We introduce a new three-party semi-quantum dialogue(3P-SQD)protocol that combines GHZ-state-based semiquantum communication,a Grover's algorithm-driven 2-bit encoding scheme,and hypergraph-based access control.In...We introduce a new three-party semi-quantum dialogue(3P-SQD)protocol that combines GHZ-state-based semiquantum communication,a Grover's algorithm-driven 2-bit encoding scheme,and hypergraph-based access control.In each round,the fully quantum participant Alice sends two bits,whereas the semi-quantum participants Bob and Charlie,restricted to semi-quantum operations such as measurements in the computational basis and reflection,each transmit one bit.The protocol incorporates probe state checking,Grover's algorithm-based encoding,and hypergraph-based authorization.It achieves information-theoretic security and controlled access,while preserving high message throughput and imposing no additional requirements on the semi-quantum users.展开更多
As an important quantum cryptanalysis algorithm,Kuperberg's algorithm efficiently addresses the dihedral hidden subgroup problem with sub-exponential acceleration.However,when dealing with large numbers,the algori...As an important quantum cryptanalysis algorithm,Kuperberg's algorithm efficiently addresses the dihedral hidden subgroup problem with sub-exponential acceleration.However,when dealing with large numbers,the algorithm demands a deeper quantum circuit depth,rendering its implementation on current quantum devices prone to noise interference and thereby significantly reducing its efficiency.To mitigate this challenge,this paper proposes a distributed Kuperberg's algorithm.It decomposes the original function into sub-functions which can be executed on different nodes in parallel.The implementation of these sub-functions necessitates a shallower quantum circuit depth and a reduced number of qubits when contrasted with the execution of the original function.Furthermore,the proposed algorithm can be directly generalized to an arbitrary number of nodes by adjusting the quantity of input qubits.The utilization of multi-node parallel processing makes the proposed algorithm a linear enhancement in query complexity relative to the original algorithm.To validate the feasibility and demonstrate the superiority of our algorithm,experiments are conducted on the Qiskit platform.展开更多
Gas hydrates are increasingly recognized as a significant unconventional energy resource and a key factor in marine geohazards and the global carbon cycle.However,accurately identifying and quantifying hydrate-bearing...Gas hydrates are increasingly recognized as a significant unconventional energy resource and a key factor in marine geohazards and the global carbon cycle.However,accurately identifying and quantifying hydrate-bearing formations remains challenging due to complex geophysical signatures and heterogeneous distribution.This study evaluates twelve supervised machine learning(ML)algorithms for two key tasks:Classification of hydrate-bearing layers and regression-based estimation of hydrate saturation,using well log and pore-water geochemical data from Site NGHP-01-19B.Two physically independent labeling frameworks are employed:One based on Archie's law using resistivity(1350 samples,29%hydratebearing),and another based on a three-phase velocity model(890 samples,25%hydrate-bearing).A diverse set of models,including tree-based ensembles(Decision Tree,Random Forest,GBDT,XGBoost,Light GBM,Cat Boost,Bagging,Ada Boost),kernel methods(SVM,SVR),instance-based learning(KNN),neural networks(MLP),and Gaussian Process models(GPR,GPC),are systematically compared using cross-validation and grid search.Ensemble methods consistently performed best in classification,with Ada Boost and GBDT,achieving test accuracies above 0.94(Archie)and 0.98(velocity-based).For regression,GPR delivered the most accurate hydrate saturation estimates(R2>0.99),while GBDT and Random Forest provided a strong balance of accuracy and computational efficiency.Notably,depth below seafloor(TDEP),though not a direct geophysical input,significantly enhanced model performance by acting as a proxy for stratigraphic and thermodynamic conditions.Group-based validation confirmed that random-sample splitting overestimates performance due to depth-wise autocorrelation,highlighting the importance of geologically informed model assessment.Overall,the consistent performance of ML models across both labeling schemes and input feature sets underscores their robustness and transferability,supporting their use as a reliable toolset for offshore gas hydrate reservoir characterization.展开更多
An adaptive path planning algorithm was proposed,which improves upon traditional A*by integrating an improved A*algorithm with the Dynamic Window Approach(DWA).This addresses the problems of slow search speed,unsmooth...An adaptive path planning algorithm was proposed,which improves upon traditional A*by integrating an improved A*algorithm with the Dynamic Window Approach(DWA).This addresses the problems of slow search speed,unsmooth paths,and poor dynamic obstacle avoidance capability.Through an“8+5”neighborhood screening,a 16-neighborhood evaluation function,and a second-order then third-order Bézier curve optimization process,a Jetson Nano+ROS(Robot Operating System)is deployed to meet the requirements of efficient and safe navigation for fire inspection robots in complex environments.The results show that,compared with the original algorithm,the proposed algorithm reduces the average number of traversed nodes by 49.23%,the number of turns in the optimized path has decreased by approximately 28.82%,decreases curvature by 66.6%,and eliminates path tangency with obstacles.This also supports real-time obstacle avoidance with integration DWA,and outperforms traditional methods.展开更多
The calculation of viewing and solar geometry angles is a critical first step in retrieving atmospheric and surface variables from geostationary satellite observations.Whereas the viewing angles for geostationary sate...The calculation of viewing and solar geometry angles is a critical first step in retrieving atmospheric and surface variables from geostationary satellite observations.Whereas the viewing angles for geostationary satellites are not timevarying,a primary source of inaccuracy in solar positioning is the use of a single timestamp.Since pixel scanning times can differ significantly across the field-of-view disk(e.g.,by approximately 13 min for Fengyun-4B),this practice leads to errors of up to±2°in solar zenith angle,which translates to±50 W m−2 in extraterrestrial irradiance;the errors in solar azimuth angle can exceed±100°.Beyond scanning time,this work also quantifies the impact of other inputs—including altitude,surface pressure,air temperature,difference between Terrestrial Time and Universal Time,and atmospheric refraction—on the resulting angles.A comparison of our precise calculations with the official National Satellite Meteorological Center L1_GEO product shows an accuracy within 0.1°,confirming its utility for most retrieval tasks.To facilitate higher precision when required,this work releases the corresponding satellite and solar positioning codes in both R and Python.展开更多
To enhance the accuracy of nearshore data products obtained from nadir radar altimeters,we introduce a novel two-step retracking algorithm for reconstructed waveforms.This approach utilizes Empirical Mode Decompositio...To enhance the accuracy of nearshore data products obtained from nadir radar altimeters,we introduce a novel two-step retracking algorithm for reconstructed waveforms.This approach utilizes Empirical Mode Decomposition(EMD)to extract trend information from the trailing edge of the waveform.Reconstructed waveforms are formed by linking the leading and trailing edge trend information.The retracking process consists of two steps:the first step focuses on retracking a segment of the leading edge to obtain 4 crucial a priori parameters.In the second step,retracking incorporates both the leading and trailing edges using the previously acquired a priori information.We tested the algorithm using data from the HY-2B radar altimeter.Results indicate that the proposed two-step retracking algorithm outperforms the Maximum Likelihood Estimation(MLE4)algorithm currently used in the operational processing of the HY-2B radar altimeter,as well as the Adaptive Leading Edge Subwaveform(ALES)algorithm,in terms of significant wave height(SWH)and sea level anomalies(SLA).Specifically,the standard deviation of the difference in SWH is reduced by 14%,and the standard deviation of the difference in SLA is reduced by approximately 18%.The two-step retracking algorithm effectively leverages trailing edge information,reduces the influence of peak noise on the leading edge,and improves both the utilization and accuracy of the waveform retracking.展开更多
The peripheral immune system has emerged as a regulator of neurodegenerative diseases such as Alzheimer’s disease.Microglia are resident immune cells in the brain that may orchestrate communication between the centra...The peripheral immune system has emerged as a regulator of neurodegenerative diseases such as Alzheimer’s disease.Microglia are resident immune cells in the brain that may orchestrate communication between the central nervous system and peripheral immune system,though the mechanisms are unclear.Here,we found that gamma-type immunoglobulin,a product originating from peripheral blood B cells,localized in the brain parenchyma of multiple mouse models with amyloid pathology,and was enriched on microglia but not on other brain cell types.Further experiments showed that gamma-type immunoglobulin bound to microglial cell membranes and led to diverse transcriptomic changes,including upregulation of pathways related to phagocytosis and immunity.Functional assays demonstrated that gamma-type immunoglobulin enhanced microglial phagocytic capacity for amyloid-beta fibrils via its Fc fragment,but not Fab fragment,fragment.Our data indicate that microglia,when exposed to gamma-type immunoglobulin,exhibit an enhanced capacity for clearing amyloid-beta fibrils,potentially via the gamma-type immunoglobulin Fc fragment signaling pathway.This suggests that parenchymal gamma-type immunoglobulin should be further investigated to determine whether it may play a beneficial role against Alzheimer’s disease by enhancing microglial function.展开更多
The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units,thereby enhancing the expected output power and avoiding negative influence.Traditional wind farm optimiz...The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units,thereby enhancing the expected output power and avoiding negative influence.Traditional wind farm optimization often uses idealized wake models,neglecting the influence of wind shear at different elevations,which leads to a lack of precision in estimating wake effects and fails to meet the accuracy and reliability requirements of practical engineering.To address this,we have constructed a three-dimensional 3D wind farm optimization model that incorporates elevation,utilizing a 3D wake model to better reflect real-world conditions.We aim to assess the optimization state of the algorithm and provide strong incentives at the right moments to ensure continuous evolution of the population.To this end,we propose an evolutionary adaptation degreeguided genetic algorithm based on power-law perturbation(PPGA)to adapt multidimensional conditions.We select the offshore wind power project in Nantong,Jiangsu,China,as a study example and compare PPGA with other well-performing algorithms under this practical project.Based on the actual wind condition data,the experimental results demonstrate that PPGA can effectively tackle this complex problem and achieve the best power efficiency.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.12201300)the Nanjing University of Science and Technology Undergraduate Innovation Training Program(Grant No.S202510288017)。
摘要We introduce a new three-party semi-quantum dialogue(3P-SQD)protocol that combines GHZ-state-based semiquantum communication,a Grover's algorithm-driven 2-bit encoding scheme,and hypergraph-based access control.In each round,the fully quantum participant Alice sends two bits,whereas the semi-quantum participants Bob and Charlie,restricted to semi-quantum operations such as measurements in the computational basis and reflection,each transmit one bit.The protocol incorporates probe state checking,Grover's algorithm-based encoding,and hypergraph-based authorization.It achieves information-theoretic security and controlled access,while preserving high message throughput and imposing no additional requirements on the semi-quantum users.
基金Project supported by the National Natural Science Foundation of China(Grant No.62171131)the Natural Science Foundation of Fujian Province,China(Grant Nos.2022J01186 and 2023J01533)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0302901)。
摘要As an important quantum cryptanalysis algorithm,Kuperberg's algorithm efficiently addresses the dihedral hidden subgroup problem with sub-exponential acceleration.However,when dealing with large numbers,the algorithm demands a deeper quantum circuit depth,rendering its implementation on current quantum devices prone to noise interference and thereby significantly reducing its efficiency.To mitigate this challenge,this paper proposes a distributed Kuperberg's algorithm.It decomposes the original function into sub-functions which can be executed on different nodes in parallel.The implementation of these sub-functions necessitates a shallower quantum circuit depth and a reduced number of qubits when contrasted with the execution of the original function.Furthermore,the proposed algorithm can be directly generalized to an arbitrary number of nodes by adjusting the quantity of input qubits.The utilization of multi-node parallel processing makes the proposed algorithm a linear enhancement in query complexity relative to the original algorithm.To validate the feasibility and demonstrate the superiority of our algorithm,experiments are conducted on the Qiskit platform.
基金supported by the China Scholarship Council under the State Scholarship Fund(202506340082)the Key Project of Guangdong Provincial Key R&D Program(2023B1111050014)+3 种基金the Youth Promotion Project of the Natural Science Foundation of Guangdong Province(2023A1515030280)the Guangdong Basic and Applied Basic Research Foundation(2023A1515010926)the Guangzhou Science and Technology Plan Project(2024A04J9876)funded by China National Petroleum Corporation(CNPC,2024DQ02-0107)。
摘要Gas hydrates are increasingly recognized as a significant unconventional energy resource and a key factor in marine geohazards and the global carbon cycle.However,accurately identifying and quantifying hydrate-bearing formations remains challenging due to complex geophysical signatures and heterogeneous distribution.This study evaluates twelve supervised machine learning(ML)algorithms for two key tasks:Classification of hydrate-bearing layers and regression-based estimation of hydrate saturation,using well log and pore-water geochemical data from Site NGHP-01-19B.Two physically independent labeling frameworks are employed:One based on Archie's law using resistivity(1350 samples,29%hydratebearing),and another based on a three-phase velocity model(890 samples,25%hydrate-bearing).A diverse set of models,including tree-based ensembles(Decision Tree,Random Forest,GBDT,XGBoost,Light GBM,Cat Boost,Bagging,Ada Boost),kernel methods(SVM,SVR),instance-based learning(KNN),neural networks(MLP),and Gaussian Process models(GPR,GPC),are systematically compared using cross-validation and grid search.Ensemble methods consistently performed best in classification,with Ada Boost and GBDT,achieving test accuracies above 0.94(Archie)and 0.98(velocity-based).For regression,GPR delivered the most accurate hydrate saturation estimates(R2>0.99),while GBDT and Random Forest provided a strong balance of accuracy and computational efficiency.Notably,depth below seafloor(TDEP),though not a direct geophysical input,significantly enhanced model performance by acting as a proxy for stratigraphic and thermodynamic conditions.Group-based validation confirmed that random-sample splitting overestimates performance due to depth-wise autocorrelation,highlighting the importance of geologically informed model assessment.Overall,the consistent performance of ML models across both labeling schemes and input feature sets underscores their robustness and transferability,supporting their use as a reliable toolset for offshore gas hydrate reservoir characterization.
基金supported by the National Natural Science Foundation of China(Nos.61975015,62375017).
摘要An adaptive path planning algorithm was proposed,which improves upon traditional A*by integrating an improved A*algorithm with the Dynamic Window Approach(DWA).This addresses the problems of slow search speed,unsmooth paths,and poor dynamic obstacle avoidance capability.Through an“8+5”neighborhood screening,a 16-neighborhood evaluation function,and a second-order then third-order Bézier curve optimization process,a Jetson Nano+ROS(Robot Operating System)is deployed to meet the requirements of efficient and safe navigation for fire inspection robots in complex environments.The results show that,compared with the original algorithm,the proposed algorithm reduces the average number of traversed nodes by 49.23%,the number of turns in the optimized path has decreased by approximately 28.82%,decreases curvature by 66.6%,and eliminates path tangency with obstacles.This also supports real-time obstacle avoidance with integration DWA,and outperforms traditional methods.
基金supported by the National Natural Science Foundation of China(Grant No.42375192).
摘要The calculation of viewing and solar geometry angles is a critical first step in retrieving atmospheric and surface variables from geostationary satellite observations.Whereas the viewing angles for geostationary satellites are not timevarying,a primary source of inaccuracy in solar positioning is the use of a single timestamp.Since pixel scanning times can differ significantly across the field-of-view disk(e.g.,by approximately 13 min for Fengyun-4B),this practice leads to errors of up to±2°in solar zenith angle,which translates to±50 W m−2 in extraterrestrial irradiance;the errors in solar azimuth angle can exceed±100°.Beyond scanning time,this work also quantifies the impact of other inputs—including altitude,surface pressure,air temperature,difference between Terrestrial Time and Universal Time,and atmospheric refraction—on the resulting angles.A comparison of our precise calculations with the official National Satellite Meteorological Center L1_GEO product shows an accuracy within 0.1°,confirming its utility for most retrieval tasks.To facilitate higher precision when required,this work releases the corresponding satellite and solar positioning codes in both R and Python.
基金The National Natural Science Foundation of China under contract No.42192531。
摘要To enhance the accuracy of nearshore data products obtained from nadir radar altimeters,we introduce a novel two-step retracking algorithm for reconstructed waveforms.This approach utilizes Empirical Mode Decomposition(EMD)to extract trend information from the trailing edge of the waveform.Reconstructed waveforms are formed by linking the leading and trailing edge trend information.The retracking process consists of two steps:the first step focuses on retracking a segment of the leading edge to obtain 4 crucial a priori parameters.In the second step,retracking incorporates both the leading and trailing edges using the previously acquired a priori information.We tested the algorithm using data from the HY-2B radar altimeter.Results indicate that the proposed two-step retracking algorithm outperforms the Maximum Likelihood Estimation(MLE4)algorithm currently used in the operational processing of the HY-2B radar altimeter,as well as the Adaptive Leading Edge Subwaveform(ALES)algorithm,in terms of significant wave height(SWH)and sea level anomalies(SLA).Specifically,the standard deviation of the difference in SWH is reduced by 14%,and the standard deviation of the difference in SLA is reduced by approximately 18%.The two-step retracking algorithm effectively leverages trailing edge information,reduces the influence of peak noise on the leading edge,and improves both the utilization and accuracy of the waveform retracking.
基金supported by the National Natural Science Foundation of China,Nos.82171082(to ZX),32000727(to TZ),32370731(to YZ)Guangdong Basic and Applied Basic Research Foundation,No.2024A151501069(to ZX)+1 种基金Shenzhen Science and Technology Program,Nos.JCYJ20210324101603009(to ZX),GJHZ20220913142807015(to TZ),JCYJ20220531100204010(to TZ),JCYJ20230807091308018(to YZ)Shenzhen Medical Research Funds,No.A2303068(to TZ).
摘要The peripheral immune system has emerged as a regulator of neurodegenerative diseases such as Alzheimer’s disease.Microglia are resident immune cells in the brain that may orchestrate communication between the central nervous system and peripheral immune system,though the mechanisms are unclear.Here,we found that gamma-type immunoglobulin,a product originating from peripheral blood B cells,localized in the brain parenchyma of multiple mouse models with amyloid pathology,and was enriched on microglia but not on other brain cell types.Further experiments showed that gamma-type immunoglobulin bound to microglial cell membranes and led to diverse transcriptomic changes,including upregulation of pathways related to phagocytosis and immunity.Functional assays demonstrated that gamma-type immunoglobulin enhanced microglial phagocytic capacity for amyloid-beta fibrils via its Fc fragment,but not Fab fragment,fragment.Our data indicate that microglia,when exposed to gamma-type immunoglobulin,exhibit an enhanced capacity for clearing amyloid-beta fibrils,potentially via the gamma-type immunoglobulin Fc fragment signaling pathway.This suggests that parenchymal gamma-type immunoglobulin should be further investigated to determine whether it may play a beneficial role against Alzheimer’s disease by enhancing microglial function.
基金partially supported by the Japan Society for the Promotion of Science(JSPS)KAKENHI(JP23K24899)Japan Science and Technology Agency(JST)Support for Pioneering Research Initiated by the Next Generation(SPRING)(JPMJSP2145).
摘要The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units,thereby enhancing the expected output power and avoiding negative influence.Traditional wind farm optimization often uses idealized wake models,neglecting the influence of wind shear at different elevations,which leads to a lack of precision in estimating wake effects and fails to meet the accuracy and reliability requirements of practical engineering.To address this,we have constructed a three-dimensional 3D wind farm optimization model that incorporates elevation,utilizing a 3D wake model to better reflect real-world conditions.We aim to assess the optimization state of the algorithm and provide strong incentives at the right moments to ensure continuous evolution of the population.To this end,we propose an evolutionary adaptation degreeguided genetic algorithm based on power-law perturbation(PPGA)to adapt multidimensional conditions.We select the offshore wind power project in Nantong,Jiangsu,China,as a study example and compare PPGA with other well-performing algorithms under this practical project.Based on the actual wind condition data,the experimental results demonstrate that PPGA can effectively tackle this complex problem and achieve the best power efficiency.