Organic room-temperature phosphorescence(RTP)materials are promising for bioimaging applications due to their tunable structures,excellent biocompatibility,and long-lived luminescence.However,the development of highly...Organic room-temperature phosphorescence(RTP)materials are promising for bioimaging applications due to their tunable structures,excellent biocompatibility,and long-lived luminescence.However,the development of highly efficient organic RTP materials for aqueous systems remains challenging,as the organic phosphorescence is prone to being quenched by the dissolved oxygen in water.Herein,heteroaromatic carboxylic acids serve as ligand vips to construct a series of host-vip composites with nontoxic,dense EDTA-M(M=Ca,Mg,and Al)coordination polymer in water.These composites exhibit ultra-long pure RTP of vip molecules with phosphorescence quantum yield up to 53%,and lifetime up to 589.7 ms,due to the synergistic effect of dual-network structure:a coordinatively cross-linked network of EDTA-M,and a non-covalent bonded network formed by ligands and water molecules.The phosphorescence intensity is more than three times that of the composite with a single coordination network.Notably,the dual-network configuration can form a rigid and dense structure and block the intrusion of external H_(2)O and O_(2) molecules to avoid phosphorescence quenching in water.As a result,the RTP of the composites remains unchanged after 1 month in water.Furthermore,the nanoparticles fabricated from composites and anionic surfactants can be successfully applied in in vivo imaging of mice for the stable RTP in water.This work provides a novel strategy for the development of high-performance RTP materials in aqueous systems.展开更多
Phosphorylated sugars,recognized as central intermediates in carbohydrate metabolism and critical precursors for enzymatic synthesis of rare sugars,face significant technical barriers in their industrialscale producti...Phosphorylated sugars,recognized as central intermediates in carbohydrate metabolism and critical precursors for enzymatic synthesis of rare sugars,face significant technical barriers in their industrialscale production.The multi-enzymatic preparation systems for these compounds inherently accumulate complex impurities,including protein-based catalysts,residual substrates,and oligosaccharide byproducts,posing persistent challenges in product separation and biocatalyst recycling.To address this limitation,we conducted a systematic investigation of ultrafiltration-based separation strategies during the multi-enzyme-catalyzed synthesis of fructose-1,6-bisphosphate(FDP),with particular emphasis on membrane fouling mechanisms.By screening the ultrafiltration membranes,UE020 showed the best performance in the model system,achieving significant separation targets:99.97% retention of bovine serum albumin,FDP/maltodextrin separation coefficient of 7.41,and FDP recovery of 93.63%.An analysis of the components of resistance revealed that concentration polarization induced by maltodextrin was the main factor constituting the resistance,irreversible resistance due to bovine serum albumin was a secondary effect,and the resistance constituted by FDP was negligible.A mitigation strategy employing powdered activated carbon for dynamic membrane formation significantly improved system performance,reducing irreversible resistance by 59.14% and enhancing flux recovery by 20.85%.In this study,ultrafiltration was strategically employed to achieve efficient separation of FDP and enzyme recovery.Significantly,we deciphered the synergistic fouling mechanisms arising from interactions within the multicomponent system containing phosphorylated sugars,oligosaccharides,and proteins.These findings provide a mechanistic framework for scaling up multi-enzymatic systems dedicated to phosphorylated sugar biosynthesis,effectively bridging the gap between laboratory-scale synthesis and industrial implementation.展开更多
In recent years,research on industrial innovation and development has primarily focused on industrial automation and intelligent manufacturing.Within the field of integrating mechatronics and intelligent control,analy...In recent years,research on industrial innovation and development has primarily focused on industrial automation and intelligent manufacturing.Within the field of integrating mechatronics and intelligent control,analyzing the efficient control of mechatronic systems enabled by generative AI for single-chip microcomputers can further highlight the value and significance of promoting AI technology applications.This paper examines the technical characteristics of generative AI in data generation,multimodal fusion,and dynamic adaptation,proposing lightweight model deployment strategies that compress large generative models to a range compatible with single-chip microcomputers,ensuring local real-time inference capabilities.It constructs an edge intelligent control architecture,enabling generative AI to directly participate in decision-making instruction generation,forming a new working system of perception,decision-making,and execution.Additionally,it designs a collaborative optimization training mechanism that leverages federated learning to overcome single-machine data limitations and enhance model generalization performance.At the application level,an intelligent fault prediction system is developed for early identification of equipment anomalies,an adaptive parameter optimization module is constructed for dynamically adjusting control strategies,and a multi-device collaborative scheduling engine is established to optimize production processes,providing technical support for embedded intelligent control in Industry 4.0 scenarios.展开更多
Reconfigurable intelligent surfaces(RISs)with the capability of nearly passive beamforming,have recently sparked considerable interests.This paper presents an energy-efficient discrete phase encoding method for RIS-as...Reconfigurable intelligent surfaces(RISs)with the capability of nearly passive beamforming,have recently sparked considerable interests.This paper presents an energy-efficient discrete phase encoding method for RIS-assisted communication systems.Firstly,the beamforming gain,power consumption and energy efficiency models for the RIS-assisted system are illustrated.On this basis,the discrete phase encoding problem is formulated for the purpose of improving the energy efficiency,under the power constraint and the quality-of-service(QoS)requirement.According to the interrelation between the phase encoding and power consumption,a three-step encoding method is proposed with the capability of customizing the beamforming gain,power consumption,and energy efficiency.Simulation results indicate that the proposed method is capable of achieving a more favorable performance in terms of satisfying the QoS demand,reducing the power consumption,and improving the energy efficiency.Furthermore,two field trials at 35 GHz evidence the superiority performance and feasibility characteristics of the proposed method in real environment.This work may provide a reference for future applications of RIS-assisted system with an energy-efficient manner.展开更多
The integration of Geostationary Earth Orbit(GEO)satellite constellations into Sixth Generation(6G)framework for cellular networks is essential to achieve global connectivity.Despite the major importance of this integ...The integration of Geostationary Earth Orbit(GEO)satellite constellations into Sixth Generation(6G)framework for cellular networks is essential to achieve global connectivity.Despite the major importance of this integration,current research often underestimates the limitations imposed by available satellite payload power,erroneously assuming a uniform maximum power density distribution across all communication beams.In this paper,we propose an Efficient Downlink Resource Allocation scheme(EDRA)that accounts for transmitting power resource limitations,variable service quality demands,and a heterogeneous number of users.Our approach relies on the thorough analysis of real-world demographic data,allowing us to optimize the allocation of downlink power and time-frequency resources in a practical and effective manner.Furthermore,we introduce an optimization model to maximize the total system revenue,using an iterative algorithm specifically designed to solve complex optimization problems.Numerical simulations demonstrated that the EDRA scheme improved the average network revenue by more than 66%relatively to standard methods,with performance gains increasingly large for an increasing diversity of service types,establishing the robustness and adaptability of the proposed EDRA scheme in the rapidly-evolving context of satellite-based communication systems.展开更多
Cloud computing has become an essential technology for the management and processing of large datasets,offering scalability,high availability,and fault tolerance.However,optimizing data replication across multiple dat...Cloud computing has become an essential technology for the management and processing of large datasets,offering scalability,high availability,and fault tolerance.However,optimizing data replication across multiple data centers poses a significant challenge,especially when balancing opposing goals such as latency,storage costs,energy consumption,and network efficiency.This study introduces a novel Dynamic Optimization Algorithm called Dynamic Multi-Objective Gannet Optimization(DMGO),designed to enhance data replication efficiency in cloud environments.Unlike traditional static replication systems,DMGO adapts dynamically to variations in network conditions,system demand,and resource availability.The approach utilizes multi-objective optimization approaches to efficiently balance data access latency,storage efficiency,and operational costs.DMGO consistently evaluates data center performance and adjusts replication algorithms in real time to guarantee optimal system efficiency.Experimental evaluations conducted in a simulated cloud environment demonstrate that DMGO significantly outperforms conventional static algorithms,achieving faster data access,lower storage overhead,reduced energy consumption,and improved scalability.The proposed methodology offers a robust and adaptable solution for modern cloud systems,ensuring efficient resource consumption while maintaining high performance.展开更多
Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2)...Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.展开更多
In rock engineering,natural cracks in rock masses subjected to external loads tend to initiate and propagate,leading to potential safety hazards.To investigate the effect of cracking behavior on the mechanical propert...In rock engineering,natural cracks in rock masses subjected to external loads tend to initiate and propagate,leading to potential safety hazards.To investigate the effect of cracking behavior on the mechanical properties of rocks,the cracking processes of pre-cracked rocks have been extensively studied using numerical modeling methods.The peridynamics(PD)exhibits advantages over other numerical methods due to the absence of the requirements for remeshing and external crack growth criterion.However,for modeling pre-cracked rock cracking processes under impact,current PD implementations lack generally applicable rock constitutive models and impact contact models,which leads to difficulties in determining rock material parameters and efficiently calculating impact loads.This paper proposes a non-ordinary state-based peridynamics(NOSBPD)modeling method integrating the Drucker-Prager(DP)plasticity model and an efficient contact model to address the above problems.In the proposed method,the Drucker-Prager plasticity model is integrated into the NOSBPD,thereby equipping NOSBPD with the capability to accurately characterize the nonlinear stress-strain relationship inherent in rocks.An efficient contact model between particles and meshes is designed to calculate the impact loads,which is essentially a coupling method of PD with the finite element method(FEM).The effectiveness of the proposed NOSBPD modeling method is verified by comparison with other numerical methods and experiments.Experimental results indicate that the proposed method can effectively and accurately predict the 3D cracking processes of pre-cracked cracks under impact loading,and the maximum principal stress is the key driver behind wing crack formation in pre-cracked rocks.展开更多
The personalized fine-tuning of large languagemodels(LLMs)on edge devices is severely constrained by limited computation resources.Although split federated learning alleviates on-device burdens,its effectiveness dimin...The personalized fine-tuning of large languagemodels(LLMs)on edge devices is severely constrained by limited computation resources.Although split federated learning alleviates on-device burdens,its effectiveness diminishes in few-shot reasoning scenarios due to the low data efficiency of conventional supervised fine-tuning,which leads to excessive communication overhead.To address this,we propose Language-Empowered Split Fine-Tuning(LESFT),a framework that integrates split architectures with a contrastive-inspired fine-tuning paradigm.LESFT simultaneously learns frommultiple logically equivalent but linguistically diverse reasoning chains,providing richer supervisory signals and improving data efficiency.This process-oriented training allows more effective reasoning adaptation with fewer samples.Extensive experiments demonstrate that LESFT consistently outperforms strong baselines such as SplitLoRA in task accuracy.LESFT consistently outperforms strong baselines on GSM8K,CommonsenseQA,and AQUA_RAT,with the largest gains observed on Qwen2.5-3B.These results indicate that LESFT can effectively adapt large language models for reasoning tasks under the computational and communication constraints of edge environments.展开更多
Federated learning often experiences slow and unstable convergence due to edge-side data heterogeneity.This problem becomes more severe when edge participation rate is low,as the information collected from different e...Federated learning often experiences slow and unstable convergence due to edge-side data heterogeneity.This problem becomes more severe when edge participation rate is low,as the information collected from different edge devices varies significantly.As a result,communication overhead increases,which further slows down the convergence process.To address this challenge,we propose a simple yet effective federated learning framework that improves consistency among edge devices.The core idea is clusters the lookahead gradients collected from edge devices on the cloud server to obtain personalized momentum for steering local updates.In parallel,a global momentum is applied during model aggregation,enabling faster convergence while preserving personalization.This strategy enables efficient propagation of the estimated global update direction to all participating edge devices and maintains alignment in local training,without introducing extra memory or communication overhead.We conduct extensive experiments on benchmark datasets such as Cifar100 and Tiny-ImageNet.The results confirm the effectiveness of our framework.On CIFAR-100,our method reaches 55%accuracy with 37 fewer rounds and achieves a competitive final accuracy of 65.46%.Even under extreme non-IID scenarios,it delivers significant improvements in both accuracy and communication efficiency.The implementation is publicly available at https://github.com/sjmp525/CollaborativeComputing/tree/FedCCM(accessed on 20 October 2025).展开更多
Understanding the coupling between carbon and water in terrestrial ecosystems is essential for achieving sustainable development.Net primary productivity(NPP),carbon use efficiency(CUE),and water use efficiency(WUE) a...Understanding the coupling between carbon and water in terrestrial ecosystems is essential for achieving sustainable development.Net primary productivity(NPP),carbon use efficiency(CUE),and water use efficiency(WUE) are key indicators for assessing carbon balance and carbon–water interactions.However,knowledge gaps remain regarding how these indicators respond to climate change and interact with one another.This study examined the spatial and temporal dynamics of NPP,CUE,and WUE,as well as their interrelationships,within the Three-North Shelterbelt Forest region of China.Furthermore,the study investigated the driving mechanisms of these indicators using Extreme Gradient Boosting(XGBoost),SHapley Additive ex Planations(SHAP),and Partial Least Squares Structural Equation Modeling(PLS-SEM).The results revealed that from 2000 to 2020,both NPP(2.69 g C/(m^(2)·a);P<0.010) and WUE(0.004 g C/(kg H_(2)O·a);P<0.010) increased significantly,while CUE exhibited a non-significant decline(–5.40×10^(–4)/a;P>0.050) across different climatic zones(arid,semi-arid,humid,and sub-humid) and vegetation types(cropland,forest,grassland,shrubland,and wetland).The correlation between WUE and NPP(correlation coefficient of 0.70) was stronger than that between CUE and NPP(correlation coefficient of 0.15).NPP and WUE were primarily influenced by leaf area index,whereas CUE was most strongly affected by elevation.The relationships between the key drivers and the three indicators were largely nonlinear,with stronger driver contributions corresponding to more pronounced nonlinear interactions.Moreover,these nonlinear relationships were modulated by differences in dry versus wet climatic conditions.Geographical factors(e.g.,longitude,latitude,and elevation) further shaped vegetation characteristics(e.g.,fractional vegetation cover and leaf area index) by regulating climatic variables such as temperature,precipitation,and evapotranspiration,ultimately influencing NPP,WUE,and CUE.This study advances the understanding of vegetation carbon–water coupling and provides a scientific basis for ecosystem management and sustainable development policy-making in various climatic zones.展开更多
Although the certified power conversion efficiency(PCE)of single-junction perovskite solar cells(PSCs)has achieved a high level of 27%,approaching the single-crystalline silicon solar cells,the device stability remain...Although the certified power conversion efficiency(PCE)of single-junction perovskite solar cells(PSCs)has achieved a high level of 27%,approaching the single-crystalline silicon solar cells,the device stability remains an urgent issue to be resolved for the commercialization.Defect passivation emerged as a viable approach to enhance the operational stability of the solar devices.Herein,phenylthiourea(PhTu)derivatives are selected as effective passivation agents to enhance the optoelectronic properties of printed methylammonium lead iodide(MAPbI_(3))films.It is demonstrated that incorporating a small amount of 1-(4-carboxyphenyl)-2-thiourea(PhTu-COOH)significantly reduces the trap-state density and leads to longer carrier lifetime of the perovskite films.As a result,the inverted solar device made of Ph Tu-COOH-modified MAPbI_(3) perovskite film shows remarkably improved efficiency(from 17.29%to 20.22%)and obviously increased open-circuit voltage(V_(OC))(from 1.043 to 1.143 V),as compared with the pristine device.Moreover,the Ph Tu-COOH-modified PSCs exhibit enhanced operational stability due to the significantly reduced trap-state density.Finally,the optimized solar module fabricated with an active area of 11.28 cm^(2) delivers a high PCE of 17.07%with negligible V_(OC)loss,demonstrating the feasibility of the blade-coating method for large-area perovskite film deposition.展开更多
Coal-derived hard carbon(HC)represents a promising anode material for sodium-ion batteries owing to its cost-effectiveness and high carbon yield.However,conventional carbonization induces excessive graphitization,yiel...Coal-derived hard carbon(HC)represents a promising anode material for sodium-ion batteries owing to its cost-effectiveness and high carbon yield.However,conventional carbonization induces excessive graphitization,yielding insufficient interlayer spacing(d_(002)<0.37 nm)and underdeveloped closed pores.Herein,we propose a dynamic crystallization control strategy through carbothermal shock treatment(1300°C,30 s)that decouples thermodynamic and kinetic constraints.This method precisely modulates graphite domain ordering kinetics,producing short-range ordered structures with expanded interlayer spacing(d_(002)=0.385 nm)and homogeneously distributed closed nanopores.Through combined in situ characterization and first-principles calculations,we elucidate a three-stage crystallization mechanism:(i)amorphous carbon transformation,(ii)open-pore collapse,and(iii)pseudo-graphitic ordering.The optimized HC achieves record performance with 88.6%initial Coulombic efficiency and 204 mA h g^(−1)plateau capacity,while its optimal interlayer spacing lowers Na+diffusion barriers to enable exceptional rate capability(221 mA h g^(−1)at 0.5C after 300 cycles).Practical pouch cells maintain 85%capacity retention after 100 cycles at−20°C and deliver 284 Wh kg^(−1)energy density.This work establishes a kinetic regulation paradigm for graphitization-prone precursors,advancing the rational design of high-performance HC anodes.展开更多
With the rapid growth of cloud computing,the number of data centers(DCs)continuously increases,leading to a high-energy consumption dilemma.Cooling,apart from IT equipment,represents the largest energy consumption in ...With the rapid growth of cloud computing,the number of data centers(DCs)continuously increases,leading to a high-energy consumption dilemma.Cooling,apart from IT equipment,represents the largest energy consumption in DCs.Passive design(PD)and active design(AD)are two important approaches in architectural design to reduce energy consumption.However,for DC cooling,few studies have summarized AD,and there are almost no studies on PD.Based on existing international research(2005-2024),this paper summarizes the current state of cooling strategies for DCs.PD encompasses floors,ceilings,and layout and zoning of racks.Additionally,other passive strategies not yet studied in DCs are critically examined.AD includes air,liquid,free,and two-phase cooling.This paper systematically compares the performance of different AD technologies on various KPIs,including energy,economic,and environmental indicators.This paper also explores the application of different cooling design strategies through best-practice examples and presents advanced algorithms for energy management in operational DCs.This study reveals that free cooling is widely employed,with Artificial Neural Networks emerging as the most popular algorithm for managing cooling energy.Finally,this paper suggests four future directions for reducing cooling energy in DCs,with a focus on the development of passive strategies.This paper provides an overview and guide to DC energy-consumption issues,emphasizes the importance of implementing passive and active design strategies to reduce DC cooling energy consumption,and provides directions and references for future energy-efficient DC designs.展开更多
The current study aims to improve the performance of the electrohydraulic servo system(EHSS)by increasing the volumetric efficiency of the pump and reducing electrical power consumption to a minimum value.An experimen...The current study aims to improve the performance of the electrohydraulic servo system(EHSS)by increasing the volumetric efficiency of the pump and reducing electrical power consumption to a minimum value.An experimental setup has been designed and built to control the cylinder position using a programmable logic controller to provide the appropriate motor speed from the AC drive to control the velocity of the hydraulic actuator;the induction motor is driven by an AC drive using a tune proportional-integral-variable frequency drive(TPI-VFD)space vector modulation(SVM)hybrid technology.Theoretically,it was analyzed and simulated by MATLAB,which showed that the starting current was reduced by 81%compared to the traditional system.Also,the settling time of the system decreased to 0.35 s to reach a steady state with a minimum error of 0.03 and an overshoot of 0.3%.On the other hand,the experimental results of the EHSS show that the three-phase induction motor with a closed-loop speed control AC drive with a programmable logic controller PLC based system is the best case for determining the appropriate operating speed.The optimum speed,frequency,and voltage were 1325.3 rpm,46.6 Hz,and 354.16 V.In addition,enhancement is achieved in closed-loop VFD-PLC,where at 6.5 bar pressure and 3.4 LPM flow,the volumetric efficiency after the pump improves to 98.6%while it reaches 96.3%before the cylinder at a flow rate of 3.32 LPM.Finally,in the closed-loop VFD-PLC in the expansion stroke,the rated electrical power consumption of the three-phase IM decreased to 532 W at the speed of 1325.3 rpm,resulting in energy savings of 20.6%.展开更多
Carbazole derivatives with a single phosphonic acid(PA)group are widely used as monolayer interfaces in perovskites and organic solar cells(OSCs).However,their hydrophilic nature renders ITO electrodes hydrophobic,lim...Carbazole derivatives with a single phosphonic acid(PA)group are widely used as monolayer interfaces in perovskites and organic solar cells(OSCs).However,their hydrophilic nature renders ITO electrodes hydrophobic,limiting further applications.In this study,a novel carbazole-based compound functionalized with two PA groups,denoted 2PACz-D1,was designed to create a dual hydrophilic interface.This configuration enables the formation of a bilayer hole-transporting layer(HTL).Specifically,one PA group anchors to the ITO electrode,while the other generates a secondary hydrophilic surface.This allows the subsequent deposition of hydrophilic PEDOT:PSS,forming a protective bilayer HTL that shields ITO from corrosive acidic polymers.The OSCs incorporating this bilayer HTL achieved a power conversion efficiency of 19.44%and exhibited improved thermal stability compared to devices with a single HTL.This work demonstrates the potential of bis-PA carbazole derivatives for tailoring the HTL surface properties,offering promising opportunities for various organic electronic devices.展开更多
UAV-mounted intelligent reflecting surface(IRS)helps address the line-of-sight(LoS)blockage between sensor nodes(SNs)and the fusion center(FC)in Internet of Things(IoT).This paper considers an IoT assisted by multiple...UAV-mounted intelligent reflecting surface(IRS)helps address the line-of-sight(LoS)blockage between sensor nodes(SNs)and the fusion center(FC)in Internet of Things(IoT).This paper considers an IoT assisted by multiple UAVs-mounted IRS(U-IRS),where the data from ground SNs are transmitted to the FC.In practice,energy efficiency(EE)and mission completion time are crucial metrics for evaluating system performance and operational costs.Recognizing their importance during data collection,we formulate a multi-objective optimization problem to maximize EE and minimize total mission completion time simultaneously.To characterize this tradeoff while considering optimization objective consistency,we construct an optimization problem that minimizes the weighted sum of the total mission completion time and the reciprocal of EE.Due to the non-convex nature of the formulated problem,obtaining optimal solutions is generally challenging.To tackle this issue,we decompose it into three subproblems:UAV-SN association,number of reflecting elements allocation,andUAVtrajectory optimization.An iterative algorithmcombining genetic algorithm,CS-BJ algorithm,and successive convex approximation technique is proposed to solve these sub-problems.Simulation results demonstrate that when the transmitted data amount is 10 and 30Mbits,compared to the static collection benchmark(the UAV hovers directly above each SN),the EE of the proposed method improves by more than 10.4% and 5.2%,while the total mission completion time is reduced by more than 5.4% and 3.3%,respectively.展开更多
The technological advancement of the vehicular Internet ofThings(IoT)has revolutionized Intelligent Transportation Systems(ITS)into next-generation ITS.The connectivity of IoT nodes enables improved data availability ...The technological advancement of the vehicular Internet ofThings(IoT)has revolutionized Intelligent Transportation Systems(ITS)into next-generation ITS.The connectivity of IoT nodes enables improved data availability and facilitates automatic control in the ITS environment.The exponential increase in IoT nodes has significantly increased the demand for an energy-efficient,mobility-aware,and secure system for distributed intelligence.This article presents a mobility-aware Deep Reinforcement Learning based Federated Learning(DRL-FL)approach to design an energy-efficient and threat-resilient ITS.In this approach,a Policy Proximal Optimization(PPO)-based DRL agent is first employed for adaptive client selection.Second,an autoencoder-based anomaly detectionmodule is considered for malicious node detection.Results reveal that the proposed framework achieved an 8%higher accuracy increase,and 15%lower energy consumption.Themodel also demonstrates greater resilience under adversarial conditions compared to the state of the art in federated learning.The adaptability of the proposed approach makes it a compelling choice for next-generation vehicular networks.展开更多
Automated essay scoring(AES)systems have gained significant importance in educational settings,offering a scalable,efficient,and objective method for evaluating student essays.However,developing AES systems for Arabic...Automated essay scoring(AES)systems have gained significant importance in educational settings,offering a scalable,efficient,and objective method for evaluating student essays.However,developing AES systems for Arabic poses distinct challenges due to the language’s complex morphology,diglossia,and the scarcity of annotated datasets.This paper presents a hybrid approach to Arabic AES by combining text-based,vector-based,and embeddingbased similarity measures to improve essay scoring accuracy while minimizing the training data required.Using a large Arabic essay dataset categorized into thematic groups,the study conducted four experiments to evaluate the impact of feature selection,data size,and model performance.Experiment 1 established a baseline using a non-machine learning approach,selecting top-N correlated features to predict essay scores.The subsequent experiments employed 5-fold cross-validation.Experiment 2 showed that combining embedding-based,text-based,and vector-based features in a Random Forest(RF)model achieved an R2 of 88.92%and an accuracy of 83.3%within a 0.5-point tolerance.Experiment 3 further refined the feature selection process,demonstrating that 19 correlated features yielded optimal results,improving R2 to 88.95%.In Experiment 4,an optimal data efficiency training approach was introduced,where training data portions increased from 5%to 50%.The study found that using just 10%of the data achieved near-peak performance,with an R2 of 85.49%,emphasizing an effective trade-off between performance and computational costs.These findings highlight the potential of the hybrid approach for developing scalable Arabic AES systems,especially in low-resource environments,addressing linguistic challenges while ensuring efficient data usage.展开更多
Rapidly improving infertile croplands and enhancing their soil organic carbon(SOC)pool necessitate substantial organic materials incorporation.Converting loose crop straw into granulated form facilitates uniform incor...Rapidly improving infertile croplands and enhancing their soil organic carbon(SOC)pool necessitate substantial organic materials incorporation.Converting loose crop straw into granulated form facilitates uniform incorporation within the plough soil layer.As an innovative soil amelioration approach,the efficiency and patterns of SOC accumulation remain unclear.Two field experiments were conducted in infertile subtropical upland and paddy soils with 0,30,60,and 90 Mg ha^(-1)granulated straw incorporation.After one year,SOC accumulation efficiency from straw input remained stable in upland(30.8–37.5%)with increasing amounts of straw incorporation,while declined from 60.0 to 38.3%in paddy.In both croplands,the contributions of lignin phenols to SOC increased with increasing straw incorporation,while the contributions from amino sugars remained constant at higher straw input levels.Subsequently,the ratios of lignin phenols to amino sugars increased with increasing straw incorporation,indicating faster plant residue accumulation compared to microbial necromass,as the granulation approach limited microbial involvement in straw transformation.Thus,single-time incorporation of substantial granulated straw presents an effective agricultural strategy for rapid amelioration of infertile croplands.展开更多
基金supported by the Startup Funds for Introduced Talents of Wuyi University(YJ202304)the National Natural Science Foundation of China(22375044).
文摘Organic room-temperature phosphorescence(RTP)materials are promising for bioimaging applications due to their tunable structures,excellent biocompatibility,and long-lived luminescence.However,the development of highly efficient organic RTP materials for aqueous systems remains challenging,as the organic phosphorescence is prone to being quenched by the dissolved oxygen in water.Herein,heteroaromatic carboxylic acids serve as ligand vips to construct a series of host-vip composites with nontoxic,dense EDTA-M(M=Ca,Mg,and Al)coordination polymer in water.These composites exhibit ultra-long pure RTP of vip molecules with phosphorescence quantum yield up to 53%,and lifetime up to 589.7 ms,due to the synergistic effect of dual-network structure:a coordinatively cross-linked network of EDTA-M,and a non-covalent bonded network formed by ligands and water molecules.The phosphorescence intensity is more than three times that of the composite with a single coordination network.Notably,the dual-network configuration can form a rigid and dense structure and block the intrusion of external H_(2)O and O_(2) molecules to avoid phosphorescence quenching in water.As a result,the RTP of the composites remains unchanged after 1 month in water.Furthermore,the nanoparticles fabricated from composites and anionic surfactants can be successfully applied in in vivo imaging of mice for the stable RTP in water.This work provides a novel strategy for the development of high-performance RTP materials in aqueous systems.
基金the funding support provided by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDC0120402)the National Key Research&Development Program of China (2022YFC2105103)。
文摘Phosphorylated sugars,recognized as central intermediates in carbohydrate metabolism and critical precursors for enzymatic synthesis of rare sugars,face significant technical barriers in their industrialscale production.The multi-enzymatic preparation systems for these compounds inherently accumulate complex impurities,including protein-based catalysts,residual substrates,and oligosaccharide byproducts,posing persistent challenges in product separation and biocatalyst recycling.To address this limitation,we conducted a systematic investigation of ultrafiltration-based separation strategies during the multi-enzyme-catalyzed synthesis of fructose-1,6-bisphosphate(FDP),with particular emphasis on membrane fouling mechanisms.By screening the ultrafiltration membranes,UE020 showed the best performance in the model system,achieving significant separation targets:99.97% retention of bovine serum albumin,FDP/maltodextrin separation coefficient of 7.41,and FDP recovery of 93.63%.An analysis of the components of resistance revealed that concentration polarization induced by maltodextrin was the main factor constituting the resistance,irreversible resistance due to bovine serum albumin was a secondary effect,and the resistance constituted by FDP was negligible.A mitigation strategy employing powdered activated carbon for dynamic membrane formation significantly improved system performance,reducing irreversible resistance by 59.14% and enhancing flux recovery by 20.85%.In this study,ultrafiltration was strategically employed to achieve efficient separation of FDP and enzyme recovery.Significantly,we deciphered the synergistic fouling mechanisms arising from interactions within the multicomponent system containing phosphorylated sugars,oligosaccharides,and proteins.These findings provide a mechanistic framework for scaling up multi-enzymatic systems dedicated to phosphorylated sugar biosynthesis,effectively bridging the gap between laboratory-scale synthesis and industrial implementation.
基金Single-Chip Microcomputer and Interface Technology Project(Project No.:SYSJ2025032)。
文摘In recent years,research on industrial innovation and development has primarily focused on industrial automation and intelligent manufacturing.Within the field of integrating mechatronics and intelligent control,analyzing the efficient control of mechatronic systems enabled by generative AI for single-chip microcomputers can further highlight the value and significance of promoting AI technology applications.This paper examines the technical characteristics of generative AI in data generation,multimodal fusion,and dynamic adaptation,proposing lightweight model deployment strategies that compress large generative models to a range compatible with single-chip microcomputers,ensuring local real-time inference capabilities.It constructs an edge intelligent control architecture,enabling generative AI to directly participate in decision-making instruction generation,forming a new working system of perception,decision-making,and execution.Additionally,it designs a collaborative optimization training mechanism that leverages federated learning to overcome single-machine data limitations and enhance model generalization performance.At the application level,an intelligent fault prediction system is developed for early identification of equipment anomalies,an adaptive parameter optimization module is constructed for dynamically adjusting control strategies,and a multi-device collaborative scheduling engine is established to optimize production processes,providing technical support for embedded intelligent control in Industry 4.0 scenarios.
基金supported in part by the National Natural Science Foundation of China under Grants 62231009 and 62261160576in part by the Fundamental Research Funds for the Central Universities under Grant 2242023K5003in part by the Startup Research Fund of Southeast University under Grant RF1028623267。
文摘Reconfigurable intelligent surfaces(RISs)with the capability of nearly passive beamforming,have recently sparked considerable interests.This paper presents an energy-efficient discrete phase encoding method for RIS-assisted communication systems.Firstly,the beamforming gain,power consumption and energy efficiency models for the RIS-assisted system are illustrated.On this basis,the discrete phase encoding problem is formulated for the purpose of improving the energy efficiency,under the power constraint and the quality-of-service(QoS)requirement.According to the interrelation between the phase encoding and power consumption,a three-step encoding method is proposed with the capability of customizing the beamforming gain,power consumption,and energy efficiency.Simulation results indicate that the proposed method is capable of achieving a more favorable performance in terms of satisfying the QoS demand,reducing the power consumption,and improving the energy efficiency.Furthermore,two field trials at 35 GHz evidence the superiority performance and feasibility characteristics of the proposed method in real environment.This work may provide a reference for future applications of RIS-assisted system with an energy-efficient manner.
基金supported by Young Elite Scientists Sponsorship Program by CAST(No.2022QNRC001)。
文摘The integration of Geostationary Earth Orbit(GEO)satellite constellations into Sixth Generation(6G)framework for cellular networks is essential to achieve global connectivity.Despite the major importance of this integration,current research often underestimates the limitations imposed by available satellite payload power,erroneously assuming a uniform maximum power density distribution across all communication beams.In this paper,we propose an Efficient Downlink Resource Allocation scheme(EDRA)that accounts for transmitting power resource limitations,variable service quality demands,and a heterogeneous number of users.Our approach relies on the thorough analysis of real-world demographic data,allowing us to optimize the allocation of downlink power and time-frequency resources in a practical and effective manner.Furthermore,we introduce an optimization model to maximize the total system revenue,using an iterative algorithm specifically designed to solve complex optimization problems.Numerical simulations demonstrated that the EDRA scheme improved the average network revenue by more than 66%relatively to standard methods,with performance gains increasingly large for an increasing diversity of service types,establishing the robustness and adaptability of the proposed EDRA scheme in the rapidly-evolving context of satellite-based communication systems.
文摘Cloud computing has become an essential technology for the management and processing of large datasets,offering scalability,high availability,and fault tolerance.However,optimizing data replication across multiple data centers poses a significant challenge,especially when balancing opposing goals such as latency,storage costs,energy consumption,and network efficiency.This study introduces a novel Dynamic Optimization Algorithm called Dynamic Multi-Objective Gannet Optimization(DMGO),designed to enhance data replication efficiency in cloud environments.Unlike traditional static replication systems,DMGO adapts dynamically to variations in network conditions,system demand,and resource availability.The approach utilizes multi-objective optimization approaches to efficiently balance data access latency,storage efficiency,and operational costs.DMGO consistently evaluates data center performance and adjusts replication algorithms in real time to guarantee optimal system efficiency.Experimental evaluations conducted in a simulated cloud environment demonstrate that DMGO significantly outperforms conventional static algorithms,achieving faster data access,lower storage overhead,reduced energy consumption,and improved scalability.The proposed methodology offers a robust and adaptable solution for modern cloud systems,ensuring efficient resource consumption while maintaining high performance.
基金supported by the National Natural Science Foundation of China(22168008,22378085)the Guangxi Natural Science Foundation(2024GXNSFDA010053)+1 种基金the Technology Development Project of Guangxi Bossco Environmental Protection Technology Co.,Ltd(202100039)Innovation Project of Guangxi Graduate Education(YCBZ2024065).
文摘Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.
基金support from the National Natural Science Foundation of China(Grant Nos.42277161 and 42230709).
文摘In rock engineering,natural cracks in rock masses subjected to external loads tend to initiate and propagate,leading to potential safety hazards.To investigate the effect of cracking behavior on the mechanical properties of rocks,the cracking processes of pre-cracked rocks have been extensively studied using numerical modeling methods.The peridynamics(PD)exhibits advantages over other numerical methods due to the absence of the requirements for remeshing and external crack growth criterion.However,for modeling pre-cracked rock cracking processes under impact,current PD implementations lack generally applicable rock constitutive models and impact contact models,which leads to difficulties in determining rock material parameters and efficiently calculating impact loads.This paper proposes a non-ordinary state-based peridynamics(NOSBPD)modeling method integrating the Drucker-Prager(DP)plasticity model and an efficient contact model to address the above problems.In the proposed method,the Drucker-Prager plasticity model is integrated into the NOSBPD,thereby equipping NOSBPD with the capability to accurately characterize the nonlinear stress-strain relationship inherent in rocks.An efficient contact model between particles and meshes is designed to calculate the impact loads,which is essentially a coupling method of PD with the finite element method(FEM).The effectiveness of the proposed NOSBPD modeling method is verified by comparison with other numerical methods and experiments.Experimental results indicate that the proposed method can effectively and accurately predict the 3D cracking processes of pre-cracked cracks under impact loading,and the maximum principal stress is the key driver behind wing crack formation in pre-cracked rocks.
基金supported in part by the National Natural Science Foundation of China(NSFC)under Grant 62276109The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through the Research Group Project number(ORF-2025-585).
文摘The personalized fine-tuning of large languagemodels(LLMs)on edge devices is severely constrained by limited computation resources.Although split federated learning alleviates on-device burdens,its effectiveness diminishes in few-shot reasoning scenarios due to the low data efficiency of conventional supervised fine-tuning,which leads to excessive communication overhead.To address this,we propose Language-Empowered Split Fine-Tuning(LESFT),a framework that integrates split architectures with a contrastive-inspired fine-tuning paradigm.LESFT simultaneously learns frommultiple logically equivalent but linguistically diverse reasoning chains,providing richer supervisory signals and improving data efficiency.This process-oriented training allows more effective reasoning adaptation with fewer samples.Extensive experiments demonstrate that LESFT consistently outperforms strong baselines such as SplitLoRA in task accuracy.LESFT consistently outperforms strong baselines on GSM8K,CommonsenseQA,and AQUA_RAT,with the largest gains observed on Qwen2.5-3B.These results indicate that LESFT can effectively adapt large language models for reasoning tasks under the computational and communication constraints of edge environments.
基金supported by the National Natural Science Foundation of China(62462040)the Yunnan Fundamental Research Projects(202501AT070345)the Major Science and Technology Projects in Yunnan Province(202202AD080013).
文摘Federated learning often experiences slow and unstable convergence due to edge-side data heterogeneity.This problem becomes more severe when edge participation rate is low,as the information collected from different edge devices varies significantly.As a result,communication overhead increases,which further slows down the convergence process.To address this challenge,we propose a simple yet effective federated learning framework that improves consistency among edge devices.The core idea is clusters the lookahead gradients collected from edge devices on the cloud server to obtain personalized momentum for steering local updates.In parallel,a global momentum is applied during model aggregation,enabling faster convergence while preserving personalization.This strategy enables efficient propagation of the estimated global update direction to all participating edge devices and maintains alignment in local training,without introducing extra memory or communication overhead.We conduct extensive experiments on benchmark datasets such as Cifar100 and Tiny-ImageNet.The results confirm the effectiveness of our framework.On CIFAR-100,our method reaches 55%accuracy with 37 fewer rounds and achieves a competitive final accuracy of 65.46%.Even under extreme non-IID scenarios,it delivers significant improvements in both accuracy and communication efficiency.The implementation is publicly available at https://github.com/sjmp525/CollaborativeComputing/tree/FedCCM(accessed on 20 October 2025).
基金the National Natural Science Foundation of China (42171124)。
文摘Understanding the coupling between carbon and water in terrestrial ecosystems is essential for achieving sustainable development.Net primary productivity(NPP),carbon use efficiency(CUE),and water use efficiency(WUE) are key indicators for assessing carbon balance and carbon–water interactions.However,knowledge gaps remain regarding how these indicators respond to climate change and interact with one another.This study examined the spatial and temporal dynamics of NPP,CUE,and WUE,as well as their interrelationships,within the Three-North Shelterbelt Forest region of China.Furthermore,the study investigated the driving mechanisms of these indicators using Extreme Gradient Boosting(XGBoost),SHapley Additive ex Planations(SHAP),and Partial Least Squares Structural Equation Modeling(PLS-SEM).The results revealed that from 2000 to 2020,both NPP(2.69 g C/(m^(2)·a);P<0.010) and WUE(0.004 g C/(kg H_(2)O·a);P<0.010) increased significantly,while CUE exhibited a non-significant decline(–5.40×10^(–4)/a;P>0.050) across different climatic zones(arid,semi-arid,humid,and sub-humid) and vegetation types(cropland,forest,grassland,shrubland,and wetland).The correlation between WUE and NPP(correlation coefficient of 0.70) was stronger than that between CUE and NPP(correlation coefficient of 0.15).NPP and WUE were primarily influenced by leaf area index,whereas CUE was most strongly affected by elevation.The relationships between the key drivers and the three indicators were largely nonlinear,with stronger driver contributions corresponding to more pronounced nonlinear interactions.Moreover,these nonlinear relationships were modulated by differences in dry versus wet climatic conditions.Geographical factors(e.g.,longitude,latitude,and elevation) further shaped vegetation characteristics(e.g.,fractional vegetation cover and leaf area index) by regulating climatic variables such as temperature,precipitation,and evapotranspiration,ultimately influencing NPP,WUE,and CUE.This study advances the understanding of vegetation carbon–water coupling and provides a scientific basis for ecosystem management and sustainable development policy-making in various climatic zones.
基金supported by the National Natural Science Foundation of China(Grant No.62205103)the Natural Science Foundation of Hunan Province(Grant No.2023JJ40216)the Elite Youth Program by the Department of Education of Hunan Province(Grant No.24B0663)。
文摘Although the certified power conversion efficiency(PCE)of single-junction perovskite solar cells(PSCs)has achieved a high level of 27%,approaching the single-crystalline silicon solar cells,the device stability remains an urgent issue to be resolved for the commercialization.Defect passivation emerged as a viable approach to enhance the operational stability of the solar devices.Herein,phenylthiourea(PhTu)derivatives are selected as effective passivation agents to enhance the optoelectronic properties of printed methylammonium lead iodide(MAPbI_(3))films.It is demonstrated that incorporating a small amount of 1-(4-carboxyphenyl)-2-thiourea(PhTu-COOH)significantly reduces the trap-state density and leads to longer carrier lifetime of the perovskite films.As a result,the inverted solar device made of Ph Tu-COOH-modified MAPbI_(3) perovskite film shows remarkably improved efficiency(from 17.29%to 20.22%)and obviously increased open-circuit voltage(V_(OC))(from 1.043 to 1.143 V),as compared with the pristine device.Moreover,the Ph Tu-COOH-modified PSCs exhibit enhanced operational stability due to the significantly reduced trap-state density.Finally,the optimized solar module fabricated with an active area of 11.28 cm^(2) delivers a high PCE of 17.07%with negligible V_(OC)loss,demonstrating the feasibility of the blade-coating method for large-area perovskite film deposition.
基金supported by the Key Laboratory of Sichuan Province for Lithium Resources Comprehensive Utilization and New Lithium Based Materials for Advanced Battery Technology(LRMKF202405)the National Natural Science Foundation of China(52402226)the Natural Science Foundation of Sichuan Province(2024NSFSC1016).
文摘Coal-derived hard carbon(HC)represents a promising anode material for sodium-ion batteries owing to its cost-effectiveness and high carbon yield.However,conventional carbonization induces excessive graphitization,yielding insufficient interlayer spacing(d_(002)<0.37 nm)and underdeveloped closed pores.Herein,we propose a dynamic crystallization control strategy through carbothermal shock treatment(1300°C,30 s)that decouples thermodynamic and kinetic constraints.This method precisely modulates graphite domain ordering kinetics,producing short-range ordered structures with expanded interlayer spacing(d_(002)=0.385 nm)and homogeneously distributed closed nanopores.Through combined in situ characterization and first-principles calculations,we elucidate a three-stage crystallization mechanism:(i)amorphous carbon transformation,(ii)open-pore collapse,and(iii)pseudo-graphitic ordering.The optimized HC achieves record performance with 88.6%initial Coulombic efficiency and 204 mA h g^(−1)plateau capacity,while its optimal interlayer spacing lowers Na+diffusion barriers to enable exceptional rate capability(221 mA h g^(−1)at 0.5C after 300 cycles).Practical pouch cells maintain 85%capacity retention after 100 cycles at−20°C and deliver 284 Wh kg^(−1)energy density.This work establishes a kinetic regulation paradigm for graphitization-prone precursors,advancing the rational design of high-performance HC anodes.
文摘With the rapid growth of cloud computing,the number of data centers(DCs)continuously increases,leading to a high-energy consumption dilemma.Cooling,apart from IT equipment,represents the largest energy consumption in DCs.Passive design(PD)and active design(AD)are two important approaches in architectural design to reduce energy consumption.However,for DC cooling,few studies have summarized AD,and there are almost no studies on PD.Based on existing international research(2005-2024),this paper summarizes the current state of cooling strategies for DCs.PD encompasses floors,ceilings,and layout and zoning of racks.Additionally,other passive strategies not yet studied in DCs are critically examined.AD includes air,liquid,free,and two-phase cooling.This paper systematically compares the performance of different AD technologies on various KPIs,including energy,economic,and environmental indicators.This paper also explores the application of different cooling design strategies through best-practice examples and presents advanced algorithms for energy management in operational DCs.This study reveals that free cooling is widely employed,with Artificial Neural Networks emerging as the most popular algorithm for managing cooling energy.Finally,this paper suggests four future directions for reducing cooling energy in DCs,with a focus on the development of passive strategies.This paper provides an overview and guide to DC energy-consumption issues,emphasizes the importance of implementing passive and active design strategies to reduce DC cooling energy consumption,and provides directions and references for future energy-efficient DC designs.
文摘The current study aims to improve the performance of the electrohydraulic servo system(EHSS)by increasing the volumetric efficiency of the pump and reducing electrical power consumption to a minimum value.An experimental setup has been designed and built to control the cylinder position using a programmable logic controller to provide the appropriate motor speed from the AC drive to control the velocity of the hydraulic actuator;the induction motor is driven by an AC drive using a tune proportional-integral-variable frequency drive(TPI-VFD)space vector modulation(SVM)hybrid technology.Theoretically,it was analyzed and simulated by MATLAB,which showed that the starting current was reduced by 81%compared to the traditional system.Also,the settling time of the system decreased to 0.35 s to reach a steady state with a minimum error of 0.03 and an overshoot of 0.3%.On the other hand,the experimental results of the EHSS show that the three-phase induction motor with a closed-loop speed control AC drive with a programmable logic controller PLC based system is the best case for determining the appropriate operating speed.The optimum speed,frequency,and voltage were 1325.3 rpm,46.6 Hz,and 354.16 V.In addition,enhancement is achieved in closed-loop VFD-PLC,where at 6.5 bar pressure and 3.4 LPM flow,the volumetric efficiency after the pump improves to 98.6%while it reaches 96.3%before the cylinder at a flow rate of 3.32 LPM.Finally,in the closed-loop VFD-PLC in the expansion stroke,the rated electrical power consumption of the three-phase IM decreased to 532 W at the speed of 1325.3 rpm,resulting in energy savings of 20.6%.
基金supported by the National Key Research and Development Program of China(No.2022YFB4200400)the National Natural Science Foundation of China(Nos.W2511056,52503289 and 52333005)+1 种基金Beijing Natural Science Foundation(No.Z230018)the Academic Excellence Foundation of BUAA for PhD Students。
文摘Carbazole derivatives with a single phosphonic acid(PA)group are widely used as monolayer interfaces in perovskites and organic solar cells(OSCs).However,their hydrophilic nature renders ITO electrodes hydrophobic,limiting further applications.In this study,a novel carbazole-based compound functionalized with two PA groups,denoted 2PACz-D1,was designed to create a dual hydrophilic interface.This configuration enables the formation of a bilayer hole-transporting layer(HTL).Specifically,one PA group anchors to the ITO electrode,while the other generates a secondary hydrophilic surface.This allows the subsequent deposition of hydrophilic PEDOT:PSS,forming a protective bilayer HTL that shields ITO from corrosive acidic polymers.The OSCs incorporating this bilayer HTL achieved a power conversion efficiency of 19.44%and exhibited improved thermal stability compared to devices with a single HTL.This work demonstrates the potential of bis-PA carbazole derivatives for tailoring the HTL surface properties,offering promising opportunities for various organic electronic devices.
基金supported in part by the Opening Project of Guangxi Wireless Broadband Communication and Signal Processing Key Laboratory under Grant AD25069102in part by the Basic Ability Improvement Project of Young and Middle Aged Teachers in Guangxi Universities,under Grant 2023KY0226+6 种基金in part by Key Laboratory of Cognitive Radio and Information Processing,Ministry of Education of China,underGrant CRKL220108in part by the Innovation Project of Guangxi Graduate Education,under Grant YCBZ2023131in part by the Doctoral Research Foundation of Guilin University of Electronic Technology,under Grant UF23038Yin part by the Bagui Youth Top Talent Projectin part by the Guangxi Key Research and Development Program under Grant AB25069510in part by Open Fund of IPOC(BUPT),No.IPOC2024B07in part by Guangxi Key Laboratory of Precision Navigation Technology and Application,under Grant DH202309.
文摘UAV-mounted intelligent reflecting surface(IRS)helps address the line-of-sight(LoS)blockage between sensor nodes(SNs)and the fusion center(FC)in Internet of Things(IoT).This paper considers an IoT assisted by multiple UAVs-mounted IRS(U-IRS),where the data from ground SNs are transmitted to the FC.In practice,energy efficiency(EE)and mission completion time are crucial metrics for evaluating system performance and operational costs.Recognizing their importance during data collection,we formulate a multi-objective optimization problem to maximize EE and minimize total mission completion time simultaneously.To characterize this tradeoff while considering optimization objective consistency,we construct an optimization problem that minimizes the weighted sum of the total mission completion time and the reciprocal of EE.Due to the non-convex nature of the formulated problem,obtaining optimal solutions is generally challenging.To tackle this issue,we decompose it into three subproblems:UAV-SN association,number of reflecting elements allocation,andUAVtrajectory optimization.An iterative algorithmcombining genetic algorithm,CS-BJ algorithm,and successive convex approximation technique is proposed to solve these sub-problems.Simulation results demonstrate that when the transmitted data amount is 10 and 30Mbits,compared to the static collection benchmark(the UAV hovers directly above each SN),the EE of the proposed method improves by more than 10.4% and 5.2%,while the total mission completion time is reduced by more than 5.4% and 3.3%,respectively.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project No.PNURSP2025R510Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘The technological advancement of the vehicular Internet ofThings(IoT)has revolutionized Intelligent Transportation Systems(ITS)into next-generation ITS.The connectivity of IoT nodes enables improved data availability and facilitates automatic control in the ITS environment.The exponential increase in IoT nodes has significantly increased the demand for an energy-efficient,mobility-aware,and secure system for distributed intelligence.This article presents a mobility-aware Deep Reinforcement Learning based Federated Learning(DRL-FL)approach to design an energy-efficient and threat-resilient ITS.In this approach,a Policy Proximal Optimization(PPO)-based DRL agent is first employed for adaptive client selection.Second,an autoencoder-based anomaly detectionmodule is considered for malicious node detection.Results reveal that the proposed framework achieved an 8%higher accuracy increase,and 15%lower energy consumption.Themodel also demonstrates greater resilience under adversarial conditions compared to the state of the art in federated learning.The adaptability of the proposed approach makes it a compelling choice for next-generation vehicular networks.
基金funded by Deanship of Graduate studies and Scientific Research at Jouf University under grant No.(DGSSR-2024-02-01264).
文摘Automated essay scoring(AES)systems have gained significant importance in educational settings,offering a scalable,efficient,and objective method for evaluating student essays.However,developing AES systems for Arabic poses distinct challenges due to the language’s complex morphology,diglossia,and the scarcity of annotated datasets.This paper presents a hybrid approach to Arabic AES by combining text-based,vector-based,and embeddingbased similarity measures to improve essay scoring accuracy while minimizing the training data required.Using a large Arabic essay dataset categorized into thematic groups,the study conducted four experiments to evaluate the impact of feature selection,data size,and model performance.Experiment 1 established a baseline using a non-machine learning approach,selecting top-N correlated features to predict essay scores.The subsequent experiments employed 5-fold cross-validation.Experiment 2 showed that combining embedding-based,text-based,and vector-based features in a Random Forest(RF)model achieved an R2 of 88.92%and an accuracy of 83.3%within a 0.5-point tolerance.Experiment 3 further refined the feature selection process,demonstrating that 19 correlated features yielded optimal results,improving R2 to 88.95%.In Experiment 4,an optimal data efficiency training approach was introduced,where training data portions increased from 5%to 50%.The study found that using just 10%of the data achieved near-peak performance,with an R2 of 85.49%,emphasizing an effective trade-off between performance and computational costs.These findings highlight the potential of the hybrid approach for developing scalable Arabic AES systems,especially in low-resource environments,addressing linguistic challenges while ensuring efficient data usage.
基金financially supported by the National Key R&D Program of China(2021YFD1901203 and 2021YFD1901204)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA0440404)+2 种基金the National Natural Science Foundation of China(42377348)the Science Foundation for Distinguished Young Scholars of Hunan Province,China(2024JJ2052)the Natural Science Foundation of Guangxi,China(2025GXNSFAA069337)。
文摘Rapidly improving infertile croplands and enhancing their soil organic carbon(SOC)pool necessitate substantial organic materials incorporation.Converting loose crop straw into granulated form facilitates uniform incorporation within the plough soil layer.As an innovative soil amelioration approach,the efficiency and patterns of SOC accumulation remain unclear.Two field experiments were conducted in infertile subtropical upland and paddy soils with 0,30,60,and 90 Mg ha^(-1)granulated straw incorporation.After one year,SOC accumulation efficiency from straw input remained stable in upland(30.8–37.5%)with increasing amounts of straw incorporation,while declined from 60.0 to 38.3%in paddy.In both croplands,the contributions of lignin phenols to SOC increased with increasing straw incorporation,while the contributions from amino sugars remained constant at higher straw input levels.Subsequently,the ratios of lignin phenols to amino sugars increased with increasing straw incorporation,indicating faster plant residue accumulation compared to microbial necromass,as the granulation approach limited microbial involvement in straw transformation.Thus,single-time incorporation of substantial granulated straw presents an effective agricultural strategy for rapid amelioration of infertile croplands.
