabling the DRL agent to progressively refine its policy through sequentially training on monthly,weekly and daily decision environments.Case studies demonstrate that,with these methods,a GenCo can reduce emission costs and increase profits by effectively leveraging carbon price fluctuations within the compliance cycle.
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Supported by Natural Science Foundation of Hunan Province(No.2023JJ70017No.2025JJ50627)Peak Climbing Project of Optometry Hospital Affiliated to Wenzhou Medical University。
文摘AIM:To investigate the sex-specific correlation between systemic factors and retinal neurovascular alterations in individuals with type 1 diabetes mellitus(T1DM)who do not exhibit signs of diabetic retinopathy(DR).METHODS:A cohort participant without DR diagnosed with T1DM,underwent comprehensive ophthalmologic evaluation,optical coherence tomography angiography retinal structural and microvascular density analysis,and systemic parameter assessment.Multiple linear regression analysis was used to investigate the impact of systemic parameters on retinal alterations in distinct gender groups.RESULTS:A total of 182 individuals were included,consisting of 85 males(mean age 23.28±12.75y)and 97 females(mean age 22.98±13.68y).Males exhibited significantly greater thickness in both the internal retinal layer and the entire retina compared to females(P<0.01),whereas females had higher densities of deep retinal vessels and choroidal capillaries(P<0.05).Additionally,glycemic control was found to have a notable influence on retinal thickness in males(P<0.05),while insulin function had a more pronounced impact on retinal structure in females(P<0.01).Furthermore,a significant correlation was observed between thyroid function markers and retinal parameters in both male and female(P<0.05).CONCLUSION:Sex differences in alterations in retinal structure and microcirculation are observed in individuals with T1DM prior to the development of clinical DR,with a noted association between these changes and systemic parameters.
基金supported by the project of the National Natural Science Foundation of China entitled“Distribution and change characteristics of construction land on slope gradient in mountainous cities of southern China”(No.41961039)。
文摘China's requisition-compensation balance strategy has dramatically reshaped cropland spatial patterns,drawing multidisciplinary research attention.However,existing studies predominantly emphasize horizontal distribution,overlooking the significant influence of slope gradient on cropland spatial patterns.This paper proposes a slope location quotient(SLQ)index that reflects the relative advantage of cropland distribution and explores the slope grade difference of cropland spatial patterns in China at the county scale.The analysis adopts 30-m resolution digital elevation model with land cover data,taking 2672 counties with cropland ratio>1%as study units.The temporal scope covers 1990 and 2020,with slope gradients categorized into five grades:0°~2°,2°~6°,6°~15°,15°~25°,and 25°~90°.Results show that:1)The inverse correlation between cropland area and slope gradient remained stable throughout the study period,with the variation in cropland area frequency across slope grades being less than 1%.2)The spatial patterns of SLQ in 1990 and 2020 both transited stepwise with slope gradient,while≤2°and>6°slopes exhibited opposing patterns.3)The mean absolute variation of SLQ during 1990-2020 increased with slope gradient(R2=0.926,p<0.01).Particularly for slope grades>15°,the mean absolute variation reached 0.26(for 15°~25°)and 0.43(for 25°~90°),respectively,and displayed a distinct southward-increasing and northwarddecreasing pattern.This study offers novel slopegradient perspectives for analyzing cropland spatial patterns.To enhance cropland protection benefits,reversing the steep cropland SLQ surge in southern China is recommended.
