Developing multi-input/multi-output(MIMO)molecular systems for information processing is of great significance in sophisticated human-made and natural processes.Herein,we present a novel design strategy of incorporati...Developing multi-input/multi-output(MIMO)molecular systems for information processing is of great significance in sophisticated human-made and natural processes.Herein,we present a novel design strategy of incorporating two azobenzene derivatives into a lanthanide(Ⅲ)-diethylenetriaminepentaacetate bisamide framework to construct a lanthanide complex-based MIMO molecular system.As a proof of concept,the terbium(Ⅲ)complex(TbL3)exhibits three types of output signals,i.e.,absorption,steadystate fluorescence,and time-resolved luminescence,with multiaddressable states in response to four kinds of input stimuli such as near-infrared light,water,pH,and reducing agent,based on the synergistic effect between Tb(Ⅲ)coordination center and azobenzene moieties.The present work may pave the way for further development of multi-stimuli-responsive lanthanide(Ⅲ)complexes and MIMO molecular systems.展开更多
Single-phase,non-isolated microinverters used in photovoltaic(PV)systems commonly encounter two persistent challenges:High-frequency leakage current and fluctuating power delivery.This paper presents a novel single-ph...Single-phase,non-isolated microinverters used in photovoltaic(PV)systems commonly encounter two persistent challenges:High-frequency leakage current and fluctuating power delivery.This paper presents a novel single-phase,non-isolated,multi-input microinverter topology with a common-ground structure that effectively eliminates ground leakage current without requiring additional active components.The proposed microinverter architecture integrates a dual-boost configuration and uses only four active switches.This is especially advantageous in terms of the component count,which is beneficial to enhance reliability,reduce cost,and simplify the overall system design.With one,two,or four PV inputs,it can operate without interruption under unbalanced voltage or partial shading and even if some inputs drop to zero.A tailored modulation scheme minimizes conduction losses while maintaining a stable direct-current(DC)-link voltage,and a decoupling capacitor efficiently absorbs the single-phase pulsating power,thus overcoming one major limitation in existing microinverter designs.By validating with a 1-kW GaN-based prototype,both the simulated and experimental results demonstrate its high efficiency,robustness,and practical suitability for cost-effective PV applications,with a peak efficiency value of 94.8%.展开更多
This paper proposes a novel multivalued recurrent neural network model driven by external inputs,along with two innovative learning algorithms.By incorporating a multivalued activation function,the proposed model can ...This paper proposes a novel multivalued recurrent neural network model driven by external inputs,along with two innovative learning algorithms.By incorporating a multivalued activation function,the proposed model can achieve multivalued many-to-one associative memory,and the newly developed algorithms enable effective storage of many-to-one patterns in the coefficient matrix while maintaining the indispensability of inputs in many-to-one associative memory.The proposed learning algorithm addresses a critical limitation of existing models which fail to ensure completely erroneous outputs when facing partial input missing in many-to-one associative memory tasks.The methodology is rigorously derived through theoretical analysis,incorporating comprehensive verification of both the existence and global exponential stability of equilibrium points.Demonstrative examples are provided in the paper to show the effectiveness of the proposed theory.展开更多
WE observe that the response speed of a linear timeinvariant system to a step reference input depends not only on the system parameters but also on the magnitude of the step input.Based on this observation,we demonstr...WE observe that the response speed of a linear timeinvariant system to a step reference input depends not only on the system parameters but also on the magnitude of the step input.Based on this observation,we demonstrate a method to schedule the magnitude of the reference input to achieve a faster response.展开更多
The multi-objective optimization problems,especially in constrained environments such as power distribution planning,demand robust strategies for discovering effective solutions.This work presents the improved variant...The multi-objective optimization problems,especially in constrained environments such as power distribution planning,demand robust strategies for discovering effective solutions.This work presents the improved variant of the Multi-population Cooperative Constrained Multi-Objective Optimization(MCCMO)Algorithm,termed Adaptive Diversity Preservation(ADP).This enhancement is primarily focused on the improvement of constraint handling strategies,local search integration,hybrid selection approaches,and adaptive parameter control.Theimproved variant was experimented on with the RWMOP50 power distribution systemplanning benchmark.As per the findings,the improved variant outperformed the original MCCMO across the eleven performance metrics,particularly in terms of convergence speed,constraint handling efficiency,and solution diversity.The results also establish that MCCMOADP consistently delivers substantial performance gains over the baseline MCCMO,demonstrating its effectiveness across performancemetrics.The new variant also excels atmaintaining the balanced trade-off between exploration and exploitation throughout the search process,making it especially suitable for complex optimization problems in multiconstrained power systems.These enhancements make MCCMO-ADP a valuable and promising candidate for handling problems such as renewable energy scheduling,logistics planning,and power system optimization.Future work will benchmark the MCCMO-ADP against widely recognized algorithms such as NSGA-Ⅱ,NSGA-Ⅲ,and MOEA/D and will also extend its validation to large-scale real-world optimization domains to further consolidate its generalizability.展开更多
The complex aerodynamic interaction between tandem tilt-wing and multi-rotor directly affects the wing surface flow and rotor thrust,making it a critical factor during the tilt transition process of this configuration...The complex aerodynamic interaction between tandem tilt-wing and multi-rotor directly affects the wing surface flow and rotor thrust,making it a critical factor during the tilt transition process of this configuration of rotorcraft.The aerodynamic interaction of tandem tilt-wing and multi-rotor is investigated based on the CFD method.The aerodynamic effect of multi tilt-rotor is simulated as virtual disk modeling by adding source terms to the Navier-Stokes equations,effectively reducing the calculation time while maintaining the accuracy of aerodynamic interaction calculations.Aerodynamic forces and flow field characteristics of the tandem tilt-wing and multi-rotor under different tilt angles are compared between cases with and without aerodynamic interaction.Furthermore,the differences in aerodynamic forces between dynamic tilt transition and fixed-angle conditions were compared.The results show that the aerodynamic interaction of multi-rotor obviously increases the lift of front tilt-wing at different tilt angles,the wing lift under interaction is increased by more than 40%compared with isolated wing at tilt angle of 15°for the computation in this paper,which is related to the increase of wing flow velocity and the suppression of flow separation caused by multi-rotor;the wing blocking effect will increase rotor thrust,especially near the tilt angles of 30°and 45°;the increases of rear wing lift and rear rotor thrust under aerodynamic interaction are not significant because of suppression by the front wing’s downwash;the unsteady effects during dynamic tilting have a relatively minor impact on aerodynamic interaction,with the aerodynamic forces on the rotors and wings during the dynamic tilting process showing little difference from those under corresponding fixed tilt angles.展开更多
Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol ...Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol based on zeroing neural networks(ZNNs)is proposed.First,a dynamic linearization data model(DLDM)is acquired via dynamic linearization technology(DLT).展开更多
Low heat input welding is widely used in the industry.The microstructure and toughness of the welded joints under low heat input conditions have received less attention than those under high heat input.The impact toug...Low heat input welding is widely used in the industry.The microstructure and toughness of the welded joints under low heat input conditions have received less attention than those under high heat input.The impact toughness,microstructure and failure mechanisms of the coarse-grain heat-affected zone(CGHAZ)in a micro-alloyed steel were investigated by welding thermal simulation with the heat input ranging from 15 to 65 kJ/cm.The impact toughness of CGHAZ is highly sensitive to variations in low heat input.The failure mechanisms were discussed from the viewpoints of micro-voids formation and micro-cracks propagation.The micro-voids are preferred to be formed and grow at soft phase of grain boundary ferrite(GBF).At the heat inputs no more than 22 kJ/cm,martensite was dominantly formed,and the micro-cracks initiated from the GBF were propagated into the grain interiors,leading to the brittle fracture and low toughness.When the heat input was increased to 31.2 kJ/cm,granular bainite became the dominant constitute,causing cracks to deflect away from GBF and propagate into prior austenite grains.The high density high-angle and low-angle grain boundaries and the presence of retained austenite,effectively restricted the crack propagation,resulting in ductile fracture behavior and enhanced toughness.High heat input(62.3 kJ/cm)promoted coarse GBF formation,providing continuous paths for microcrack propagation.This direct intergranular crack progression caused brittle fracture and low toughness.Industrial cold cracking in the CGHAZ can thus be controlled by heat input optimization to maximize toughness.展开更多
This study integrates explicit input enhancement into comparative continuation writing,defined as a task in which learners produce a continuation by comparing their own expression with an input text,aligning with its ...This study integrates explicit input enhancement into comparative continuation writing,defined as a task in which learners produce a continuation by comparing their own expression with an input text,aligning with its discourse structure and linguistic features,while developing their own ideas.It aims to examine whether English as a Foreign Language(EFL)learners in China exhibit differences in discourse competence and writing performance when completing comparative continuation writing combined with different input enhancement techniques,and whether the alignment effect occurs at the discourse level.Sixty first-year Chinese senior middle school students were divided into four groups:three groups engaged in comparative continuation writing with varying input enhancement,achieved by combining different techniques,while a control group performed a designated-topic writing task.The results revealed that three comparative continuation writing groups outperformed the designated-topic writing group in discourse competence,particularly in the use of temporal connectives.However,differences and some inconsistencies were observed among the comparative continuation writing groups across individual indices.The study highlights effective ways to incorporate comparative continuation writing into English instruction and demonstrates how explicit input enhancement can complement the task,simultaneously activating the alignment effect proposed by the xu-argument and enhancing discourse competence in writing.展开更多
In this paper,we study the issue of controlling a rotating flexible body-beam system(RFBBS)which consists of a tip mass attached to the free-end and a rigid disk attached to the clamped-end of an Euler-Bernoulli beam....In this paper,we study the issue of controlling a rotating flexible body-beam system(RFBBS)which consists of a tip mass attached to the free-end and a rigid disk attached to the clamped-end of an Euler-Bernoulli beam.The boundary control input is affected by both unknown disturbance and nonlinear input backlash.First,the input backlash is considered as desired control input combined with a nonlinear input error,converting it to an external disturbance,and then,the control signal is designed through the energy-based control method.Next,the closed-loop system’s stability is analysed through Lyapunov direct method.Finally,the efficacy of the proposed control scheme is tested through numerical simulations utilizing the finite difference method.展开更多
Researchers are increasingly focused on enabling groups of multiple unmanned vehicles to operate cohesively in complex,real-world environments,where coordinated formation control and obstacle avoidance are essential f...Researchers are increasingly focused on enabling groups of multiple unmanned vehicles to operate cohesively in complex,real-world environments,where coordinated formation control and obstacle avoidance are essential for executing sophisticated collective tasks.This paper presents a Distributed Formation Control and Obstacle Avoidance(DFCOA)framework for multi-unmanned ground vehicles(UGV).DFCOA integrates a virtual leader structure for global guidance,an improved A^(*)path planning algorithm with an advanced cost function for efficient path planning,and a repulsive-force-based improved vector field histogram star(VFH^(*))technique for collision avoidance.The virtual leader generates a reference trajectory while enabling distributed execution;the improved A^(*)algorithm reduces planning time and number of nodes to determine the shortest path from the starting position to the goal;and the improved VFH^(*)uses 2D LiDAR data with inter-agent repulsive force to simultaneously avoid collision with obstacles and maintain safe inter-vehicle distances.The formation stability of the proposed DFCOA reaches 95.8%and 94.6%in two scenarios,with root mean square(RMS)centroid errors of 0.9516 and 1.0008 m,respectively.Velocity tracking is precise(velocity centroid error RMS of 0.2699 and 0.1700 m/s),and linear velocities closely match the desired 0.3 m/s.Safety metrics showed average collision risks of 0.7773 and 0.5143,with minimum inter-vehicle distances of 0.4702 and 0.8763 m,confirming collision-free navigation of four UGVs.DFCOA outperforms conventional methods in formation stability,path efficiency,and scalability,proving its suitability for decentralized multi-UGV applications.展开更多
To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework ba...To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.展开更多
Soil greenhouse gas(GHG)emissions contribute profoundly to global warming;however,how plant detritus input alters GHG emissions is poorly understood.Here,we used detritus input and removal treatments(i.e.,DIRT:control...Soil greenhouse gas(GHG)emissions contribute profoundly to global warming;however,how plant detritus input alters GHG emissions is poorly understood.Here,we used detritus input and removal treatments(i.e.,DIRT:control,CK;double litter,DL;no roots with double litter,NRDL;no litter,NL;no roots,NR;no roots and no litter,NRNL)to assess the effects of litter and root inputs on soil CO_(2),CH_(4),and N_(2)O fluxes in soils in a coniferous(Pinus yunnanensis)and a broad-leaf forest(Quercus pannosa)in a subalpine region in southwestern China.Litter addition increased CO_(2) emissions on average 22.22%,but did not significantly alter CH_(4) uptake and N_(2)O emission compared to the CK.Litter removal(NL and NRNL)significantly reduced CO_(2) emissions on average 30.22%and N_(2)O emissions on average 31.16%from both forest soils,but did not significantly affect soil CH_(4) uptake.Root removal(NR and NRNL)generally decreased these three soil GHG fluxes.Changes inβ-1,4-glucosidase(BG)involved in C and phospholipid fatty acid(PLFAs)biomass were projected to influence CO_(2) emissions,while soil microclimates(temperature and moisture)combined with BG activity mainly regulated CH_(4) uptake.Alterations in dissolved organic nitrogen,microbial biomass nitrogen and BG were mainly responsible for changes in N_(2)O emissions.Interestingly,coniferous forest soil seemed to promote CH_(4) uptake more than the broad-leaf forest soil,but CO_(2) and N_(2)O fluxes were not significantly affected by the forest types.As expected,litter addition significantly increased the warming potential,while litter removal relatively lowered it.These findings revealed the divergent roles of plant detritus input and forest type in shaping soil GHG fluxes,thereby providing insights into forest management and predicting contributions of subalpine forests to global warming.展开更多
The pursuit of simultaneously high wear resistance and excellent lubrication in multi‐principal element alloy(MPEA)composites is often hindered by a fundamental trade‐off,which is exacerbated by the agglomeration of...The pursuit of simultaneously high wear resistance and excellent lubrication in multi‐principal element alloy(MPEA)composites is often hindered by a fundamental trade‐off,which is exacerbated by the agglomeration of high‐content graphene reinforcements.This compromise becomes particularly severe in composites with high‐content graphene reinforcements,whose agglomeration leads to embrittlement and lubrication failure.Here,a flake powder-metallurgy strategy is developed to construct a self‐assembled lamellar structure in graphene/CoCrNi MPEA composites(Gr/MPEA_(AL)).This approach enables the uniform dispersion of a high graphene content(3.0 wt%),which is unattainable by conventional methods.The resulting composite exhibits a rare dual enhancement in performance:an order‐of‐magnitude improvement in wear resistance coupled with a low coefficient of friction.Intriguingly,the tribological behavior shows significant anisotropy,with optimal performance observed when sliding perpendicular to the lamellae.Through a multi‐scale methodology combining molecular dynamics simulations,finite element analysis,and systematic experiments,it is revealed that this exceptional performance stems from the synergy of high‐density deformation nanotwins,efficient strain delocalization,and abundant graphene‐derived lubricating sites.This work establishes a general paradigm for designing composite architectures that reconcile traditionally incompatible properties,offering broad implications for developing next‐generation structural materials with integrated mechanical robustness and surface functionality for safety‐critical applications.展开更多
Phytomelatonin,an emerging plant hormone,plays vital roles in plant growth,development,and stress adaptation(Arnao et al.,2022;Ullah et al.,2024).It acts both as a direct antioxidant and a signaling molecule,engaging ...Phytomelatonin,an emerging plant hormone,plays vital roles in plant growth,development,and stress adaptation(Arnao et al.,2022;Ullah et al.,2024).It acts both as a direct antioxidant and a signaling molecule,engaging complex networks and interacting with other phytohormones(Liu et al.,2022;Khan et al.,2023).Although phytomelatonin receptors(PMTRs)have been identified in many plants(Wei et al.,2018;Wang et al.,2022;Liu et al.,2025),the downstream signaling mechanisms,particularly receptor-mediated protein modifications and transcriptional regulation,remain poorly characterized.展开更多
High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging ...High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging foundation models and multimodal learning frameworks are enabling scalable and transferable representations of cellular states,while advances in interpretability and real-world data integration are bridging the gap between discovery and clinical application.This paper outlines a concise roadmap for AI-driven,transcriptome-centered multi-omics integration in precision medicine(Figure 1).展开更多
Amyotrophic lateral sclerosis(ALS)is a rapidly progressing neurodegenerative disease,leading to muscle weakness,paralysis and ultimately death due to respiratory failure.Currently licensed drugs have only very limited...Amyotrophic lateral sclerosis(ALS)is a rapidly progressing neurodegenerative disease,leading to muscle weakness,paralysis and ultimately death due to respiratory failure.Currently licensed drugs have only very limited effects on slowing down disease progression or biomarkers.Despite numerous successful preclinical analyses,most new drugs fail when translated to clinical trials(Petrov et al.,2017).This is believed to be,in part,due to the multilayer heterogeneity of ALS(e.g.,clinical,genetic,and molecular;Tzeplaeff et al.,2024).Studies integrating multi-omic data are still limited,making it difficult to fully understand the biological complexity that characterizes the disease.展开更多
Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technol...Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technology overcomes the limitations of traditional single-organ models,providing a novel platform for investigating complex disease mechanisms and evaluating drug efficacy and toxicity.Although it demonstrates broad application prospects,its development still faces critical bottlenecks,including inadequate physiological coupling between organs,short functional maintenance durations,and limited real-time monitoring capabilities.Contemporary research is advancing along three key directions,including functional coupling,sensor integration,and full-process automation systems,to propel the technology toward enhanced levels of physiological relevance and predictive accuracy.展开更多
The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measu...The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%.展开更多
New electronic devices based on the physical properties of electrically driven skyrmions are promising for logic computing and nonvolatile memory applications.However,achieving efficient and practical compute-storage ...New electronic devices based on the physical properties of electrically driven skyrmions are promising for logic computing and nonvolatile memory applications.However,achieving efficient and practical compute-storage integration remains challenging owing to the structural complexity,limited functionality,and low flexibility observed in most skyrmion-based devices.In this study,we designed a novel device architecture that integrates seven basic logic gates into a unified physical structure.Their operation can be enabled by physical mechanisms,such as spin-orbit torque,spin-transfer torque,skyrmion-edge repulsions,and skyrmion-skyrmion interactions.Furthermore,by incorporating voltage-controlled magnetic anisotropy,the device achieved multi-input capability and reconfigurability functionality.Ultralow power consumption(<1 fJ/bit per logic function)and extremely high logic density were achieved.Significantly,the compatibility of this nanotrack design with existing skyrmion racetrack memory paves the way for advanced in-memory computing in spintronic architectures.展开更多
基金the financial support from the National Natural Science Foundation of China(Grants:21771105,21973044)the Natural Science Foundation of Jiangsu Province(Grant:BK20170103,BK20211587)the Six Talent Peaks Project in Jiangsu Province(Grant:SWYY-043).
文摘Developing multi-input/multi-output(MIMO)molecular systems for information processing is of great significance in sophisticated human-made and natural processes.Herein,we present a novel design strategy of incorporating two azobenzene derivatives into a lanthanide(Ⅲ)-diethylenetriaminepentaacetate bisamide framework to construct a lanthanide complex-based MIMO molecular system.As a proof of concept,the terbium(Ⅲ)complex(TbL3)exhibits three types of output signals,i.e.,absorption,steadystate fluorescence,and time-resolved luminescence,with multiaddressable states in response to four kinds of input stimuli such as near-infrared light,water,pH,and reducing agent,based on the synergistic effect between Tb(Ⅲ)coordination center and azobenzene moieties.The present work may pave the way for further development of multi-stimuli-responsive lanthanide(Ⅲ)complexes and MIMO molecular systems.
基金supported by Libyan Cultural Affair/London,Libya under Grant No.13840.
文摘Single-phase,non-isolated microinverters used in photovoltaic(PV)systems commonly encounter two persistent challenges:High-frequency leakage current and fluctuating power delivery.This paper presents a novel single-phase,non-isolated,multi-input microinverter topology with a common-ground structure that effectively eliminates ground leakage current without requiring additional active components.The proposed microinverter architecture integrates a dual-boost configuration and uses only four active switches.This is especially advantageous in terms of the component count,which is beneficial to enhance reliability,reduce cost,and simplify the overall system design.With one,two,or four PV inputs,it can operate without interruption under unbalanced voltage or partial shading and even if some inputs drop to zero.A tailored modulation scheme minimizes conduction losses while maintaining a stable direct-current(DC)-link voltage,and a decoupling capacitor efficiently absorbs the single-phase pulsating power,thus overcoming one major limitation in existing microinverter designs.By validating with a 1-kW GaN-based prototype,both the simulated and experimental results demonstrate its high efficiency,robustness,and practical suitability for cost-effective PV applications,with a peak efficiency value of 94.8%.
基金supported by the National Natural Science Foundation of China(Grant Nos.62376105,12101208,and 61906072)the Fundamental Research Funds for the Central Universities(Grant No.2662022XXQD001).
文摘This paper proposes a novel multivalued recurrent neural network model driven by external inputs,along with two innovative learning algorithms.By incorporating a multivalued activation function,the proposed model can achieve multivalued many-to-one associative memory,and the newly developed algorithms enable effective storage of many-to-one patterns in the coefficient matrix while maintaining the indispensability of inputs in many-to-one associative memory.The proposed learning algorithm addresses a critical limitation of existing models which fail to ensure completely erroneous outputs when facing partial input missing in many-to-one associative memory tasks.The methodology is rigorously derived through theoretical analysis,incorporating comprehensive verification of both the existence and global exponential stability of equilibrium points.Demonstrative examples are provided in the paper to show the effectiveness of the proposed theory.
文摘WE observe that the response speed of a linear timeinvariant system to a step reference input depends not only on the system parameters but also on the magnitude of the step input.Based on this observation,we demonstrate a method to schedule the magnitude of the reference input to achieve a faster response.
文摘The multi-objective optimization problems,especially in constrained environments such as power distribution planning,demand robust strategies for discovering effective solutions.This work presents the improved variant of the Multi-population Cooperative Constrained Multi-Objective Optimization(MCCMO)Algorithm,termed Adaptive Diversity Preservation(ADP).This enhancement is primarily focused on the improvement of constraint handling strategies,local search integration,hybrid selection approaches,and adaptive parameter control.Theimproved variant was experimented on with the RWMOP50 power distribution systemplanning benchmark.As per the findings,the improved variant outperformed the original MCCMO across the eleven performance metrics,particularly in terms of convergence speed,constraint handling efficiency,and solution diversity.The results also establish that MCCMOADP consistently delivers substantial performance gains over the baseline MCCMO,demonstrating its effectiveness across performancemetrics.The new variant also excels atmaintaining the balanced trade-off between exploration and exploitation throughout the search process,making it especially suitable for complex optimization problems in multiconstrained power systems.These enhancements make MCCMO-ADP a valuable and promising candidate for handling problems such as renewable energy scheduling,logistics planning,and power system optimization.Future work will benchmark the MCCMO-ADP against widely recognized algorithms such as NSGA-Ⅱ,NSGA-Ⅲ,and MOEA/D and will also extend its validation to large-scale real-world optimization domains to further consolidate its generalizability.
基金supported by the National Key Laboratory of Helicopter Aeromechanics Fund(No.2024-CXPT-GF-JJ-093-05).
文摘The complex aerodynamic interaction between tandem tilt-wing and multi-rotor directly affects the wing surface flow and rotor thrust,making it a critical factor during the tilt transition process of this configuration of rotorcraft.The aerodynamic interaction of tandem tilt-wing and multi-rotor is investigated based on the CFD method.The aerodynamic effect of multi tilt-rotor is simulated as virtual disk modeling by adding source terms to the Navier-Stokes equations,effectively reducing the calculation time while maintaining the accuracy of aerodynamic interaction calculations.Aerodynamic forces and flow field characteristics of the tandem tilt-wing and multi-rotor under different tilt angles are compared between cases with and without aerodynamic interaction.Furthermore,the differences in aerodynamic forces between dynamic tilt transition and fixed-angle conditions were compared.The results show that the aerodynamic interaction of multi-rotor obviously increases the lift of front tilt-wing at different tilt angles,the wing lift under interaction is increased by more than 40%compared with isolated wing at tilt angle of 15°for the computation in this paper,which is related to the increase of wing flow velocity and the suppression of flow separation caused by multi-rotor;the wing blocking effect will increase rotor thrust,especially near the tilt angles of 30°and 45°;the increases of rear wing lift and rear rotor thrust under aerodynamic interaction are not significant because of suppression by the front wing’s downwash;the unsteady effects during dynamic tilting have a relatively minor impact on aerodynamic interaction,with the aerodynamic forces on the rotors and wings during the dynamic tilting process showing little difference from those under corresponding fixed tilt angles.
基金supported by the National Nature Science Foundation of China(U21A20166)the Science and Technology Development Foundation of Jilin Province(20230508095RC)+2 种基金the Major Science and Technology Projects of Jilin Province and Changchun City(20220301033GX)the Development and Reform Commission Foundation of Jilin Province(2023C034-3)the Interdisciplinary Integration and Innovation Project of JLU(JLUXKJC2020202).
文摘Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol based on zeroing neural networks(ZNNs)is proposed.First,a dynamic linearization data model(DLDM)is acquired via dynamic linearization technology(DLT).
基金supported by the National Natural Science Foundation of China(No.51804232)Beijing Municipal Natural Science Foundation(No.2212041)+1 种基金supported by the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities)(FRF-IDRY-20-020)GIMRT Program of the Institute for Materials Research,Tohoku University(202303-RDKGE-0518).
文摘Low heat input welding is widely used in the industry.The microstructure and toughness of the welded joints under low heat input conditions have received less attention than those under high heat input.The impact toughness,microstructure and failure mechanisms of the coarse-grain heat-affected zone(CGHAZ)in a micro-alloyed steel were investigated by welding thermal simulation with the heat input ranging from 15 to 65 kJ/cm.The impact toughness of CGHAZ is highly sensitive to variations in low heat input.The failure mechanisms were discussed from the viewpoints of micro-voids formation and micro-cracks propagation.The micro-voids are preferred to be formed and grow at soft phase of grain boundary ferrite(GBF).At the heat inputs no more than 22 kJ/cm,martensite was dominantly formed,and the micro-cracks initiated from the GBF were propagated into the grain interiors,leading to the brittle fracture and low toughness.When the heat input was increased to 31.2 kJ/cm,granular bainite became the dominant constitute,causing cracks to deflect away from GBF and propagate into prior austenite grains.The high density high-angle and low-angle grain boundaries and the presence of retained austenite,effectively restricted the crack propagation,resulting in ductile fracture behavior and enhanced toughness.High heat input(62.3 kJ/cm)promoted coarse GBF formation,providing continuous paths for microcrack propagation.This direct intergranular crack progression caused brittle fracture and low toughness.Industrial cold cracking in the CGHAZ can thus be controlled by heat input optimization to maximize toughness.
文摘This study integrates explicit input enhancement into comparative continuation writing,defined as a task in which learners produce a continuation by comparing their own expression with an input text,aligning with its discourse structure and linguistic features,while developing their own ideas.It aims to examine whether English as a Foreign Language(EFL)learners in China exhibit differences in discourse competence and writing performance when completing comparative continuation writing combined with different input enhancement techniques,and whether the alignment effect occurs at the discourse level.Sixty first-year Chinese senior middle school students were divided into four groups:three groups engaged in comparative continuation writing with varying input enhancement,achieved by combining different techniques,while a control group performed a designated-topic writing task.The results revealed that three comparative continuation writing groups outperformed the designated-topic writing group in discourse competence,particularly in the use of temporal connectives.However,differences and some inconsistencies were observed among the comparative continuation writing groups across individual indices.The study highlights effective ways to incorporate comparative continuation writing into English instruction and demonstrates how explicit input enhancement can complement the task,simultaneously activating the alignment effect proposed by the xu-argument and enhancing discourse competence in writing.
基金supported in part by the National Natural Science Fundation of China under Grant Nos.62403263 and 62373207in part by the Natural Science Fundation of Qingdao,China under Grant No.24-4-4-zrjj-88-jch+1 种基金in part by the Team Plan for Youth Innovation of Universities in Shandong Province under Grant No.2024KJH148in part by the Foundation of Key Laboratory of Autonomous Systems and Networked Control(South China University of Technology),Ministry of Education under Grant No.2024A01.
文摘In this paper,we study the issue of controlling a rotating flexible body-beam system(RFBBS)which consists of a tip mass attached to the free-end and a rigid disk attached to the clamped-end of an Euler-Bernoulli beam.The boundary control input is affected by both unknown disturbance and nonlinear input backlash.First,the input backlash is considered as desired control input combined with a nonlinear input error,converting it to an external disturbance,and then,the control signal is designed through the energy-based control method.Next,the closed-loop system’s stability is analysed through Lyapunov direct method.Finally,the efficacy of the proposed control scheme is tested through numerical simulations utilizing the finite difference method.
文摘Researchers are increasingly focused on enabling groups of multiple unmanned vehicles to operate cohesively in complex,real-world environments,where coordinated formation control and obstacle avoidance are essential for executing sophisticated collective tasks.This paper presents a Distributed Formation Control and Obstacle Avoidance(DFCOA)framework for multi-unmanned ground vehicles(UGV).DFCOA integrates a virtual leader structure for global guidance,an improved A^(*)path planning algorithm with an advanced cost function for efficient path planning,and a repulsive-force-based improved vector field histogram star(VFH^(*))technique for collision avoidance.The virtual leader generates a reference trajectory while enabling distributed execution;the improved A^(*)algorithm reduces planning time and number of nodes to determine the shortest path from the starting position to the goal;and the improved VFH^(*)uses 2D LiDAR data with inter-agent repulsive force to simultaneously avoid collision with obstacles and maintain safe inter-vehicle distances.The formation stability of the proposed DFCOA reaches 95.8%and 94.6%in two scenarios,with root mean square(RMS)centroid errors of 0.9516 and 1.0008 m,respectively.Velocity tracking is precise(velocity centroid error RMS of 0.2699 and 0.1700 m/s),and linear velocities closely match the desired 0.3 m/s.Safety metrics showed average collision risks of 0.7773 and 0.5143,with minimum inter-vehicle distances of 0.4702 and 0.8763 m,confirming collision-free navigation of four UGVs.DFCOA outperforms conventional methods in formation stability,path efficiency,and scalability,proving its suitability for decentralized multi-UGV applications.
基金supported by the confidential research grant No.a8317。
文摘To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.
基金supported by the National Natural Science Foundation of China(32130069)the National Key Research and Development Program of China(2024YFF1306700)the Scientific Research Foundation of Education Department of Yunnan Province(2024Y004).
文摘Soil greenhouse gas(GHG)emissions contribute profoundly to global warming;however,how plant detritus input alters GHG emissions is poorly understood.Here,we used detritus input and removal treatments(i.e.,DIRT:control,CK;double litter,DL;no roots with double litter,NRDL;no litter,NL;no roots,NR;no roots and no litter,NRNL)to assess the effects of litter and root inputs on soil CO_(2),CH_(4),and N_(2)O fluxes in soils in a coniferous(Pinus yunnanensis)and a broad-leaf forest(Quercus pannosa)in a subalpine region in southwestern China.Litter addition increased CO_(2) emissions on average 22.22%,but did not significantly alter CH_(4) uptake and N_(2)O emission compared to the CK.Litter removal(NL and NRNL)significantly reduced CO_(2) emissions on average 30.22%and N_(2)O emissions on average 31.16%from both forest soils,but did not significantly affect soil CH_(4) uptake.Root removal(NR and NRNL)generally decreased these three soil GHG fluxes.Changes inβ-1,4-glucosidase(BG)involved in C and phospholipid fatty acid(PLFAs)biomass were projected to influence CO_(2) emissions,while soil microclimates(temperature and moisture)combined with BG activity mainly regulated CH_(4) uptake.Alterations in dissolved organic nitrogen,microbial biomass nitrogen and BG were mainly responsible for changes in N_(2)O emissions.Interestingly,coniferous forest soil seemed to promote CH_(4) uptake more than the broad-leaf forest soil,but CO_(2) and N_(2)O fluxes were not significantly affected by the forest types.As expected,litter addition significantly increased the warming potential,while litter removal relatively lowered it.These findings revealed the divergent roles of plant detritus input and forest type in shaping soil GHG fluxes,thereby providing insights into forest management and predicting contributions of subalpine forests to global warming.
基金supported by Guangdong Basic and Applied Basic Research Foundation(No.2024A1515012378)Natural Science Foundation of China(Nos.52471093,52274367)+3 种基金fund of the State Key Laboratory of Solidification Processing in NPU(No.2025‐QZ‐03)the Practice and Innovation Funds for Graduate Students of Northwestern Polytechnical University(No.PF2025041)Fundamental Research Projects of Science&Technology Innovation and development Plan in Yantai City(No.2024JCYJ099)project(No.ZR2024QE213)supported by Shandong Provincial Natural Science Foundation.
文摘The pursuit of simultaneously high wear resistance and excellent lubrication in multi‐principal element alloy(MPEA)composites is often hindered by a fundamental trade‐off,which is exacerbated by the agglomeration of high‐content graphene reinforcements.This compromise becomes particularly severe in composites with high‐content graphene reinforcements,whose agglomeration leads to embrittlement and lubrication failure.Here,a flake powder-metallurgy strategy is developed to construct a self‐assembled lamellar structure in graphene/CoCrNi MPEA composites(Gr/MPEA_(AL)).This approach enables the uniform dispersion of a high graphene content(3.0 wt%),which is unattainable by conventional methods.The resulting composite exhibits a rare dual enhancement in performance:an order‐of‐magnitude improvement in wear resistance coupled with a low coefficient of friction.Intriguingly,the tribological behavior shows significant anisotropy,with optimal performance observed when sliding perpendicular to the lamellae.Through a multi‐scale methodology combining molecular dynamics simulations,finite element analysis,and systematic experiments,it is revealed that this exceptional performance stems from the synergy of high‐density deformation nanotwins,efficient strain delocalization,and abundant graphene‐derived lubricating sites.This work establishes a general paradigm for designing composite architectures that reconcile traditionally incompatible properties,offering broad implications for developing next‐generation structural materials with integrated mechanical robustness and surface functionality for safety‐critical applications.
基金supported by the grants from the Key Research and Development Program of Xinjiang Uygur autonomous region in China(Grant No.2023B02017)the National Key Research and Development Program of China(Grant No.2024YFD2300703)+1 种基金the financial support from the Beijing Rural Revitalization Agricultural Science and Technology Project(Grant No.NY2401080000),BAIC01-2025the 2115 Talent Development Program of China Agricultural University.
文摘Phytomelatonin,an emerging plant hormone,plays vital roles in plant growth,development,and stress adaptation(Arnao et al.,2022;Ullah et al.,2024).It acts both as a direct antioxidant and a signaling molecule,engaging complex networks and interacting with other phytohormones(Liu et al.,2022;Khan et al.,2023).Although phytomelatonin receptors(PMTRs)have been identified in many plants(Wei et al.,2018;Wang et al.,2022;Liu et al.,2025),the downstream signaling mechanisms,particularly receptor-mediated protein modifications and transcriptional regulation,remain poorly characterized.
文摘High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging foundation models and multimodal learning frameworks are enabling scalable and transferable representations of cellular states,while advances in interpretability and real-world data integration are bridging the gap between discovery and clinical application.This paper outlines a concise roadmap for AI-driven,transcriptome-centered multi-omics integration in precision medicine(Figure 1).
文摘Amyotrophic lateral sclerosis(ALS)is a rapidly progressing neurodegenerative disease,leading to muscle weakness,paralysis and ultimately death due to respiratory failure.Currently licensed drugs have only very limited effects on slowing down disease progression or biomarkers.Despite numerous successful preclinical analyses,most new drugs fail when translated to clinical trials(Petrov et al.,2017).This is believed to be,in part,due to the multilayer heterogeneity of ALS(e.g.,clinical,genetic,and molecular;Tzeplaeff et al.,2024).Studies integrating multi-omic data are still limited,making it difficult to fully understand the biological complexity that characterizes the disease.
基金supported by the Shenzhen Medical Research Fund(Grant No.A2303049)Guangdong Basic and Applied Basic Research(Grant No.2023A1515010647)+1 种基金National Natural Science Foundation of China(Grant No.22004135)Shenzhen Science and Technology Program(Grant No.RCBS20210706092409020,GXWD20201231165807008,20200824162253002).
文摘Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technology overcomes the limitations of traditional single-organ models,providing a novel platform for investigating complex disease mechanisms and evaluating drug efficacy and toxicity.Although it demonstrates broad application prospects,its development still faces critical bottlenecks,including inadequate physiological coupling between organs,short functional maintenance durations,and limited real-time monitoring capabilities.Contemporary research is advancing along three key directions,including functional coupling,sensor integration,and full-process automation systems,to propel the technology toward enhanced levels of physiological relevance and predictive accuracy.
文摘The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%.
基金support from the National Natural Science Foundation of China (Grant No.12474101)support from the National Natural Science Foundation of China (Grant Nos.52272202 and W2421027)support from the National Natural Science Foundation of China (Grant No.52501307)。
文摘New electronic devices based on the physical properties of electrically driven skyrmions are promising for logic computing and nonvolatile memory applications.However,achieving efficient and practical compute-storage integration remains challenging owing to the structural complexity,limited functionality,and low flexibility observed in most skyrmion-based devices.In this study,we designed a novel device architecture that integrates seven basic logic gates into a unified physical structure.Their operation can be enabled by physical mechanisms,such as spin-orbit torque,spin-transfer torque,skyrmion-edge repulsions,and skyrmion-skyrmion interactions.Furthermore,by incorporating voltage-controlled magnetic anisotropy,the device achieved multi-input capability and reconfigurability functionality.Ultralow power consumption(<1 fJ/bit per logic function)and extremely high logic density were achieved.Significantly,the compatibility of this nanotrack design with existing skyrmion racetrack memory paves the way for advanced in-memory computing in spintronic architectures.
