Salinity is one of the major abiotic stresses limiting chickpea(Cicer arietinum L.)productivity,particularly in arid and semi-arid regions where soil salinization is intensifying.Developing cost-effective and practica...Salinity is one of the major abiotic stresses limiting chickpea(Cicer arietinum L.)productivity,particularly in arid and semi-arid regions where soil salinization is intensifying.Developing cost-effective and practical strategies to enhance seedling establishment and early vigor under saline conditions is therefore essential.In this study,we compared two seed-priming agents-1 mM proline and 25 mM NaCl-under identical hydroponic conditions to elucidate tissue-specific responses to 25 mM NaCl stress.Proline priming significantly improved shoot length(by~23%),total chlorophyll content(by~19%),and ascorbate peroxidase(ASPOX)activity.In contrast,NaCl priming enhanced root biomass retention(by~38%)and peroxidase(POD)activity under salinity stress.Both priming treatments induced higher proline accumulation and antioxidant capacity,though with tissue-specific effects:proline favored aboveground resilience,while NaCl strengthened root ionic and oxidative balance.These findings highlight the complementary nature of proline and NaCl priming and support the concept of stress“memory,”whereby plants acquire enhanced readiness to cope with salinity.Integrating such priming strategies into chickpea cultivation could contribute to improved yield stability and sustainability in saline agroecosystems.展开更多
Harmonic mode-locking(HML)in soliton fiber lasers is crucial for generating high-repetition-rate pulse trains beyond the fundamental cavity frequency,enabling advanced applications in,for example,optical communication...Harmonic mode-locking(HML)in soliton fiber lasers is crucial for generating high-repetition-rate pulse trains beyond the fundamental cavity frequency,enabling advanced applications in,for example,optical communication and precision sensing.However,achieving HML in experiments is challenging,owing to its inherent instability and high sensitivity to laser parameters,resulting in complex and iterative adjustments.In this paper,a novel HML technique utilizing bidirectional adjustment of pump power is proposed,and it is experimentally demonstrated in an all-fiber hybrid mode-locked soliton laser.By first increasing the pump power to generate a soliton bunch with a certain number of pulses and then gradually decreasing it,HML can be achieved at an order corresponding to the number of pulses in the soliton bunch.Experimental results on the evolution of temporal pulse trains during bidirectional adjustment of the pump power enable a relationship to be established between pump power and soliton bunching with increasing pump power,and reveal the collapse of the soliton bunch and subsequent gradual uniform distribution of solitons into an HML state with decreasing pump power.Second-to sixth-order HML is successfully generated using the proposed technique,and an analysis of the results provides a deeper understanding of the observed pulse dynamics.展开更多
The operational Tropical Regional Atmospheric Model System(TRAMS)often underestimates initial typhoon intensity when using the global analysis field as the initial condition.The TRAMS tropical cyclone(TC)initializatio...The operational Tropical Regional Atmospheric Model System(TRAMS)often underestimates initial typhoon intensity when using the global analysis field as the initial condition.The TRAMS tropical cyclone(TC)initialization scheme,developed based on the incremental analysis updates(IAU)technique,effectively reduces initial bias.However,the original IAU-based TC initialization scheme only adjusts the wind field at the analysis moment,with other variables adjusted implicitly under the model's constraints according to a gradually inserted wind increment(named“univariate adjustment scheme”hereafter).The univariate adjustment scheme requires approximately 3 h to reach a dynamic equilibrium state,which constrains the assimilation of hourly TC observations and causes excessive dissipation of meaningful short-wave information in adjustment increments.To address this limitation,this study develops a multivariate adjustment IAU-based TC initialization scheme that incorporates gradient wind balance and hydrostatic balance as its largescale constraints.Numerical experiments with TC Hato(2017)demonstrate that the multivariate adjustment scheme reduces the IAU relaxation time to 1 h while marginally improving forecast skill.These findings are consistently replicated across 12 additional TC cases.The development of the IAU-based multivariate adjustment initialization scheme establishes a foundation for 4-D initialization using hourly TC observations.展开更多
Chinese abbreviations improve communicative efficiency by extracting key components from longer expressions.They are widely used in both daily communication and professional domains.However,existing abbreviation gener...Chinese abbreviations improve communicative efficiency by extracting key components from longer expressions.They are widely used in both daily communication and professional domains.However,existing abbreviation generation methods still face two major challenges.First,sequence-labeling-based approaches often neglect contextual meaning by making binary decisions at the character level,leading to abbreviations that fail to capture semantic completeness.Second,generation-basedmethods rely heavily on a single decoding process,which frequently produces correct abbreviations but ranks them lower due to inadequate semantic evaluation.To address these limitations,we propose a novel two-stage frameworkwithGeneration–Iterative Optimization forAbbreviation(GIOA).In the first stage,we design aChain-of-Thought prompting strategy and incorporate definitional and situational contexts to generate multiple abbreviation candidates.In the second stage,we introduce a Semantic Preservation Dynamic Adjustment mechanism that alternates between character-level importance estimation and semantic restoration to optimize candidate ranking.Experiments on two public benchmark datasets show that our method outperforms existing state-of-the-art approaches,achieving Hit@1 improvements of 15.15%and 13.01%,respectively,while maintaining consistent results in Hit@3.展开更多
In image analysis,high-precision semantic segmentation predominantly relies on supervised learning.Despite significant advancements driven by deep learning techniques,challenges such as class imbalance and dynamic per...In image analysis,high-precision semantic segmentation predominantly relies on supervised learning.Despite significant advancements driven by deep learning techniques,challenges such as class imbalance and dynamic performance evaluation persist.Traditional weighting methods,often based on pre-statistical class counting,tend to overemphasize certain classes while neglecting others,particularly rare sample categories.Approaches like focal loss and other rare-sample segmentation techniques introduce multiple hyperparameters that require manual tuning,leading to increased experimental costs due to their instability.This paper proposes a novel CAWASeg framework to address these limitations.Our approach leverages Grad-CAM technology to generate class activation maps,identifying key feature regions that the model focuses on during decision-making.We introduce a Comprehensive Segmentation Performance Score(CSPS)to dynamically evaluate model performance by converting these activation maps into pseudo mask and comparing them with Ground Truth.Additionally,we design two adaptive weights for each class:a Basic Weight(BW)and a Ratio Weight(RW),which the model adjusts during training based on real-time feedback.Extensive experiments on the COCO-Stuff,CityScapes,and ADE20k datasets demonstrate that our CAWASeg framework significantly improves segmentation performance for rare sample categories while enhancing overall segmentation accuracy.The proposed method offers a robust and efficient solution for addressing class imbalance in semantic segmentation tasks.展开更多
In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a ...In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a composition solution under their budget constraints.Existing studies typically evaluate satisfaction solely based on energy transmission capacity,while overlooking critical factors such as price and trustworthiness of the provider,leading to a mismatch between optimization outcomes and user needs.To address this gap,we construct a user satisfaction evaluation model for multi-user and multi-provider scenarios,systematically incorporating service price,transmission capacity,and trustworthiness into the satisfaction assessment framework.Furthermore,we propose a Budget-Aware Preference Adjustment Model that predicts users’baseline preference weights from historical data and dynamically adjusts them according to budget levels,thereby reflecting user preferences more realistically under varying budget constraints.In addition,to tackle the composition optimization problem,we develop a ReflectiveEvolutionary Large Language Model—Guided Ant Colony Optimization algorithm,which leverages the reflective evolution capability of large language models to iteratively generate and refine heuristic information that guides the search process.Experimental results demonstrate that the proposed framework effectively integrates personalized preferences with budget sensitivity,accurately predicts users’preferences,and significantly enhances their satisfaction under complex constraints.展开更多
Path planning for Unmanned Aerial Vehicles(UAVs)in complex environments presents several challenges.Traditional algorithms often struggle with the complexity of high-dimensional search spaces,leading to inefficiencies...Path planning for Unmanned Aerial Vehicles(UAVs)in complex environments presents several challenges.Traditional algorithms often struggle with the complexity of high-dimensional search spaces,leading to inefficiencies.Additionally,the non-linear nature of cost functions can cause algorithms to become trapped in local optima.Furthermore,there is often a lack of adequate consideration for real-world constraints,for example,due to the necessity for obstacle avoidance or because of the restrictions of flight safety.To address the aforementioned issues,this paper proposes a dynamic weighted spherical particle swarm optimization(DW-SPSO)algorithm.The algorithm adopts a dual Sigmoid-based adaptive weight adjustment mechanism for balancing global exploration and local exploitation,as well as a lens-based opposition learning one to improve search flexibility and solution diversity.Simulation experiments on real digital elevation models demonstrate that DW-SPSO significantly outperforms recent state-of-the-art particle swarm optimization(PSO)variants in terms of path safety,smoothness,and convergence speed.The performance superiority is statistically validated by the Wilcoxon signed-rank test.The results confirm the algorithm’s effectiveness in generating high-quality UAV paths under diverse threat conditions,offering a robust solution for autonomous navigation systems.展开更多
The world economy is now in a period of indepth adjustment.The intensification of geopolitical conflicts,a rise of trade protectionism,and reconfiguration of global supply chains have prompted all countries to re-exam...The world economy is now in a period of indepth adjustment.The intensification of geopolitical conflicts,a rise of trade protectionism,and reconfiguration of global supply chains have prompted all countries to re-examine their openness to trade amid rising uncertainties.Against this backdrop,China’s continuing commitment to promoting higherlevel opening up and building the Hainan Free Trade Port(Hainan FTP)has distinct contemporary significance and strategic value.展开更多
An optimized volt-ampere reactive(VAR)control framework is proposed for transmission-level power systems to simultaneously mitigate voltage deviations and active-power losses through coordinated control of large-scale...An optimized volt-ampere reactive(VAR)control framework is proposed for transmission-level power systems to simultaneously mitigate voltage deviations and active-power losses through coordinated control of large-scale wind/solar farms with shunt static var generators(SVGs).The model explicitly represents reactive-power regulation characteristics of doubly-fed wind turbines and PV inverters under real-time meteorological conditions,and quantifies SVG high-speed compensation capability,enabling seamless transition from localized VAR management to a globally coordinated strategy.An enhanced adaptive gain-sharing knowledge optimizer(AGSK-SD)integrates simulated annealing and diversity maintenance to autonomously tune voltage-control actions,renewable source reactive-power set-points,and SVG output.The algorithm adaptively modulates knowledge factors and ratios across search phases,performs SA-based fine-grained local exploitation,and periodically re-injects population diversity to prevent premature convergence.Comprehensive tests on IEEE 9-bus and 39-bus systems demonstrate AGSK-SD’s superiority over NSGA-II and MOPSO in hypervolume(HV),inverse generative distance(IGD),and spread metrics while maintaining acceptable computational burden.The method reduces network losses from 2.7191 to 2.15 MW(20.79%reduction)and from 15.1891 to 11.22 MW(26.16%reduction)in the 9-bus and 39-bus systems respectively.Simultaneously,the cumulative voltage-deviation index decreases from 0.0277 to 3.42×10^(−4) p.u.(98.77%reduction)in the 9-bus system,and from 0.0556 to 0.0107 p.u.(80.76%reduction)in the 39-bus system.These improvements demonstrate significant suppression of line losses and voltage fluctuations.Comparative analysis with traditional heuristic optimization algorithms confirms the superior performance of the proposed approach.展开更多
Solar radiation modification,a scheme aimed at mitigating rapid global warming triggered by anthropogenic greenhouse gas emissions,has been explored through the G1ext experiment under the Geoengineering Model Intercom...Solar radiation modification,a scheme aimed at mitigating rapid global warming triggered by anthropogenic greenhouse gas emissions,has been explored through the G1ext experiment under the Geoengineering Model Intercomparison Project(GeoMIP) framework,utilizing the Chinese Academy of Sciences Earth System Model version 2(CAS-ESM2.0).This paper briefly describes the basic configuration and experimental design of the CAS-ESM2.0 for G1ext,which involves a sudden reduction in solar irradiance to counterbalance the radiative forcing of an abrupt quadrupling of atmospheric CO_(2) concentration,running for 100 years.Preliminary results show that this model can reproduce well the compensatory effect of a uniform decrease in global solar radiation on the radiative forcing resulting from an abrupt quadrupling of CO_(2) concentration.Like other Earth system models,CAS-ESM2.0 reasonably captures variations in radiative adjustments,surface air temperature,and precipitation patterns,both globally and locally,under the G1ext scenario.The generated datasets have been released on the Earth System Grid Federation data server,providing insight into the potential efficacy and impact of solar geoengineering strategies.展开更多
The Yangtze River Delta(YRD)region has witnessed a consistent decrease in NO_(2),CO,and PM_(2.5) from 2016 to 2023.However,ozone has exhibited fluctuating patterns.Quantifying ozone contributions from emissions,both w...The Yangtze River Delta(YRD)region has witnessed a consistent decrease in NO_(2),CO,and PM_(2.5) from 2016 to 2023.However,ozone has exhibited fluctuating patterns.Quantifying ozone contributions from emissions,both within and outside the YRD,is essential for understanding city-cluster-scale ozone pollution(CCSOP).To address these concerns,a comprehensive approach combining Kolmogorov-Zurbenko filtering,Empirical Orthogonal Function,Absolute Principal Component Score,andMultiple Linear Regression methods(KZ-EOF-APCs-MLR)was employed to quantify the impacts of meteorological factors,local and non-local emission contributions of ozone(LECO and NECO).Emission changes were identified as the predominant factor shaping annual fluctuations in ambient ozone.Notably,during the previous andmiddle stages of the COVID-19 pandemic(from2017 to 2021),emissions reductions led to a marked decrease in YRD ozone levels(-7.01μg/m^(3)),with a pronounced rebound post-pandemic(2022 to 2023)(+8.04μg/m^(3)).Seasonally,the emissioninduced ozone exhibited fluctuating upward trend during autumn and winter,suggesting a transition of ozone pollution towards colder seasons.Spatially,high LECO concentrated in the eastern YRD(EYRD)across spring,autumn,and winter,becoming prominent in the central YRD(CYRD)during summer.During CCSOP,the CYRD exhibited the highest LECO and exceedance frequency(20.82μg/m^(3) and 45.27%).LECO explained a large portion of ozone variability during CCSOP,particularly in the EYRD,while NECO showed less explanatory power but consistently high contributions(148.05±15.52μg/m^(3)).These findings offer valuable insights for a deeper understanding of the evolving patterns of ozone pollution and the issue of CCSOP in the YRD.展开更多
In the context of post-stimulation shale gas wells,the terms“shut-in”and“flowback”refer to two critical phases that occur after hydraulic fracturing(fracking)has been completed.These stages play a crucial role in ...In the context of post-stimulation shale gas wells,the terms“shut-in”and“flowback”refer to two critical phases that occur after hydraulic fracturing(fracking)has been completed.These stages play a crucial role in determining both the well’s initial production performance and its long-term hydrocarbon recovery.By establishing a comprehensive big data analysis platform,the flowback dynamics of over 1000 shale gas wells were analyzed in this work,leading to the development of an index system for evaluating flowback production capacity.Additionally,a shut-in chart was created for wells with different types of post-stimulation fracture networks,providing a structured approach to optimizing production strategies.A dynamic analysis method for flowback was also developed,using daily pressure drop and artificial fracture conductivity as key indicators.This method offers a systematic and effective approach to managing the shut-in and flowback processes for gas wells.Field trials demonstrated significant improvements:the probability of sand production was reduced,gas breakthrough time was extended,artificial fracture conductivity was enhanced,and the average estimated ultimate recovery(EUR)per well increased.展开更多
To realize effective co-phasing adjustment in large-aperture sparse-aperture telescopes,a multichannel stripe tracking approach is employed,allowing simultaneous interferometric measurements of multiple optical paths ...To realize effective co-phasing adjustment in large-aperture sparse-aperture telescopes,a multichannel stripe tracking approach is employed,allowing simultaneous interferometric measurements of multiple optical paths and circumventing the need for pairwise measurements along the mirror boundaries in traditional interferometric methods.This approach enhances detection efficiency and reduces system complexity.Here,the principles of the multibeam interference process and construction of a co-phasing detection module based on direct optical fiber connections were analyzed using wavefront optics theory.Error analysis was conducted on the system surface obtained through multipath interference.Potential applications of the interferometric method were explored.Finally,the principle was verified by experiment,an interferometric fringe contrast better than 0.4 is achieved through flat field calibration and incoherent digital synthesis.The dynamic range of the measurement exceeds 10 times of the center wavelength of the working band(1550 nm).Moreover,a resolution better than one-tenth of the working center wavelength(1550 nm)was achieved.Simultaneous three-beam interference can be achieved,leading to a 50%improvement in detection efficiency.This method can effectively enhance the efficiency of sparse aperture telescope co-phasing,meeting the requirements for observations of 8-10 m telescopes.This study provides a technological foundation for observing distant and faint celestial objects.展开更多
In order to study the preferred skin color for printing images,two CMYK images from ISO 400 and one from iStock,including five skin color images of East Asian females was selected in this study.The images were adjuste...In order to study the preferred skin color for printing images,two CMYK images from ISO 400 and one from iStock,including five skin color images of East Asian females was selected in this study.The images were adjusted with the CMYK printing ink volume variation of the single,double and triple channels in the given 280%total ink limit conditions.A larger number of color vision normal observers were organized to carry out the color preference evaluation experiment,and the selected preferred skin colors were analyzed.The distribution range of the chromaticity values for skin color images were obtained and the results indicated that there are three regions for printing skin color preferences,and the observers have a memory preference for brighter,fairer skin colors in young female and a reddish skin colors in girl,which can provide the guidance for color adjustment of printed skin color images.展开更多
This study aimed to explore how core self-evaluations and gender influence interpersonal adjustment and depression risk.Participants were 1748 college students(female=59.73%,male=40.27%,mean age=18.71 years,SD=0.78 yea...This study aimed to explore how core self-evaluations and gender influence interpersonal adjustment and depression risk.Participants were 1748 college students(female=59.73%,male=40.27%,mean age=18.71 years,SD=0.78 years).The students completed the Interpersonal Adjustment Scale for College Students,Center for Epidemiological Studies Depression Scale,and Core Self-evaluation Scale.The results of Linear regression and mediated moderated effects modeling revealed that college students with higher interpersonal adjustment and core self-evaluation scores were at lower risk for depression.Core self-evaluation mediated the relationship between interpersonal adjustment and depression in college students for lower risk for depression.Gender moderated the relationship between interpersonal adjustment and core self-evaluation in college students for higher risk for depression in female students.From thesefindings,we conclude that interpersonal adjustment and core self-evaluation are significant for screening depression risk college students.Moreover,female students may benefit from targeted interventions aimed at their interpersonal adjustment for reducing their risk of depression.展开更多
Underwater Gliders(UGs)have emerged as vital instruments in marine research,offering distinct advantages including low operational costs,extended range capabilities,and superior durability.Traditional UGs,however,face...Underwater Gliders(UGs)have emerged as vital instruments in marine research,offering distinct advantages including low operational costs,extended range capabilities,and superior durability.Traditional UGs,however,face limitations due to their substantial size,weight,cost,and deployment complexity.Moreover,the conventional oil pump method for buoyancy adjustment exhibits slow response times,resulting in increased unsteady gliding depth ratios.These constraints limit their application in shallow water environments such as ports,coastal waters,and inland water bodies.This paper presents the TL-200,a small-sized underwater glider that incorporates an integrated buoyancy-driven and attitude adjustment mechanism.Through the implementation of an innovative buoyancy drive unit,the TL-200 achieves enhanced buoyancy regulation response while maintaining a simplified structure compared to conventional gliders.A dynamic model for the TL-200 was developed and validated through comparative analysis of numerical results and experimental data.Utilizing this dynamic model,motion simulations were conducted to examine the influence of metacentric height on motion parameters.Additionally,the study evaluated the gliding efficiency and energy consumption of the TL-200 under varying buoyancy adjustments.The findings demonstrate the effectiveness of this small-sized underwater glider's integrated buoyancy-driven and attitude adjustment mechanism.展开更多
Through the analysis of the actual situation and process of painting industrial steel components in Hechang Company,we have modified the mixing ratio of paint,thinner,and curing agent.Additionally,we have effectively ...Through the analysis of the actual situation and process of painting industrial steel components in Hechang Company,we have modified the mixing ratio of paint,thinner,and curing agent.Additionally,we have effectively adjusted the drying time of various paint types under different seasons and temperatures.Eventually,a painting solution suitable for our company has been developed.According to this process,the painting quality has been significantly improved,costs have been saved,the labor intensity has been reduced,and production efficiency has been remarkably enhanced.展开更多
BACKGROUND Ovarian cancer patients often face complex treatment processes and psychological challenges,with different treatment modalities potentially affecting patients’psychological adjustment abilities.AIM To expl...BACKGROUND Ovarian cancer patients often face complex treatment processes and psychological challenges,with different treatment modalities potentially affecting patients’psychological adjustment abilities.AIM To explore the differences in psychological adjustment patterns among ovarian cancer patients receiving surgery,chemotherapy,targeted therapy,and combined therapy,and to analyze their relationship with clinical outcomes.METHODS A retrospective analysis was conducted on the clinical data of 286 ovarian cancer patients who received different treatment modalities from January 2020 to December 2023.Patients were divided into surgery group(n=78),chemotherapy group(n=65),targeted therapy group(n=61),and combined therapy group(n=82).The Self-Rating Anxiety Scale,Self-Rating Depression Scale,and Psychological Adjustment to Cancer Scale were used to assess psychological status,while quality of life,treatment adherence,and two-year survival rate data were collected.Some patients(n=76)received systematic psychological intervention,and the intervention effects were evaluated.RESULTS Patients in the combined therapy group had significantly higher Self-Rating Anxiety Scale(56.3±7.2)and Self-Rating Depression Scale(58.4±6.9)scores than other groups,with the highest incidence of anxiety(58.5%)and depression(62.2%);the targeted therapy group scored highest in the positive coping dimension(28.5±3.6)and had the lowest incidence of anxiety and depression(29.5%/31.1%).Logistic regression analysis showed that positive coping(odds ratio=2.86,95%confidence interval:1.75-4.68)and utilization of social support(odds ratio=2.13,95%confidence interval:1.42-3.56)were protective factors for good treatment adherence.Longitudinal assessment showed that although all patients experienced increased anxiety and depression symptoms at 3 months of treatment,the targeted therapy group and surgery group showed significant improvement at 6 months(P<0.05),while the combined therapy group showed no significant improvement.Psychological intervention effectively improved patients’treatment adherence(by 22.7%)and quality of life(by 15.6 points),with the best effect in the combined therapy group(anxiety incidence decreased by 30.5%,P<0.001).CONCLUSION Different treatment modalities significantly affect the psychological adjustment abilities of ovarian cancer patients,with combined therapy patients facing greater psychological challenges,while targeted therapy patients exhibit healthier psychological adjustment patterns.展开更多
Photomechanics is a crucial branch of solid mechanics.The localization of point targets constitutes a fundamental problem in optical experimental mechanics,with extensive applications in various missions of unmanned a...Photomechanics is a crucial branch of solid mechanics.The localization of point targets constitutes a fundamental problem in optical experimental mechanics,with extensive applications in various missions of unmanned aerial vehicles.Localizing moving targets is crucial for analyzing their motion characteristics and dynamic properties.Reconstructing the trajectories of points from asynchronous cameras is a significant challenge.It encompasses two coupled sub-problems:Trajectory reconstruction and camera synchronization.Present methods typically address only one of these sub-problems individually.This paper proposes a 3D trajectory reconstruction method for point targets based on asynchronous cameras,simultaneously solving both sub-problems.Firstly,we extend the trajectory intersection method to asynchronous cameras to resolve the limitation of traditional triangulation that requires camera synchronization.Secondly,we develop models for camera temporal information and target motion,based on imaging mechanisms and target dynamics characteristics.The parameters are optimized simultaneously to achieve trajectory reconstruction without accurate time parameters.Thirdly,we optimize the camera rotations alongside the camera time information and target motion parameters,using tighter and more continuous constraints on moving points.The reconstruction accuracy is significantly improved,especially when the camera rotations are inaccurate.Finally,the simulated and real-world experimental results demonstrate the feasibility and accuracy of the proposed method.The real-world results indicate that the proposed algorithm achieved a localization error of 112.95 m at an observation distance range of 15-20 km.展开更多
China’s endeavors to mitigate recurrent crop residue burning(CRB)and improve air quality have yielded positive results owing to recent pollution prevention policies.Nonetheless,persistent challenges remain,particular...China’s endeavors to mitigate recurrent crop residue burning(CRB)and improve air quality have yielded positive results owing to recent pollution prevention policies.Nonetheless,persistent challenges remain,particularly in the Northeast China(NEC),where low temperature complicates crop residue management.Here,we examined the effects of cropping pattern adjustment on variations of CRB patterns in NEC during 2001-2021,utilizing the Moderate-resolution Imaging Spectroradiometer(MODIS)burned area dataset,the Visible Infrared Imaging Radiometer Suite(VIIRS)active fire dataset,and the high-accuracy crop planting area maps.Our results revealed an overall upward trend of 805.96 km^(2)/yr in NEC CRB from 2001 to 2021.The corn CRB area accounted for more than 50%of the total CRB area in each CRB-intensive year(2013-2021),and the increasing corn CRB generally aligns with the growing corn cultivation fields.A seasonal shift in CRB was found around 2017,with intensive CRB activities transitioning from both autumn and spring to primarily spring,particularly in the Songnen Plain and Sanjiang Plain.The changing trend of PM2.5 concentration aligned spatially with the shift.Moreover,the CRBs in spring of 2020 and 2021 were more severe than the major burning seasons in previous years,likely due to the disruptions during COVID-19 lockdowns.In certain years,the explanatory power of spring CRB on PM2.5 concentration was comparable to that of other natural factors,such as precipitation.This study underscores the critical need for sustained and region-specific strategies to tackle the challenges posed by CRBs.展开更多
文摘Salinity is one of the major abiotic stresses limiting chickpea(Cicer arietinum L.)productivity,particularly in arid and semi-arid regions where soil salinization is intensifying.Developing cost-effective and practical strategies to enhance seedling establishment and early vigor under saline conditions is therefore essential.In this study,we compared two seed-priming agents-1 mM proline and 25 mM NaCl-under identical hydroponic conditions to elucidate tissue-specific responses to 25 mM NaCl stress.Proline priming significantly improved shoot length(by~23%),total chlorophyll content(by~19%),and ascorbate peroxidase(ASPOX)activity.In contrast,NaCl priming enhanced root biomass retention(by~38%)and peroxidase(POD)activity under salinity stress.Both priming treatments induced higher proline accumulation and antioxidant capacity,though with tissue-specific effects:proline favored aboveground resilience,while NaCl strengthened root ionic and oxidative balance.These findings highlight the complementary nature of proline and NaCl priming and support the concept of stress“memory,”whereby plants acquire enhanced readiness to cope with salinity.Integrating such priming strategies into chickpea cultivation could contribute to improved yield stability and sustainability in saline agroecosystems.
基金supported by the National Natural Science Foundation of China(Grant No.52475574).
文摘Harmonic mode-locking(HML)in soliton fiber lasers is crucial for generating high-repetition-rate pulse trains beyond the fundamental cavity frequency,enabling advanced applications in,for example,optical communication and precision sensing.However,achieving HML in experiments is challenging,owing to its inherent instability and high sensitivity to laser parameters,resulting in complex and iterative adjustments.In this paper,a novel HML technique utilizing bidirectional adjustment of pump power is proposed,and it is experimentally demonstrated in an all-fiber hybrid mode-locked soliton laser.By first increasing the pump power to generate a soliton bunch with a certain number of pulses and then gradually decreasing it,HML can be achieved at an order corresponding to the number of pulses in the soliton bunch.Experimental results on the evolution of temporal pulse trains during bidirectional adjustment of the pump power enable a relationship to be established between pump power and soliton bunching with increasing pump power,and reveal the collapse of the soliton bunch and subsequent gradual uniform distribution of solitons into an HML state with decreasing pump power.Second-to sixth-order HML is successfully generated using the proposed technique,and an analysis of the results provides a deeper understanding of the observed pulse dynamics.
基金supported by the National University of Defense Technology(NUDT)Research Initiation Funding for High-Level Scientific and Technological Innovative Talents(202402-YJRC-LJ-001)the National Natural Science Foundation of China(Grant No.U2142213)+1 种基金the Basic and Applied Basic Research Foundation of Guangdong Province(Grants 2025A1515011835,2022A1515011870)the National Natural Science Foundation of China(Grant No.42305167)。
文摘The operational Tropical Regional Atmospheric Model System(TRAMS)often underestimates initial typhoon intensity when using the global analysis field as the initial condition.The TRAMS tropical cyclone(TC)initialization scheme,developed based on the incremental analysis updates(IAU)technique,effectively reduces initial bias.However,the original IAU-based TC initialization scheme only adjusts the wind field at the analysis moment,with other variables adjusted implicitly under the model's constraints according to a gradually inserted wind increment(named“univariate adjustment scheme”hereafter).The univariate adjustment scheme requires approximately 3 h to reach a dynamic equilibrium state,which constrains the assimilation of hourly TC observations and causes excessive dissipation of meaningful short-wave information in adjustment increments.To address this limitation,this study develops a multivariate adjustment IAU-based TC initialization scheme that incorporates gradient wind balance and hydrostatic balance as its largescale constraints.Numerical experiments with TC Hato(2017)demonstrate that the multivariate adjustment scheme reduces the IAU relaxation time to 1 h while marginally improving forecast skill.These findings are consistently replicated across 12 additional TC cases.The development of the IAU-based multivariate adjustment initialization scheme establishes a foundation for 4-D initialization using hourly TC observations.
基金supported by the National Key Research and Development Program of China(2020AAA0109300)the Shanghai Collaborative Innovation Center of data intelligence technology(No.0232-A1-8900-24-13).
文摘Chinese abbreviations improve communicative efficiency by extracting key components from longer expressions.They are widely used in both daily communication and professional domains.However,existing abbreviation generation methods still face two major challenges.First,sequence-labeling-based approaches often neglect contextual meaning by making binary decisions at the character level,leading to abbreviations that fail to capture semantic completeness.Second,generation-basedmethods rely heavily on a single decoding process,which frequently produces correct abbreviations but ranks them lower due to inadequate semantic evaluation.To address these limitations,we propose a novel two-stage frameworkwithGeneration–Iterative Optimization forAbbreviation(GIOA).In the first stage,we design aChain-of-Thought prompting strategy and incorporate definitional and situational contexts to generate multiple abbreviation candidates.In the second stage,we introduce a Semantic Preservation Dynamic Adjustment mechanism that alternates between character-level importance estimation and semantic restoration to optimize candidate ranking.Experiments on two public benchmark datasets show that our method outperforms existing state-of-the-art approaches,achieving Hit@1 improvements of 15.15%and 13.01%,respectively,while maintaining consistent results in Hit@3.
基金supported by the Funds for Central-Guided Local Science and Technology Development(Grant No.202407AC110005)Key Technologies for the Construction of a Whole-Process Intelligent Service System for Neuroendocrine Neoplasm.Supported by 2023 Opening Research Fund of Yunnan Key Laboratory of Digital Communications(YNJTKFB-20230686,YNKLDC-KFKT-202304).
文摘In image analysis,high-precision semantic segmentation predominantly relies on supervised learning.Despite significant advancements driven by deep learning techniques,challenges such as class imbalance and dynamic performance evaluation persist.Traditional weighting methods,often based on pre-statistical class counting,tend to overemphasize certain classes while neglecting others,particularly rare sample categories.Approaches like focal loss and other rare-sample segmentation techniques introduce multiple hyperparameters that require manual tuning,leading to increased experimental costs due to their instability.This paper proposes a novel CAWASeg framework to address these limitations.Our approach leverages Grad-CAM technology to generate class activation maps,identifying key feature regions that the model focuses on during decision-making.We introduce a Comprehensive Segmentation Performance Score(CSPS)to dynamically evaluate model performance by converting these activation maps into pseudo mask and comparing them with Ground Truth.Additionally,we design two adaptive weights for each class:a Basic Weight(BW)and a Ratio Weight(RW),which the model adjusts during training based on real-time feedback.Extensive experiments on the COCO-Stuff,CityScapes,and ADE20k datasets demonstrate that our CAWASeg framework significantly improves segmentation performance for rare sample categories while enhancing overall segmentation accuracy.The proposed method offers a robust and efficient solution for addressing class imbalance in semantic segmentation tasks.
基金supported by the National Natural Science Foundation of China under Grant 62472264the Natural Science Distinguished Youth Foundation of Shandong Province under Grant ZR2025QA13。
文摘In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a composition solution under their budget constraints.Existing studies typically evaluate satisfaction solely based on energy transmission capacity,while overlooking critical factors such as price and trustworthiness of the provider,leading to a mismatch between optimization outcomes and user needs.To address this gap,we construct a user satisfaction evaluation model for multi-user and multi-provider scenarios,systematically incorporating service price,transmission capacity,and trustworthiness into the satisfaction assessment framework.Furthermore,we propose a Budget-Aware Preference Adjustment Model that predicts users’baseline preference weights from historical data and dynamically adjusts them according to budget levels,thereby reflecting user preferences more realistically under varying budget constraints.In addition,to tackle the composition optimization problem,we develop a ReflectiveEvolutionary Large Language Model—Guided Ant Colony Optimization algorithm,which leverages the reflective evolution capability of large language models to iteratively generate and refine heuristic information that guides the search process.Experimental results demonstrate that the proposed framework effectively integrates personalized preferences with budget sensitivity,accurately predicts users’preferences,and significantly enhances their satisfaction under complex constraints.
基金supported by the National Natural Science Foundation of China(Grant No.62106092)the Natural Science Foundation of Fujian Province(Grant Nos.2024J01822,2025J01981)the Natural Science Foundation of Zhangzhou City(Grant No.ZZ2024J28).
文摘Path planning for Unmanned Aerial Vehicles(UAVs)in complex environments presents several challenges.Traditional algorithms often struggle with the complexity of high-dimensional search spaces,leading to inefficiencies.Additionally,the non-linear nature of cost functions can cause algorithms to become trapped in local optima.Furthermore,there is often a lack of adequate consideration for real-world constraints,for example,due to the necessity for obstacle avoidance or because of the restrictions of flight safety.To address the aforementioned issues,this paper proposes a dynamic weighted spherical particle swarm optimization(DW-SPSO)algorithm.The algorithm adopts a dual Sigmoid-based adaptive weight adjustment mechanism for balancing global exploration and local exploitation,as well as a lens-based opposition learning one to improve search flexibility and solution diversity.Simulation experiments on real digital elevation models demonstrate that DW-SPSO significantly outperforms recent state-of-the-art particle swarm optimization(PSO)variants in terms of path safety,smoothness,and convergence speed.The performance superiority is statistically validated by the Wilcoxon signed-rank test.The results confirm the algorithm’s effectiveness in generating high-quality UAV paths under diverse threat conditions,offering a robust solution for autonomous navigation systems.
文摘The world economy is now in a period of indepth adjustment.The intensification of geopolitical conflicts,a rise of trade protectionism,and reconfiguration of global supply chains have prompted all countries to re-examine their openness to trade amid rising uncertainties.Against this backdrop,China’s continuing commitment to promoting higherlevel opening up and building the Hainan Free Trade Port(Hainan FTP)has distinct contemporary significance and strategic value.
基金supported by Yunnan Power Grid Co.,Ltd.Science and Technology Project:Research and application of key technologies for graphical-based power grid accident reconstruction and simulation(YNKJXM20240333).
文摘An optimized volt-ampere reactive(VAR)control framework is proposed for transmission-level power systems to simultaneously mitigate voltage deviations and active-power losses through coordinated control of large-scale wind/solar farms with shunt static var generators(SVGs).The model explicitly represents reactive-power regulation characteristics of doubly-fed wind turbines and PV inverters under real-time meteorological conditions,and quantifies SVG high-speed compensation capability,enabling seamless transition from localized VAR management to a globally coordinated strategy.An enhanced adaptive gain-sharing knowledge optimizer(AGSK-SD)integrates simulated annealing and diversity maintenance to autonomously tune voltage-control actions,renewable source reactive-power set-points,and SVG output.The algorithm adaptively modulates knowledge factors and ratios across search phases,performs SA-based fine-grained local exploitation,and periodically re-injects population diversity to prevent premature convergence.Comprehensive tests on IEEE 9-bus and 39-bus systems demonstrate AGSK-SD’s superiority over NSGA-II and MOPSO in hypervolume(HV),inverse generative distance(IGD),and spread metrics while maintaining acceptable computational burden.The method reduces network losses from 2.7191 to 2.15 MW(20.79%reduction)and from 15.1891 to 11.22 MW(26.16%reduction)in the 9-bus and 39-bus systems respectively.Simultaneously,the cumulative voltage-deviation index decreases from 0.0277 to 3.42×10^(−4) p.u.(98.77%reduction)in the 9-bus system,and from 0.0556 to 0.0107 p.u.(80.76%reduction)in the 39-bus system.These improvements demonstrate significant suppression of line losses and voltage fluctuations.Comparative analysis with traditional heuristic optimization algorithms confirms the superior performance of the proposed approach.
基金supported by the National Natural Science Foundation of China(Grant No.41875126)the National Key Scientific and Technological Infrastructure project “Earth System Numerical Simulation Facility”(EarthLab)。
文摘Solar radiation modification,a scheme aimed at mitigating rapid global warming triggered by anthropogenic greenhouse gas emissions,has been explored through the G1ext experiment under the Geoengineering Model Intercomparison Project(GeoMIP) framework,utilizing the Chinese Academy of Sciences Earth System Model version 2(CAS-ESM2.0).This paper briefly describes the basic configuration and experimental design of the CAS-ESM2.0 for G1ext,which involves a sudden reduction in solar irradiance to counterbalance the radiative forcing of an abrupt quadrupling of atmospheric CO_(2) concentration,running for 100 years.Preliminary results show that this model can reproduce well the compensatory effect of a uniform decrease in global solar radiation on the radiative forcing resulting from an abrupt quadrupling of CO_(2) concentration.Like other Earth system models,CAS-ESM2.0 reasonably captures variations in radiative adjustments,surface air temperature,and precipitation patterns,both globally and locally,under the G1ext scenario.The generated datasets have been released on the Earth System Grid Federation data server,providing insight into the potential efficacy and impact of solar geoengineering strategies.
基金supported by the National Natural Science Foundation of China(Nos.U19A2044,42105132,42030609,41975037)the National Key Research and Development Programof China(No.2022YFC3700303).
文摘The Yangtze River Delta(YRD)region has witnessed a consistent decrease in NO_(2),CO,and PM_(2.5) from 2016 to 2023.However,ozone has exhibited fluctuating patterns.Quantifying ozone contributions from emissions,both within and outside the YRD,is essential for understanding city-cluster-scale ozone pollution(CCSOP).To address these concerns,a comprehensive approach combining Kolmogorov-Zurbenko filtering,Empirical Orthogonal Function,Absolute Principal Component Score,andMultiple Linear Regression methods(KZ-EOF-APCs-MLR)was employed to quantify the impacts of meteorological factors,local and non-local emission contributions of ozone(LECO and NECO).Emission changes were identified as the predominant factor shaping annual fluctuations in ambient ozone.Notably,during the previous andmiddle stages of the COVID-19 pandemic(from2017 to 2021),emissions reductions led to a marked decrease in YRD ozone levels(-7.01μg/m^(3)),with a pronounced rebound post-pandemic(2022 to 2023)(+8.04μg/m^(3)).Seasonally,the emissioninduced ozone exhibited fluctuating upward trend during autumn and winter,suggesting a transition of ozone pollution towards colder seasons.Spatially,high LECO concentrated in the eastern YRD(EYRD)across spring,autumn,and winter,becoming prominent in the central YRD(CYRD)during summer.During CCSOP,the CYRD exhibited the highest LECO and exceedance frequency(20.82μg/m^(3) and 45.27%).LECO explained a large portion of ozone variability during CCSOP,particularly in the EYRD,while NECO showed less explanatory power but consistently high contributions(148.05±15.52μg/m^(3)).These findings offer valuable insights for a deeper understanding of the evolving patterns of ozone pollution and the issue of CCSOP in the YRD.
基金PetroChina Research Applied Science and Technology Project,“Shale Gas Scale Increase Production and Exploration andDevelopment Technology-Research and Application of Key Technology of Deep Shale Gas Scale Production”(No.2023ZZ21YJ01).
文摘In the context of post-stimulation shale gas wells,the terms“shut-in”and“flowback”refer to two critical phases that occur after hydraulic fracturing(fracking)has been completed.These stages play a crucial role in determining both the well’s initial production performance and its long-term hydrocarbon recovery.By establishing a comprehensive big data analysis platform,the flowback dynamics of over 1000 shale gas wells were analyzed in this work,leading to the development of an index system for evaluating flowback production capacity.Additionally,a shut-in chart was created for wells with different types of post-stimulation fracture networks,providing a structured approach to optimizing production strategies.A dynamic analysis method for flowback was also developed,using daily pressure drop and artificial fracture conductivity as key indicators.This method offers a systematic and effective approach to managing the shut-in and flowback processes for gas wells.Field trials demonstrated significant improvements:the probability of sand production was reduced,gas breakthrough time was extended,artificial fracture conductivity was enhanced,and the average estimated ultimate recovery(EUR)per well increased.
文摘To realize effective co-phasing adjustment in large-aperture sparse-aperture telescopes,a multichannel stripe tracking approach is employed,allowing simultaneous interferometric measurements of multiple optical paths and circumventing the need for pairwise measurements along the mirror boundaries in traditional interferometric methods.This approach enhances detection efficiency and reduces system complexity.Here,the principles of the multibeam interference process and construction of a co-phasing detection module based on direct optical fiber connections were analyzed using wavefront optics theory.Error analysis was conducted on the system surface obtained through multipath interference.Potential applications of the interferometric method were explored.Finally,the principle was verified by experiment,an interferometric fringe contrast better than 0.4 is achieved through flat field calibration and incoherent digital synthesis.The dynamic range of the measurement exceeds 10 times of the center wavelength of the working band(1550 nm).Moreover,a resolution better than one-tenth of the working center wavelength(1550 nm)was achieved.Simultaneous three-beam interference can be achieved,leading to a 50%improvement in detection efficiency.This method can effectively enhance the efficiency of sparse aperture telescope co-phasing,meeting the requirements for observations of 8-10 m telescopes.This study provides a technological foundation for observing distant and faint celestial objects.
文摘In order to study the preferred skin color for printing images,two CMYK images from ISO 400 and one from iStock,including five skin color images of East Asian females was selected in this study.The images were adjusted with the CMYK printing ink volume variation of the single,double and triple channels in the given 280%total ink limit conditions.A larger number of color vision normal observers were organized to carry out the color preference evaluation experiment,and the selected preferred skin colors were analyzed.The distribution range of the chromaticity values for skin color images were obtained and the results indicated that there are three regions for printing skin color preferences,and the observers have a memory preference for brighter,fairer skin colors in young female and a reddish skin colors in girl,which can provide the guidance for color adjustment of printed skin color images.
基金supported by the Education Working Committee of the Xinjiang Uygur Autonomous Region Party Committee(grant number 2023GZYB10).
文摘This study aimed to explore how core self-evaluations and gender influence interpersonal adjustment and depression risk.Participants were 1748 college students(female=59.73%,male=40.27%,mean age=18.71 years,SD=0.78 years).The students completed the Interpersonal Adjustment Scale for College Students,Center for Epidemiological Studies Depression Scale,and Core Self-evaluation Scale.The results of Linear regression and mediated moderated effects modeling revealed that college students with higher interpersonal adjustment and core self-evaluation scores were at lower risk for depression.Core self-evaluation mediated the relationship between interpersonal adjustment and depression in college students for lower risk for depression.Gender moderated the relationship between interpersonal adjustment and core self-evaluation in college students for higher risk for depression in female students.From thesefindings,we conclude that interpersonal adjustment and core self-evaluation are significant for screening depression risk college students.Moreover,female students may benefit from targeted interventions aimed at their interpersonal adjustment for reducing their risk of depression.
基金financially supported by the National Key Research and Development Program of China(Grant No.2023YFC3008001)the National Natural Science Foundation of China(Grant No.52371357)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515240035)。
文摘Underwater Gliders(UGs)have emerged as vital instruments in marine research,offering distinct advantages including low operational costs,extended range capabilities,and superior durability.Traditional UGs,however,face limitations due to their substantial size,weight,cost,and deployment complexity.Moreover,the conventional oil pump method for buoyancy adjustment exhibits slow response times,resulting in increased unsteady gliding depth ratios.These constraints limit their application in shallow water environments such as ports,coastal waters,and inland water bodies.This paper presents the TL-200,a small-sized underwater glider that incorporates an integrated buoyancy-driven and attitude adjustment mechanism.Through the implementation of an innovative buoyancy drive unit,the TL-200 achieves enhanced buoyancy regulation response while maintaining a simplified structure compared to conventional gliders.A dynamic model for the TL-200 was developed and validated through comparative analysis of numerical results and experimental data.Utilizing this dynamic model,motion simulations were conducted to examine the influence of metacentric height on motion parameters.Additionally,the study evaluated the gliding efficiency and energy consumption of the TL-200 under varying buoyancy adjustments.The findings demonstrate the effectiveness of this small-sized underwater glider's integrated buoyancy-driven and attitude adjustment mechanism.
文摘Through the analysis of the actual situation and process of painting industrial steel components in Hechang Company,we have modified the mixing ratio of paint,thinner,and curing agent.Additionally,we have effectively adjusted the drying time of various paint types under different seasons and temperatures.Eventually,a painting solution suitable for our company has been developed.According to this process,the painting quality has been significantly improved,costs have been saved,the labor intensity has been reduced,and production efficiency has been remarkably enhanced.
文摘BACKGROUND Ovarian cancer patients often face complex treatment processes and psychological challenges,with different treatment modalities potentially affecting patients’psychological adjustment abilities.AIM To explore the differences in psychological adjustment patterns among ovarian cancer patients receiving surgery,chemotherapy,targeted therapy,and combined therapy,and to analyze their relationship with clinical outcomes.METHODS A retrospective analysis was conducted on the clinical data of 286 ovarian cancer patients who received different treatment modalities from January 2020 to December 2023.Patients were divided into surgery group(n=78),chemotherapy group(n=65),targeted therapy group(n=61),and combined therapy group(n=82).The Self-Rating Anxiety Scale,Self-Rating Depression Scale,and Psychological Adjustment to Cancer Scale were used to assess psychological status,while quality of life,treatment adherence,and two-year survival rate data were collected.Some patients(n=76)received systematic psychological intervention,and the intervention effects were evaluated.RESULTS Patients in the combined therapy group had significantly higher Self-Rating Anxiety Scale(56.3±7.2)and Self-Rating Depression Scale(58.4±6.9)scores than other groups,with the highest incidence of anxiety(58.5%)and depression(62.2%);the targeted therapy group scored highest in the positive coping dimension(28.5±3.6)and had the lowest incidence of anxiety and depression(29.5%/31.1%).Logistic regression analysis showed that positive coping(odds ratio=2.86,95%confidence interval:1.75-4.68)and utilization of social support(odds ratio=2.13,95%confidence interval:1.42-3.56)were protective factors for good treatment adherence.Longitudinal assessment showed that although all patients experienced increased anxiety and depression symptoms at 3 months of treatment,the targeted therapy group and surgery group showed significant improvement at 6 months(P<0.05),while the combined therapy group showed no significant improvement.Psychological intervention effectively improved patients’treatment adherence(by 22.7%)and quality of life(by 15.6 points),with the best effect in the combined therapy group(anxiety incidence decreased by 30.5%,P<0.001).CONCLUSION Different treatment modalities significantly affect the psychological adjustment abilities of ovarian cancer patients,with combined therapy patients facing greater psychological challenges,while targeted therapy patients exhibit healthier psychological adjustment patterns.
基金supported by the Hunan Provin〓〓cial Natural Science Foundation for Excellent Young Scholars(Grant No.2023JJ20045)the National Natural Science Foundation of China(Grant No.12372189)。
文摘Photomechanics is a crucial branch of solid mechanics.The localization of point targets constitutes a fundamental problem in optical experimental mechanics,with extensive applications in various missions of unmanned aerial vehicles.Localizing moving targets is crucial for analyzing their motion characteristics and dynamic properties.Reconstructing the trajectories of points from asynchronous cameras is a significant challenge.It encompasses two coupled sub-problems:Trajectory reconstruction and camera synchronization.Present methods typically address only one of these sub-problems individually.This paper proposes a 3D trajectory reconstruction method for point targets based on asynchronous cameras,simultaneously solving both sub-problems.Firstly,we extend the trajectory intersection method to asynchronous cameras to resolve the limitation of traditional triangulation that requires camera synchronization.Secondly,we develop models for camera temporal information and target motion,based on imaging mechanisms and target dynamics characteristics.The parameters are optimized simultaneously to achieve trajectory reconstruction without accurate time parameters.Thirdly,we optimize the camera rotations alongside the camera time information and target motion parameters,using tighter and more continuous constraints on moving points.The reconstruction accuracy is significantly improved,especially when the camera rotations are inaccurate.Finally,the simulated and real-world experimental results demonstrate the feasibility and accuracy of the proposed method.The real-world results indicate that the proposed algorithm achieved a localization error of 112.95 m at an observation distance range of 15-20 km.
基金supported by the National Key Research and Devel-opment Program of China(Grant No.2023YFD1500200)the funding project of Northeast Geological S&T Innovation Center of China Geologi-cal Survey(Grant No.QCJJ2022-9)+3 种基金the Strategic Priority Research Pro-gram of the Chinese Academy of Sciences(Grant No.XDA28060100)the Youth Interdisciplinary Team Project of the Chinese Academy of Sciences(JCTD-2021-04)the Informatization Plan of the Chinese Academy of Sciences(Grant No.CAS-WX2021PY-0109)the National Natural Science Foundation of China(Grants No.41971078,42271375,72221002,42001378).
文摘China’s endeavors to mitigate recurrent crop residue burning(CRB)and improve air quality have yielded positive results owing to recent pollution prevention policies.Nonetheless,persistent challenges remain,particularly in the Northeast China(NEC),where low temperature complicates crop residue management.Here,we examined the effects of cropping pattern adjustment on variations of CRB patterns in NEC during 2001-2021,utilizing the Moderate-resolution Imaging Spectroradiometer(MODIS)burned area dataset,the Visible Infrared Imaging Radiometer Suite(VIIRS)active fire dataset,and the high-accuracy crop planting area maps.Our results revealed an overall upward trend of 805.96 km^(2)/yr in NEC CRB from 2001 to 2021.The corn CRB area accounted for more than 50%of the total CRB area in each CRB-intensive year(2013-2021),and the increasing corn CRB generally aligns with the growing corn cultivation fields.A seasonal shift in CRB was found around 2017,with intensive CRB activities transitioning from both autumn and spring to primarily spring,particularly in the Songnen Plain and Sanjiang Plain.The changing trend of PM2.5 concentration aligned spatially with the shift.Moreover,the CRBs in spring of 2020 and 2021 were more severe than the major burning seasons in previous years,likely due to the disruptions during COVID-19 lockdowns.In certain years,the explanatory power of spring CRB on PM2.5 concentration was comparable to that of other natural factors,such as precipitation.This study underscores the critical need for sustained and region-specific strategies to tackle the challenges posed by CRBs.
