Shenzhen,a major city in southern China,has experienced rapid advancements in Unmanned Aerial Vehicle(UAV)technology,resulting in extensive logistics networks with thousands of daily flights.However,frequent disruptio...Shenzhen,a major city in southern China,has experienced rapid advancements in Unmanned Aerial Vehicle(UAV)technology,resulting in extensive logistics networks with thousands of daily flights.However,frequent disruptions due to its subtropical monsoon climate,including typhoons and gusty winds,present ongoing challenges.Despite the growing focus on operational costs and third-party risks,research on low-altitude urban wind fields remains scarce.This study addresses this gap by integrating wind field analysis into UAV path planning,introducing key innovations to the classical model.First,UAV wind resistance and turbulence constraints are analyzed,mapping high-wind-speed and turbulence-prone zones in the airspace.Second,wind dynamics are incorporated into path planning by considering airspeed and groundspeed variation,optimizing waypoint selection and flight speed adjustments to improve overall energy efficiency.Additionally,a wind-aware Theta*algorithm is proposed,leveraging wind vectors to expedite search process,while Computational Fluid Dynamics(CFD)techniques are employed to calculate wind fields.A case study of Shenzhen,examining wind patterns over the past decade,demonstrates a 6.23%improvement in groundspeed and a 7.69%reduction in energy consumption compared to wind-agnostic models.This framework advances UAV logistics by enhancing route safety and energy efficiency,contributing to more cost-effective operations.展开更多
The deformation characteristics and thermal response of anchor rods are crucial for ensuring the stability and safety of surrounding rock support structures.However,existing research has predominantly concentrated on ...The deformation characteristics and thermal response of anchor rods are crucial for ensuring the stability and safety of surrounding rock support structures.However,existing research has predominantly concentrated on the mechanical performance of anchor rods,with limited attention to the coupled evolution of strain and temperature fields during tensile deformation.This knowledge gap hinders a comprehensive understanding of the synergistic mechanical-thermal response mechanisms in anchor rods under loading conditions.To address this limitation,the present study systematically investigated the evolution of strain and temperature fields,along with their correlation,during the test of micro-negative Poisson's ratio(NPR)and ordinary Poisson's ratio(PR)anchor rods.Digital image correlation(DIC)and infrared thermography(IRT)techniques were employed for this exploration.The uniaxial tensile tests were conducted at two different rates,and the ordinary PR anchor rod(Q235 anchor rod)was established as a control group for comparative analysis.The findings reveal that the micro-NPR anchor rod exhibit strain localization at multiple locations during the tensile process,whereas Q235 anchors show local strain concentration in only one region.The standard deviation evolution curves for both the strain and temperature field exhibit two distinct phases in the two anchor rods.The evolution patterns between these two types of curves are basically consistent.The two standard deviation curves for the micro-NPR anchor rod display a wavy increase in the second phase,while for the Q235 anchor rod,they increase steadily until the specimen is damaged.The correlation analysis reveals that the standard deviations of strain and temperature differences for both types of anchor rods are significantly correlated.These findings demonstrate the synergistic evolution mechanism of deformation and thermal response,providing a potential foundation for utilizing thermal monitoring to assess the stability of rock support structures.展开更多
Temperature-dependent resistivity,upper critical field H_(c2)and its anisotropy in overdoped superconducting Ba_(1-x)K_x Fe_2As_2(x=0.6-1)single crystals have been measured in steady magnetic fields up to 44 T and low...Temperature-dependent resistivity,upper critical field H_(c2)and its anisotropy in overdoped superconducting Ba_(1-x)K_x Fe_2As_2(x=0.6-1)single crystals have been measured in steady magnetic fields up to 44 T and low temperatures down to 0.4 K.Analysis using both the quadratic term and power-law fitting demonstrates that the in-plane resistivityρ_(ab)(T)progressively approaches the Fermi-liquid T~2behavior with increasing K doping and reaches a saturation plateau at x≈0.8.The temperature dependence of both H_(c2)^(ab)and H^(c)_(c2)follows the Werthamer-Helfand-Hohenberg model,incorporating orbital and spin paramagnetic effects.For x≤0.8,the orbital effect dominates for H ab,while the Pauli paramagnetic effect prevails for H c.For x>0.8,the Pauli paramagnetic effect becomes dominant in both crystallographic directions.The anisotropy of H_(c2)(0)exhibits a discontinuity in its dependence on K doping concentration with a significant enhancement at x=0.8 and a maximum at x=0.9.These experimental results indicate that the electron correlation effect is enhanced in the heavily overdoped Ba_(1-x)K_(x)Fe_(2)As_(2)system where the underlying symmetries are broken due to the Fermi surface reconstruction before x=0.9.展开更多
To address the challenges of high-precision optical surface defect detection,we propose a novel design for a wide-field and broadband light field camera in this work.The proposed system can achieve a 50°field of ...To address the challenges of high-precision optical surface defect detection,we propose a novel design for a wide-field and broadband light field camera in this work.The proposed system can achieve a 50°field of view and operates at both visible and near-infrared wavelengths.Using the principles of light field imaging,the proposed design enables 3D reconstruction of optical surfaces,thus enabling vertical surface height measurements with enhanced accuracy.Using Zemax-based simulations,we evaluate the system’s modulation transfer function,its optical aberrations,and its tolerance to shape variations through Zernike coefficient adjustments.The results demonstrate that this camera can achieve the required spatial resolution while also maintaining high imaging quality and thus offers a promising solution for advanced optical surface defect inspection.展开更多
The effects of initial spin orientation on the final electron beam polarization in laser wakefield acceleration in a pre-polarized plasma are investigated theoretically and numerically.From the results of variation of...The effects of initial spin orientation on the final electron beam polarization in laser wakefield acceleration in a pre-polarized plasma are investigated theoretically and numerically.From the results of variation of the initial spin direction,the spin dynamics of the electron beam are found to depend on the self-injection mechanism.The effects of wakefields and laser fields are studied using test particle dynamics and particle-in-cell simulations based on the Thomas-Bargmann-Michel-Telegdi equation.Compared with transverse injection,longitudinal injection is found to be preferable for obtaining a highly polarized electron beam.展开更多
Innovative S-scheme heterostructures face intrinsic limitations in charge separation due to insufficient interfacial driving forces.This work pioneers a dual-vacancy engineering strategy to break this bottleneck,const...Innovative S-scheme heterostructures face intrinsic limitations in charge separation due to insufficient interfacial driving forces.This work pioneers a dual-vacancy engineering strategy to break this bottleneck,constructing a plasmonic ZnIn_(2)S_(4-x)MoO_(3-x)(ZIS/MO)S-scheme heterojunction where oxygen and sulfur vacancies synergistically reconfigure charge transfer dynamics via dual-path modulation.Uniquely,sulfur vacancies amplify the built-in electric field(IEF)intensity by enlarging the Fermi level gap,while oxygen and sulfur dual-vacancies induce localized surface plasmon resonance(LSPR)via free-carrier concentration enhancement.Simultaneously,sulfur vacancies lower the H^(*)adsorption barrier,and dual vacancies amplify photothermal conversion by promoting nonradiative decay,accelerating temperature elevation and kinetics.Electron dynamics confirm that this dual-vacancy synergy prolongs charge carrier lifetime by a factor of 5.23.Consequently,the optimized sulfur vacancy-rich ZnIn_(2)S_(4-x)/MoO_(3-x)(R-ZIS/MO)exhibits remarkable photocatalytic hydrogen production rates of 3.60 mmol g^(-1) h^(-1)under visible light and 22.74 mmol g^(-1) h^(-1) under full-spectrum irradiation,representing 7.8-fold and17.2-fold enhancements,respectively.This study establishes a new paradigm.Targeted dual-vacancy coordination in plasmonic heterostructures enables unprecedented IEF-LSPR co-modulation,opening avenues for high-efficiency solar energy conversion.展开更多
AIM:To identify early biomarkers associated with glaucomatous visual field(VF)progression in patients with normal-tension glaucoma(NTG).METHODS:This study included patients were divided into two groups based on diseas...AIM:To identify early biomarkers associated with glaucomatous visual field(VF)progression in patients with normal-tension glaucoma(NTG).METHODS:This study included patients were divided into two groups based on disease progression status.Tear samples were collected for proteomic analysis.Dataindependent acquisition(DIA)mass spectrometry combined with bioinformatic analyses was performed to identify and validate potential protein biomarkers for NTG progression.Additionally,differentially expressed proteins(DEPs)were evaluated using mediating effect models and receiver operating characteristic(ROC)curve analysis.RESULTS:A total of 19 patients(20 eyes)with NTG participated in this study,including 10 patients(4 males and 6 females;10 eyes)in the progression group with mean age of 67.70±9.03y and 10 patients(4 males and 6 females;10 eyes)in the non-progression group with mean age of 68.60±7.58y.A total of 158 significantly differentially expressed proteins were detected.UniProt database annotation identified 3 upregulated proteins and 12 downregulated proteins.Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis showed that these DEPs were mainly enriched in pathways such as oocyte meiosis.Gene Ontology(GO)enrichment analysis revealed functional clusters related to cellular processes.Weighted gene coexpression network analysis(WGCNA)indicated that the core proteins were primarily involved in the neurodegenerationmultiple diseases pathway and cellular processes.Mediating effect analysis identified PRDX4(L)as a potential protein biomarker.ROC curve analysis showed that GNAI1 had the largest area under the curve(AUC=0.889).CONCLUSION:This study identifies 15 differentially expressed proteins in the tear fluid of NTG patients,including PRDX4(L).PRDX4(L)plays a key role in oxidative stress.展开更多
A solenoid is typically used in normally conducting and superconducting radio frequency(SRF)photoinjectors to compensate for the projected transverse beam emittance.In the ELBE SRF Gun-Ⅱ,a superconducting solenoid is...A solenoid is typically used in normally conducting and superconducting radio frequency(SRF)photoinjectors to compensate for the projected transverse beam emittance.In the ELBE SRF Gun-Ⅱ,a superconducting solenoid is positioned inside the gun cryomodule approximately 0.7 m from the end of the gun cavity.The spherical aberration and multipole field effects caused by offset and tilt limit the reduction in beam emittance for high bunch charges.We designed a novel superconducting(SC)solenoid with a lower spherical aberration coefficient.In the simulation,the beam emittance from the spherical aberration decreased by 47%.Both the longitudinal and transverse fields were measured and analyzed using the formalism fitting method to assess the performance of the SC solenoid within the cryomodule and its influence on the beam transverse emittance.展开更多
Background:The bacterial biofilm poses a significant challenge to traditional antibiotic therapy.There is a great need to develop novel antibiofilm agents combined with biofilm disrupting and bacteria-killing without ...Background:The bacterial biofilm poses a significant challenge to traditional antibiotic therapy.There is a great need to develop novel antibiofilm agents combined with biofilm disrupting and bacteria-killing without the dependence of antibiotic.Methods:Herein,we prepared ultrasound/magnetic field-responsive ferroferric oxide nanoparticles(Fe_(3)O_(4))/glucose oxidase microbubbles(FGMB)to form a cascade catalytic system for effective removing methicillin-resistant Staphylococcus aureus biofilms.FGMB were prepared through interfacial self-assembly of Fe_(3)O_(4) nanoparticles(NPs)and glucose oxidase(GOx)at the gas-liquid interface stabilized by surfactants.Under ultrasound/magnetic field stimulation,FGMB disrupted biofilm architecture through microbubble collapse-induced microjets and magnetically driven displacement.Simultaneously,ultrasound-triggered rupture of FGMB released GOx and Fe_(3)O_(4) NPs.Glucose can be oxidized by GOx to generate gluconic acid and hydrogen peroxide which was subsequently catalyzed into hydroxyl radicals by Fe_(3)O_(4) NPs,enabling chemical eradication of biofilm-embedded bacteria.Results:Optical microscopy images demonstrated that FGMB have spherical structure with average size of approximately 17μm.FGMB showed a 65.4%decrease in methicillin-resistant Staphylococcus aureus biofilm biomass and 1.1 log bacterial inactivation efficiency(91.2%),suggesting effective biofilm elimination.In vitro experimental results also indicate that FGMB have good biocompatibility.Conclusion:This antibiofilm strategy integrated dual modes of physical biofilm disruption with chemical bacteria-killing shows great potential as a versatile,non-resistant strategy for bacterial biofilm elimination.展开更多
Peroxymonosulfate(PMS)-based advanced oxidation processes(AOPs)are an effective way to remove emerging contaminants(ECs)from water.The catalytic process involving PMS is hindered by the suboptimal electron trans-fer e...Peroxymonosulfate(PMS)-based advanced oxidation processes(AOPs)are an effective way to remove emerging contaminants(ECs)from water.The catalytic process involving PMS is hindered by the suboptimal electron trans-fer efficiency of current catalysts,the further application of AOPs technology is limited.Here,it is proposed that the interfacial electric field can be controlled by bor(B)-doped FeNC catalysts,which shows significant advantages in the efficient generation,release and participation of reactive oxygen species(ROS)in the reaction.The super exchange interaction between Fe sites and N and B sites is realized through the directional transfer of electrons in the interfacial electric field,which ensures the high efficiency and stability of the PMS catalytic process.B doping increases the d orbitals distribution at Fermi level,which facilitates enhanced electron transition activity,thereby promoting the effective generation of (1)^O_(2).At the same time,orbital hybridization causes the center of the d band to move to a lower energy level,which not only contributes to the desorption process of (1)^O_(2),but also accelerates its release.In addition,B-doping also improved the adsorption capacity of organic pollutants and shortened the migration distance of ROS,thereby significantly improving the degradation efficiency of ECs.The B-doping strategy outlined offers a novel approach to the development of FeNC catalysts,it lays a theoretical foundation and offers technical insights for the integration of PMS/AOPs technology in the ECs management.展开更多
The spin-sensitive nature of redox reactions in energy conversion systems,such as the oxygen evolution reaction(OER),has attracted increasing attention due to its potential for enhancing catalytic efficiency.Magnetic ...The spin-sensitive nature of redox reactions in energy conversion systems,such as the oxygen evolution reaction(OER),has attracted increasing attention due to its potential for enhancing catalytic efficiency.Magnetic fields(MFs)have been proposed to enhance OER performance by influencing the spin states of oxygen intermediates.However,prior study has predominantly focused on MF effects mediated by the intrinsic magnetic properties of electrocatalysts or magnetohydrodynamics.In this work,we report a universal enhancement in OER activity,achieving over 150% increase in current density under a200 mT MF across diamagnetic,paramagnetic and magnetic electrocatalysts in 1 M KOH.Through systematic investigation of MF orientation and strength,pH,applied potentials,and the use of benzoquinone radical scavenger,we demonstrate that MF-driven performance improvements arise from direct modulation of oxygen radical spin states.Specifically,MFs promote the formation of spin-triplet oxygen intermediates(↑O–O↑),a critical step for O–O bond formation,independent of the catalyst's intrinsic magnetism.However,the local magnetic environment near the catalyst surface,governed by its magnetic properties,indirectly influences radical spin dynamics by alternating the effective field experienced by intermediates.These findings redefine the role of spin manipulation in electrocatalysis,advancing understanding of MF-driven spin effects in redox reactions.展开更多
Detecting geomagnetic anomalies preceding earthquakes is a challenging yet promising area of research that has gained increasing attention in recent years.This study introduces a novel reconstruction-based modeling ap...Detecting geomagnetic anomalies preceding earthquakes is a challenging yet promising area of research that has gained increasing attention in recent years.This study introduces a novel reconstruction-based modeling approach enhanced by negative learning,employing a Bidirectional Long Short-Term Memory(BiLSTM)network explicitly trained to accurately reconstruct non-seismic geomagnetic signals while intentionally amplifying reconstruction errors for seismic signals.By penalizing the model for accurately reconstructing seismic anomalies,the negative learning approach effectively magnifies the differences between normal and anomalous data.This strategic differentiation enhances the sensitivity of the BiLSTM network,enabling improved detection of subtle geomagnetic anomalies that may serve as earthquake precursors.Experimental validation clearly demonstrated statistically significant higher reconstruction errors for seismic signals compared to non-seismic signals,confirmed through the Mann-Whitney U test with a p-value of 0.0035 for Root Mean Square Error(RMSE).These results provide compelling evidence of the enhanced anomaly detection capability achieved through negative learning.Unlike traditional classification-based methods,negative learning explicitly encourages sensitivity to subtle precursor signals embedded within complex geomagnetic data,establishing a robust basis for further development of reliable earthquake prediction methods.展开更多
Metal additive manufacturing(AM)technology has promising applications across many fields due to its near-net-shape advantages.The quality of the as-built component is closely linked to the temperature evolution during...Metal additive manufacturing(AM)technology has promising applications across many fields due to its near-net-shape advantages.The quality of the as-built component is closely linked to the temperature evolution during the metal AM process,which exhibits strong nonlinearities,localized high gradients,and rapid cooling rates.Therefore,real-time prediction of the temperature field is essential for effective online process control to achieve high fabrication quality,which poses surprising challenges for numerical methods,as traditional methods suffer from the inherent time-consuming nature of fine time-space discretizations.In this study,we proposed an isothermal surface imaging and transfer learning framework for fast prediction of isothermal surfaces,which are further used to reconstruct the high-dimensional,nonlinear temperature field.It consists of three key parts:physics-guided isothermal surface imaging to reduce the problem dimensionality by transforming the unstructured temperature field into a series of structured grayscale images,a pre-trained hybrid parameter-to-image generative neural network for the isothermal surface prediction in favor of small training samples,and a transfer learning strategy leveraging physical similarity of these isothermal surfaces in the metal AM process to obtain the 3D temperature field.The training samples are generated using a high-fidelity numerical model,which is validated against experimental data.The predicted results from the proposed framework agree well with those from the high-fidelity numerical simulation for a given combination of process parameters,achieving a computational cost measured in seconds.It is expected that the proposed framework could serve as a powerful tool for predicting the temperature field and further facilitating online control of process parameters.展开更多
This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging v...This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging variogram across various anisotropic modes,providing mathematical models to enhance our understanding of random fields.A new anisotropy index,called LSAI,is introduced to quantify anisotropy based on the autocorrelation length and the orientation of the principal axes within the variogram.An LSAI value closer to one indicates a lower degree of anisotropy.The present study examines how the degree of anisotropy varies with different autocorrelation lengths and angles between the principal axes,providing valuable insights into these relationships.To improve the accuracy of parameter probability distribution estimations,this study integrates limited field test data using a Bayesian inference approach.Additionally,the Markov chain Monte Carlo simulation method is employed to develop a conditional random field(CRF)for the deformation modulus.By incorporating data from field bearing plate tests,the posterior variance data for the deformation modulus are derived.This process facilitates the construction of a detailed and reliable CRF for the deformation modulus.展开更多
Magnetic field-driven spin polarization modulation has emerged as an effective way to boost the electrocatalytic oxygen evolution reaction(OER).However,the correlation among catalyst structure,magnetic property,and ma...Magnetic field-driven spin polarization modulation has emerged as an effective way to boost the electrocatalytic oxygen evolution reaction(OER).However,the correlation among catalyst structure,magnetic property,and magnetic field enhanced-electrochemical activity remains to be fully elucidated.Herein,single-domain CoFe_(2)O_(4) catalysts with tunable oxygen vacancies(CFO-V_(O)) were synthesized to probe how V_(O) mediates magnetism and OER activity under magnetic field.The introduction of V_(O) can simultaneously modulate saturation magnetization(M_(s)) and coercivity(H_(c)),where the increased M_(s) dominates the magnetic field-enhanced OER activity.Under a 14,000 G magnetic field,the optimized CFO-V_(O) exhibits up to 16.1 % reduction in overpotential and 365 % enhancement in magnetocurrent(MC).Electrochemical analyses and post-OER characterization reveal that the magnetic field synergistically improves OER kinetics through lattice distortion induction,magnetohydrodynamic effect,and spin charge transfer effect.Importantly,the magnetic field promotes additional Co^(3+) generation to compensate for charge imbalance caused by V_(O) filling,maintaining dynamic equilibrium of V_(O) and effective reactant adsorption-conversion processes.This work unveils the synergistic mechanism of V_(O) and magnetic parameters for enhancing OER performance under the magnetic field,providing new insights into the design of high-efficiency spinregulated OER catalysts.展开更多
In response to the Ministry of Education’s requirements for building distinctive model software schools,Software College of Northeastern University and Shenzhen Kingdom Technology Co.,Ltd.jointly developed the specia...In response to the Ministry of Education’s requirements for building distinctive model software schools,Software College of Northeastern University and Shenzhen Kingdom Technology Co.,Ltd.jointly developed the specialized course“Application and Practice of RPA Technology in FinTech”.Addressing pain points in financial digital transformation,the course integrates robotic process automation(RPA)principles,financial domain knowledge,and RPA platform practice into a“technology-scenario-capability”trinity teaching system.Through 64 credit hours of integrated theory and practice,it covers RPA fundamentals,financial applications,RPA operations(including core skills like Web/desktop automation),and AI integration,cultivating students’ability to design and implement automated financial workflows.It innovatively features a RPA simulation platform,30+financial case studies,and modular task resources,creating a“teacher-machine-student”interactive model.Practice demonstrates the course effectively enhances students’integration of technical application and business acumen,providing a scalable paradigm for cultivating interdisciplinary FinTech talent.展开更多
A phase-field model including magnetic field induced dendrite fragmentation was established and applied to the cases with different initial crystal nuclear positions for AA5754 aluminum alloy electromagnetic laser bea...A phase-field model including magnetic field induced dendrite fragmentation was established and applied to the cases with different initial crystal nuclear positions for AA5754 aluminum alloy electromagnetic laser beam welding.Compare the calculated results that include dendrite fragmentation caused by the thermal electromagnetic Lorentz force with the results that consider only the thermal electromagnetic Lorentz force,without fragmentation,at the characteristic time instants.Both in the early and late stages,the small fragmentation at the dendrite tip promotes the number of higher-order branches and their growth,especially in the direction perpendicular to the solidification.The later stage fragmentation has the possibility of breaking one grain into several,which verifies the possibility of grain refinement caused by dendrite fragmentation.The fracture surface caused by fragmentation also makes more solid-liquid interfaces and their growth.In addition,the cases with different initial nuclear positions were compared.The grain growth in the low-temperature zone can be inhibited by the equiaxed grains'fragmentation at the high-temperature area(179.8μm^(2) and 14.7% start at the center,115.4μm^(2) and 9.4% start at the high-temperature corner,134.3μm^(2) and 10.9%start at the low-temperature corner),which is another kind of grain refinement by the dendrite fragmentation.This kind of inhibition effect on grain growth in the low-temperature region will be enhanced with the increasing time interval between the two crystal nuclei’appearance(179.8μm^(2) and 14.7%when virtual grains appear at t=4.3803 s and t=4.3803 s,134.3μm^(2) and 10.9%at t=4.0977 s and t=3.9564 s,and 115.4μm^(2) and 9.4%at t=3.8151 s and t=3.5325 s).展开更多
Heliostat field design for tower solar thermal plants must jointly address solar geometry,optical losses,and layout optimization under engineering constraints.We develop an end-to-end workflow that(i)adopts a consiste...Heliostat field design for tower solar thermal plants must jointly address solar geometry,optical losses,and layout optimization under engineering constraints.We develop an end-to-end workflow that(i)adopts a consistent East–North–Up(ENU)convention for all plant-and sun-related vectors;(ii)integrates cosine efficiency,projection-based shading and blocking(SB),atmospheric transmittance,and an HFLCAL(heliostat field local calculation)truncation model into a single optical chain;and(iii)couples an Eliminate-Blocking(EB)layout prior with an improved“Cheetah”metaheuristic to search ring topology,mirror sizes,and heights while enforcing spacing,kinematics,and rated-power requirements.Projection-based SB is calibrated against Monte-Carlo ray tracing at representative sun positions,and the HFLCAL truncation model is used to quantify sensitivities to sunshape and error-budget parameters.In a three-phase study(fixed-size baseline,uniform sizing,heterogeneous sizing),the EB-guided optimizer improves annual per-area output relative to a radial baseline and reliably attains a 60 MW target.Under equal evaluation budgets,the proposed optimizer converges faster and with lower variance than GA-and PSO-based baselines,while respecting panel-level peak-flux limits through a smooth penalization of flux violations.The resulting layouts exhibit outward-increasing azimuthal spacing and ring-wise size sharing that are consistent with recent heliostat-field deployment experience.The framework is modular,auditable,and readily adaptable to alternative receivers,sites,and cost-aware objectives.展开更多
Recently,large-scale deep learning models have been increasingly adopted for point cloud classification.However,thesemethods typically require collecting extensive datasets frommultiple clients,which may lead to priva...Recently,large-scale deep learning models have been increasingly adopted for point cloud classification.However,thesemethods typically require collecting extensive datasets frommultiple clients,which may lead to privacy leaks.Federated learning provides an effective solution to data leakage by eliminating the need for data transmission,relying instead on the exchange of model parameters.However,the uneven distribution of client data can still affect the model’s ability to generalize effectively.To address these challenges,we propose a new framework for point cloud classification called Federated Dynamic Aggregation Selection Strategy-based Multi-Receptive Field Fusion Classification Framework(FDASS-MRFCF).Specifically,we tackle these challenges with two key innovations:(1)During the client local training phase,we propose a Multi-Receptive Field Fusion Classification Model(MRFCM),which captures local and global structures in point cloud data through dynamic convolution and multi-scale feature fusion,enhancing the robustness of point cloud classification.(2)In the server aggregation phase,we introduce a Federated Dynamic Aggregation Selection Strategy(FDASS),which employs a hybrid strategy to average client model parameters,skip aggregation,or reallocate local models to different clients,thereby balancing global consistency and local diversity.We evaluate our framework using the ModelNet40 and ShapeNetPart benchmarks,demonstrating its effectiveness.The proposed method is expected to significantly advance the field of point cloud classification in a secure environment.展开更多
In the dispersed computing environment driven by intelligent networks,intrusion detection faces significant challenges.This paper proposes a multilayer decentralized federated learning framework based on mean field ga...In the dispersed computing environment driven by intelligent networks,intrusion detection faces significant challenges.This paper proposes a multilayer decentralized federated learning framework based on mean field game theory(MFG-DFL).The framework organizes networked computing points(NCPs)into a three-layer collaborative architecture,and innovatively introduces MFG theory to model the complex dynamic interactions,which among large-scale NCPs as a game between a representative NCP and the mean field.By solving the coupled HJB and FPK equations,we design a dynamic incentive mechanism to fairly quantify and reward NCP contributions,thus aligning individual rationality with the global objectives of the system.The simulation results on the CICIoT2023 data set demonstrate the outstanding performance of the proposed framework.Specifically,it achieves an intrusion detection accuracy of 81.09%in highly non-IID scenarios,showcasing a well-balanced trade-off between computational efficiency and performance enhancement.展开更多
基金supported by the National Natural Science Foundation of China(No.U2433214)。
文摘Shenzhen,a major city in southern China,has experienced rapid advancements in Unmanned Aerial Vehicle(UAV)technology,resulting in extensive logistics networks with thousands of daily flights.However,frequent disruptions due to its subtropical monsoon climate,including typhoons and gusty winds,present ongoing challenges.Despite the growing focus on operational costs and third-party risks,research on low-altitude urban wind fields remains scarce.This study addresses this gap by integrating wind field analysis into UAV path planning,introducing key innovations to the classical model.First,UAV wind resistance and turbulence constraints are analyzed,mapping high-wind-speed and turbulence-prone zones in the airspace.Second,wind dynamics are incorporated into path planning by considering airspeed and groundspeed variation,optimizing waypoint selection and flight speed adjustments to improve overall energy efficiency.Additionally,a wind-aware Theta*algorithm is proposed,leveraging wind vectors to expedite search process,while Computational Fluid Dynamics(CFD)techniques are employed to calculate wind fields.A case study of Shenzhen,examining wind patterns over the past decade,demonstrates a 6.23%improvement in groundspeed and a 7.69%reduction in energy consumption compared to wind-agnostic models.This framework advances UAV logistics by enhancing route safety and energy efficiency,contributing to more cost-effective operations.
基金supported by State Key Laboratory for Geomechanics and Deep Underground Engineering,China University of Mining&Technology,Beijing(Grant No.SKLGDUEK2120)。
文摘The deformation characteristics and thermal response of anchor rods are crucial for ensuring the stability and safety of surrounding rock support structures.However,existing research has predominantly concentrated on the mechanical performance of anchor rods,with limited attention to the coupled evolution of strain and temperature fields during tensile deformation.This knowledge gap hinders a comprehensive understanding of the synergistic mechanical-thermal response mechanisms in anchor rods under loading conditions.To address this limitation,the present study systematically investigated the evolution of strain and temperature fields,along with their correlation,during the test of micro-negative Poisson's ratio(NPR)and ordinary Poisson's ratio(PR)anchor rods.Digital image correlation(DIC)and infrared thermography(IRT)techniques were employed for this exploration.The uniaxial tensile tests were conducted at two different rates,and the ordinary PR anchor rod(Q235 anchor rod)was established as a control group for comparative analysis.The findings reveal that the micro-NPR anchor rod exhibit strain localization at multiple locations during the tensile process,whereas Q235 anchors show local strain concentration in only one region.The standard deviation evolution curves for both the strain and temperature field exhibit two distinct phases in the two anchor rods.The evolution patterns between these two types of curves are basically consistent.The two standard deviation curves for the micro-NPR anchor rod display a wavy increase in the second phase,while for the Q235 anchor rod,they increase steadily until the specimen is damaged.The correlation analysis reveals that the standard deviations of strain and temperature differences for both types of anchor rods are significantly correlated.These findings demonstrate the synergistic evolution mechanism of deformation and thermal response,providing a potential foundation for utilizing thermal monitoring to assess the stability of rock support structures.
基金supported by the National Key Research and Development Program of China(Grant Nos.2024YFA1611100,2023YFA1406100,and 2018YFA0704201)the Systematic Fundamental Research Program Leveraging Major Scientific and Technological Infrastructure,Chinese Academy of Sciences(Grant No.JZHKYPT-2021-08)+1 种基金the National Natural Science Foundation of China(Grant Nos.11704385,11874359,and 12274444)the Strategic Priority Research Program(B)of the Chinese Academy of Sciences(Grant No.XDB25000000)。
文摘Temperature-dependent resistivity,upper critical field H_(c2)and its anisotropy in overdoped superconducting Ba_(1-x)K_x Fe_2As_2(x=0.6-1)single crystals have been measured in steady magnetic fields up to 44 T and low temperatures down to 0.4 K.Analysis using both the quadratic term and power-law fitting demonstrates that the in-plane resistivityρ_(ab)(T)progressively approaches the Fermi-liquid T~2behavior with increasing K doping and reaches a saturation plateau at x≈0.8.The temperature dependence of both H_(c2)^(ab)and H^(c)_(c2)follows the Werthamer-Helfand-Hohenberg model,incorporating orbital and spin paramagnetic effects.For x≤0.8,the orbital effect dominates for H ab,while the Pauli paramagnetic effect prevails for H c.For x>0.8,the Pauli paramagnetic effect becomes dominant in both crystallographic directions.The anisotropy of H_(c2)(0)exhibits a discontinuity in its dependence on K doping concentration with a significant enhancement at x=0.8 and a maximum at x=0.9.These experimental results indicate that the electron correlation effect is enhanced in the heavily overdoped Ba_(1-x)K_(x)Fe_(2)As_(2)system where the underlying symmetries are broken due to the Fermi surface reconstruction before x=0.9.
基金supported by the Jilin Science and Technology Development Plan (20240101029JJ) for the following study:synchronized high-speed detection of surface shape and defects in the grinding stage of complex surfaces (KLMSZZ202305)for the high-precision wide dynamic large aperture optical inspection system for fine astronomical observation by the National Major Research Instrument Development Project (62127901)+2 种基金for ultrasmooth manufacturing technology of large diameter complex curved surface by the National Key R&D Program(2022YFB3403405)for research on the key technology of rapid synchronous detection of surface shape and subsurface defects in the grinding stage of large diameter complex surfaces by the International Cooperation Project(2025010157)The Key Laboratory of Optical System Advanced Manufacturing Technology,Chinese Academy of Sciences (2022KLOMT02-04) also supported this study
文摘To address the challenges of high-precision optical surface defect detection,we propose a novel design for a wide-field and broadband light field camera in this work.The proposed system can achieve a 50°field of view and operates at both visible and near-infrared wavelengths.Using the principles of light field imaging,the proposed design enables 3D reconstruction of optical surfaces,thus enabling vertical surface height measurements with enhanced accuracy.Using Zemax-based simulations,we evaluate the system’s modulation transfer function,its optical aberrations,and its tolerance to shape variations through Zernike coefficient adjustments.The results demonstrate that this camera can achieve the required spatial resolution while also maintaining high imaging quality and thus offers a promising solution for advanced optical surface defect inspection.
基金supported by the National Natural Science Foundation of China(Grant Nos.11804348,11775056,11975154,12225505,and 12405281)the Science Challenge(Project No.TZ2018005)+2 种基金supported by the Shanghai Pujiang Program(Grant No.23PJ1414600)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB0890203)supported by the Accelerator Technology Helmholtz Infrastructure consortium ATHENA.
文摘The effects of initial spin orientation on the final electron beam polarization in laser wakefield acceleration in a pre-polarized plasma are investigated theoretically and numerically.From the results of variation of the initial spin direction,the spin dynamics of the electron beam are found to depend on the self-injection mechanism.The effects of wakefields and laser fields are studied using test particle dynamics and particle-in-cell simulations based on the Thomas-Bargmann-Michel-Telegdi equation.Compared with transverse injection,longitudinal injection is found to be preferable for obtaining a highly polarized electron beam.
基金supported by the NSF of China(Nos.22579102 and 22405160)the Natural Science Foundation of Hubei Province(2024AFB288)+2 种基金the Natural Science Research Project of Yichang City(Grant A25-3-007)the 111 Project(D20015)the Key Project Foundation of Hubei Three Gorges Laboratory(SC250009)。
文摘Innovative S-scheme heterostructures face intrinsic limitations in charge separation due to insufficient interfacial driving forces.This work pioneers a dual-vacancy engineering strategy to break this bottleneck,constructing a plasmonic ZnIn_(2)S_(4-x)MoO_(3-x)(ZIS/MO)S-scheme heterojunction where oxygen and sulfur vacancies synergistically reconfigure charge transfer dynamics via dual-path modulation.Uniquely,sulfur vacancies amplify the built-in electric field(IEF)intensity by enlarging the Fermi level gap,while oxygen and sulfur dual-vacancies induce localized surface plasmon resonance(LSPR)via free-carrier concentration enhancement.Simultaneously,sulfur vacancies lower the H^(*)adsorption barrier,and dual vacancies amplify photothermal conversion by promoting nonradiative decay,accelerating temperature elevation and kinetics.Electron dynamics confirm that this dual-vacancy synergy prolongs charge carrier lifetime by a factor of 5.23.Consequently,the optimized sulfur vacancy-rich ZnIn_(2)S_(4-x)/MoO_(3-x)(R-ZIS/MO)exhibits remarkable photocatalytic hydrogen production rates of 3.60 mmol g^(-1) h^(-1)under visible light and 22.74 mmol g^(-1) h^(-1) under full-spectrum irradiation,representing 7.8-fold and17.2-fold enhancements,respectively.This study establishes a new paradigm.Targeted dual-vacancy coordination in plasmonic heterostructures enables unprecedented IEF-LSPR co-modulation,opening avenues for high-efficiency solar energy conversion.
基金Supported by The Eye Hospital of Wenzhou Medical University(No.KYQD20220304)The Fifth Batch of Provincial Ten Thousand Personnel Program Outstanding Talents Funding(No.474092204)+1 种基金Innovative Talents and Teams(2024)-The Fifth Batch of Funding Funds for Scientific and Technological Innovation Leading Talents Under the Provincial Ten Thousand Personnel Program(No.4240924003G)The Key R&D Program of Zhejiang(No.2022C03112).
文摘AIM:To identify early biomarkers associated with glaucomatous visual field(VF)progression in patients with normal-tension glaucoma(NTG).METHODS:This study included patients were divided into two groups based on disease progression status.Tear samples were collected for proteomic analysis.Dataindependent acquisition(DIA)mass spectrometry combined with bioinformatic analyses was performed to identify and validate potential protein biomarkers for NTG progression.Additionally,differentially expressed proteins(DEPs)were evaluated using mediating effect models and receiver operating characteristic(ROC)curve analysis.RESULTS:A total of 19 patients(20 eyes)with NTG participated in this study,including 10 patients(4 males and 6 females;10 eyes)in the progression group with mean age of 67.70±9.03y and 10 patients(4 males and 6 females;10 eyes)in the non-progression group with mean age of 68.60±7.58y.A total of 158 significantly differentially expressed proteins were detected.UniProt database annotation identified 3 upregulated proteins and 12 downregulated proteins.Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis showed that these DEPs were mainly enriched in pathways such as oocyte meiosis.Gene Ontology(GO)enrichment analysis revealed functional clusters related to cellular processes.Weighted gene coexpression network analysis(WGCNA)indicated that the core proteins were primarily involved in the neurodegenerationmultiple diseases pathway and cellular processes.Mediating effect analysis identified PRDX4(L)as a potential protein biomarker.ROC curve analysis showed that GNAI1 had the largest area under the curve(AUC=0.889).CONCLUSION:This study identifies 15 differentially expressed proteins in the tear fluid of NTG patients,including PRDX4(L).PRDX4(L)plays a key role in oxidative stress.
基金Open Access funding enabled and organized by Projekt DEAL.
文摘A solenoid is typically used in normally conducting and superconducting radio frequency(SRF)photoinjectors to compensate for the projected transverse beam emittance.In the ELBE SRF Gun-Ⅱ,a superconducting solenoid is positioned inside the gun cryomodule approximately 0.7 m from the end of the gun cavity.The spherical aberration and multipole field effects caused by offset and tilt limit the reduction in beam emittance for high bunch charges.We designed a novel superconducting(SC)solenoid with a lower spherical aberration coefficient.In the simulation,the beam emittance from the spherical aberration decreased by 47%.Both the longitudinal and transverse fields were measured and analyzed using the formalism fitting method to assess the performance of the SC solenoid within the cryomodule and its influence on the beam transverse emittance.
基金supported by the National Natural Science Foundation of China(22375101)the Natural Science of Colleges and Universities in Jiangsu Province(24KJB430027).
文摘Background:The bacterial biofilm poses a significant challenge to traditional antibiotic therapy.There is a great need to develop novel antibiofilm agents combined with biofilm disrupting and bacteria-killing without the dependence of antibiotic.Methods:Herein,we prepared ultrasound/magnetic field-responsive ferroferric oxide nanoparticles(Fe_(3)O_(4))/glucose oxidase microbubbles(FGMB)to form a cascade catalytic system for effective removing methicillin-resistant Staphylococcus aureus biofilms.FGMB were prepared through interfacial self-assembly of Fe_(3)O_(4) nanoparticles(NPs)and glucose oxidase(GOx)at the gas-liquid interface stabilized by surfactants.Under ultrasound/magnetic field stimulation,FGMB disrupted biofilm architecture through microbubble collapse-induced microjets and magnetically driven displacement.Simultaneously,ultrasound-triggered rupture of FGMB released GOx and Fe_(3)O_(4) NPs.Glucose can be oxidized by GOx to generate gluconic acid and hydrogen peroxide which was subsequently catalyzed into hydroxyl radicals by Fe_(3)O_(4) NPs,enabling chemical eradication of biofilm-embedded bacteria.Results:Optical microscopy images demonstrated that FGMB have spherical structure with average size of approximately 17μm.FGMB showed a 65.4%decrease in methicillin-resistant Staphylococcus aureus biofilm biomass and 1.1 log bacterial inactivation efficiency(91.2%),suggesting effective biofilm elimination.In vitro experimental results also indicate that FGMB have good biocompatibility.Conclusion:This antibiofilm strategy integrated dual modes of physical biofilm disruption with chemical bacteria-killing shows great potential as a versatile,non-resistant strategy for bacterial biofilm elimination.
基金supported by the National Natural Science Foundation of China(No.22278156)the Guangdong Special Support Program Project(No.2021JC060580)+1 种基金the Young Elite Scientists Sponsorship Program by CAST-Doctoral Student Special Plan,the China Scholarship Council Program(No.202406150148)the Natural Science Foundation of Guangdong Province(No.2023A1515011186).
文摘Peroxymonosulfate(PMS)-based advanced oxidation processes(AOPs)are an effective way to remove emerging contaminants(ECs)from water.The catalytic process involving PMS is hindered by the suboptimal electron trans-fer efficiency of current catalysts,the further application of AOPs technology is limited.Here,it is proposed that the interfacial electric field can be controlled by bor(B)-doped FeNC catalysts,which shows significant advantages in the efficient generation,release and participation of reactive oxygen species(ROS)in the reaction.The super exchange interaction between Fe sites and N and B sites is realized through the directional transfer of electrons in the interfacial electric field,which ensures the high efficiency and stability of the PMS catalytic process.B doping increases the d orbitals distribution at Fermi level,which facilitates enhanced electron transition activity,thereby promoting the effective generation of (1)^O_(2).At the same time,orbital hybridization causes the center of the d band to move to a lower energy level,which not only contributes to the desorption process of (1)^O_(2),but also accelerates its release.In addition,B-doping also improved the adsorption capacity of organic pollutants and shortened the migration distance of ROS,thereby significantly improving the degradation efficiency of ECs.The B-doping strategy outlined offers a novel approach to the development of FeNC catalysts,it lays a theoretical foundation and offers technical insights for the integration of PMS/AOPs technology in the ECs management.
基金supported by the Singapore Ministry of Education through MOE Tier 2 grant(MOE-T2EP10223-0006)the Australia Research Council(DP190100150,DE250100232)+2 种基金Singapore-International Synchrotron Access Programme(SG-SAP)the funding support from the RIE 2025 Industry Alignment FundIndustry Collaboration Projects(IAF-ICP)(Award I2301E0023),administered by A*STARsupported by Nanofilm Technologies International Limited。
文摘The spin-sensitive nature of redox reactions in energy conversion systems,such as the oxygen evolution reaction(OER),has attracted increasing attention due to its potential for enhancing catalytic efficiency.Magnetic fields(MFs)have been proposed to enhance OER performance by influencing the spin states of oxygen intermediates.However,prior study has predominantly focused on MF effects mediated by the intrinsic magnetic properties of electrocatalysts or magnetohydrodynamics.In this work,we report a universal enhancement in OER activity,achieving over 150% increase in current density under a200 mT MF across diamagnetic,paramagnetic and magnetic electrocatalysts in 1 M KOH.Through systematic investigation of MF orientation and strength,pH,applied potentials,and the use of benzoquinone radical scavenger,we demonstrate that MF-driven performance improvements arise from direct modulation of oxygen radical spin states.Specifically,MFs promote the formation of spin-triplet oxygen intermediates(↑O–O↑),a critical step for O–O bond formation,independent of the catalyst's intrinsic magnetism.However,the local magnetic environment near the catalyst surface,governed by its magnetic properties,indirectly influences radical spin dynamics by alternating the effective field experienced by intermediates.These findings redefine the role of spin manipulation in electrocatalysis,advancing understanding of MF-driven spin effects in redox reactions.
基金funded by the Ministry of Higher Education through Universiti Putra Malaysia(UPM)under Grant FRGS/1/2023/STG07/UPM/02/4.
文摘Detecting geomagnetic anomalies preceding earthquakes is a challenging yet promising area of research that has gained increasing attention in recent years.This study introduces a novel reconstruction-based modeling approach enhanced by negative learning,employing a Bidirectional Long Short-Term Memory(BiLSTM)network explicitly trained to accurately reconstruct non-seismic geomagnetic signals while intentionally amplifying reconstruction errors for seismic signals.By penalizing the model for accurately reconstructing seismic anomalies,the negative learning approach effectively magnifies the differences between normal and anomalous data.This strategic differentiation enhances the sensitivity of the BiLSTM network,enabling improved detection of subtle geomagnetic anomalies that may serve as earthquake precursors.Experimental validation clearly demonstrated statistically significant higher reconstruction errors for seismic signals compared to non-seismic signals,confirmed through the Mann-Whitney U test with a p-value of 0.0035 for Root Mean Square Error(RMSE).These results provide compelling evidence of the enhanced anomaly detection capability achieved through negative learning.Unlike traditional classification-based methods,negative learning explicitly encourages sensitivity to subtle precursor signals embedded within complex geomagnetic data,establishing a robust basis for further development of reliable earthquake prediction methods.
基金funded by the National Natural Science Foundation of China under Grant No.11972086the Fundamental Research Funds for the Central Universities。
文摘Metal additive manufacturing(AM)technology has promising applications across many fields due to its near-net-shape advantages.The quality of the as-built component is closely linked to the temperature evolution during the metal AM process,which exhibits strong nonlinearities,localized high gradients,and rapid cooling rates.Therefore,real-time prediction of the temperature field is essential for effective online process control to achieve high fabrication quality,which poses surprising challenges for numerical methods,as traditional methods suffer from the inherent time-consuming nature of fine time-space discretizations.In this study,we proposed an isothermal surface imaging and transfer learning framework for fast prediction of isothermal surfaces,which are further used to reconstruct the high-dimensional,nonlinear temperature field.It consists of three key parts:physics-guided isothermal surface imaging to reduce the problem dimensionality by transforming the unstructured temperature field into a series of structured grayscale images,a pre-trained hybrid parameter-to-image generative neural network for the isothermal surface prediction in favor of small training samples,and a transfer learning strategy leveraging physical similarity of these isothermal surfaces in the metal AM process to obtain the 3D temperature field.The training samples are generated using a high-fidelity numerical model,which is validated against experimental data.The predicted results from the proposed framework agree well with those from the high-fidelity numerical simulation for a given combination of process parameters,achieving a computational cost measured in seconds.It is expected that the proposed framework could serve as a powerful tool for predicting the temperature field and further facilitating online control of process parameters.
基金supported by the Doctoral Research Funds for Nanchang HangKong University,China(Grant No.EA202411211)support is gratefully acknowledged.
文摘This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging variogram across various anisotropic modes,providing mathematical models to enhance our understanding of random fields.A new anisotropy index,called LSAI,is introduced to quantify anisotropy based on the autocorrelation length and the orientation of the principal axes within the variogram.An LSAI value closer to one indicates a lower degree of anisotropy.The present study examines how the degree of anisotropy varies with different autocorrelation lengths and angles between the principal axes,providing valuable insights into these relationships.To improve the accuracy of parameter probability distribution estimations,this study integrates limited field test data using a Bayesian inference approach.Additionally,the Markov chain Monte Carlo simulation method is employed to develop a conditional random field(CRF)for the deformation modulus.By incorporating data from field bearing plate tests,the posterior variance data for the deformation modulus are derived.This process facilitates the construction of a detailed and reliable CRF for the deformation modulus.
基金supported by the “Climbing Plan” of Harbin Normal University (No.XKB202301)National Natural Science Foundation of China (Nos.21871065 and 22071038)。
文摘Magnetic field-driven spin polarization modulation has emerged as an effective way to boost the electrocatalytic oxygen evolution reaction(OER).However,the correlation among catalyst structure,magnetic property,and magnetic field enhanced-electrochemical activity remains to be fully elucidated.Herein,single-domain CoFe_(2)O_(4) catalysts with tunable oxygen vacancies(CFO-V_(O)) were synthesized to probe how V_(O) mediates magnetism and OER activity under magnetic field.The introduction of V_(O) can simultaneously modulate saturation magnetization(M_(s)) and coercivity(H_(c)),where the increased M_(s) dominates the magnetic field-enhanced OER activity.Under a 14,000 G magnetic field,the optimized CFO-V_(O) exhibits up to 16.1 % reduction in overpotential and 365 % enhancement in magnetocurrent(MC).Electrochemical analyses and post-OER characterization reveal that the magnetic field synergistically improves OER kinetics through lattice distortion induction,magnetohydrodynamic effect,and spin charge transfer effect.Importantly,the magnetic field promotes additional Co^(3+) generation to compensate for charge imbalance caused by V_(O) filling,maintaining dynamic equilibrium of V_(O) and effective reactant adsorption-conversion processes.This work unveils the synergistic mechanism of V_(O) and magnetic parameters for enhancing OER performance under the magnetic field,providing new insights into the design of high-efficiency spinregulated OER catalysts.
文摘In response to the Ministry of Education’s requirements for building distinctive model software schools,Software College of Northeastern University and Shenzhen Kingdom Technology Co.,Ltd.jointly developed the specialized course“Application and Practice of RPA Technology in FinTech”.Addressing pain points in financial digital transformation,the course integrates robotic process automation(RPA)principles,financial domain knowledge,and RPA platform practice into a“technology-scenario-capability”trinity teaching system.Through 64 credit hours of integrated theory and practice,it covers RPA fundamentals,financial applications,RPA operations(including core skills like Web/desktop automation),and AI integration,cultivating students’ability to design and implement automated financial workflows.It innovatively features a RPA simulation platform,30+financial case studies,and modular task resources,creating a“teacher-machine-student”interactive model.Practice demonstrates the course effectively enhances students’integration of technical application and business acumen,providing a scalable paradigm for cultivating interdisciplinary FinTech talent.
基金supported by the Alexander von Humboldt Foundation,and Deutsche Forschungsgemeinschaft(DFG,German Research Foundation,Project No.506270597 and No.466939224).
文摘A phase-field model including magnetic field induced dendrite fragmentation was established and applied to the cases with different initial crystal nuclear positions for AA5754 aluminum alloy electromagnetic laser beam welding.Compare the calculated results that include dendrite fragmentation caused by the thermal electromagnetic Lorentz force with the results that consider only the thermal electromagnetic Lorentz force,without fragmentation,at the characteristic time instants.Both in the early and late stages,the small fragmentation at the dendrite tip promotes the number of higher-order branches and their growth,especially in the direction perpendicular to the solidification.The later stage fragmentation has the possibility of breaking one grain into several,which verifies the possibility of grain refinement caused by dendrite fragmentation.The fracture surface caused by fragmentation also makes more solid-liquid interfaces and their growth.In addition,the cases with different initial nuclear positions were compared.The grain growth in the low-temperature zone can be inhibited by the equiaxed grains'fragmentation at the high-temperature area(179.8μm^(2) and 14.7% start at the center,115.4μm^(2) and 9.4% start at the high-temperature corner,134.3μm^(2) and 10.9%start at the low-temperature corner),which is another kind of grain refinement by the dendrite fragmentation.This kind of inhibition effect on grain growth in the low-temperature region will be enhanced with the increasing time interval between the two crystal nuclei’appearance(179.8μm^(2) and 14.7%when virtual grains appear at t=4.3803 s and t=4.3803 s,134.3μm^(2) and 10.9%at t=4.0977 s and t=3.9564 s,and 115.4μm^(2) and 9.4%at t=3.8151 s and t=3.5325 s).
文摘Heliostat field design for tower solar thermal plants must jointly address solar geometry,optical losses,and layout optimization under engineering constraints.We develop an end-to-end workflow that(i)adopts a consistent East–North–Up(ENU)convention for all plant-and sun-related vectors;(ii)integrates cosine efficiency,projection-based shading and blocking(SB),atmospheric transmittance,and an HFLCAL(heliostat field local calculation)truncation model into a single optical chain;and(iii)couples an Eliminate-Blocking(EB)layout prior with an improved“Cheetah”metaheuristic to search ring topology,mirror sizes,and heights while enforcing spacing,kinematics,and rated-power requirements.Projection-based SB is calibrated against Monte-Carlo ray tracing at representative sun positions,and the HFLCAL truncation model is used to quantify sensitivities to sunshape and error-budget parameters.In a three-phase study(fixed-size baseline,uniform sizing,heterogeneous sizing),the EB-guided optimizer improves annual per-area output relative to a radial baseline and reliably attains a 60 MW target.Under equal evaluation budgets,the proposed optimizer converges faster and with lower variance than GA-and PSO-based baselines,while respecting panel-level peak-flux limits through a smooth penalization of flux violations.The resulting layouts exhibit outward-increasing azimuthal spacing and ring-wise size sharing that are consistent with recent heliostat-field deployment experience.The framework is modular,auditable,and readily adaptable to alternative receivers,sites,and cost-aware objectives.
基金supported in part by the National Key Research and Development Program of Chinaunder(Grant 2021YFB3101100)in part by the National Natural Science Foundation of Chinaunder(Grant 42461057),(Grant 62272123),and(Grant 42371470)+1 种基金in part by the Fundamental Research Program of Shanxi Province under(Grant 202303021212164)in part by the Postgraduate Education Innovation Program of Shanxi Province under(Grant 2024KY474).
文摘Recently,large-scale deep learning models have been increasingly adopted for point cloud classification.However,thesemethods typically require collecting extensive datasets frommultiple clients,which may lead to privacy leaks.Federated learning provides an effective solution to data leakage by eliminating the need for data transmission,relying instead on the exchange of model parameters.However,the uneven distribution of client data can still affect the model’s ability to generalize effectively.To address these challenges,we propose a new framework for point cloud classification called Federated Dynamic Aggregation Selection Strategy-based Multi-Receptive Field Fusion Classification Framework(FDASS-MRFCF).Specifically,we tackle these challenges with two key innovations:(1)During the client local training phase,we propose a Multi-Receptive Field Fusion Classification Model(MRFCM),which captures local and global structures in point cloud data through dynamic convolution and multi-scale feature fusion,enhancing the robustness of point cloud classification.(2)In the server aggregation phase,we introduce a Federated Dynamic Aggregation Selection Strategy(FDASS),which employs a hybrid strategy to average client model parameters,skip aggregation,or reallocate local models to different clients,thereby balancing global consistency and local diversity.We evaluate our framework using the ModelNet40 and ShapeNetPart benchmarks,demonstrating its effectiveness.The proposed method is expected to significantly advance the field of point cloud classification in a secure environment.
基金National Science Foundation Project of China(62436004,62372317)National Key Research and Development Program of China(2023YFC3331702)。
文摘In the dispersed computing environment driven by intelligent networks,intrusion detection faces significant challenges.This paper proposes a multilayer decentralized federated learning framework based on mean field game theory(MFG-DFL).The framework organizes networked computing points(NCPs)into a three-layer collaborative architecture,and innovatively introduces MFG theory to model the complex dynamic interactions,which among large-scale NCPs as a game between a representative NCP and the mean field.By solving the coupled HJB and FPK equations,we design a dynamic incentive mechanism to fairly quantify and reward NCP contributions,thus aligning individual rationality with the global objectives of the system.The simulation results on the CICIoT2023 data set demonstrate the outstanding performance of the proposed framework.Specifically,it achieves an intrusion detection accuracy of 81.09%in highly non-IID scenarios,showcasing a well-balanced trade-off between computational efficiency and performance enhancement.
