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
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
Efficient energy utilization in covert communication sustains covertness while assuring communication quality and efficiency.This paper investigates covert communication energy efficiency(EE)in direct uplink satellite...Efficient energy utilization in covert communication sustains covertness while assuring communication quality and efficiency.This paper investigates covert communication energy efficiency(EE)in direct uplink satellite-ground communications,focusing on enhancing system EE via optimized transmit beamforming and satellite orbit altitude selection.This paper first establishes an optimization problem to maximize system EE in a direct uplink satelliteground covert communication scenario.To solve this non-convex optimization problem,it is decomposed into two subproblems and solved using the successive convex approximation(SCA)method.Based on the above methods,this paper proposes an overall iterative optimization algorithm.Simulation results demonstrate that the proposed algorithm surpasses the conventional baseline algorithms in terms of system EE.Furthermore,they elucidate the correlation between the amount of information received by the receiver and the variations in the satellite’s orbital altitude.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
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
In Wireless Sensor Networks(WSNs),survivability is a crucial issue that is greatly impacted by energy efficiency.Solutions that satisfy application objectives while extending network life are needed to address severe ...In Wireless Sensor Networks(WSNs),survivability is a crucial issue that is greatly impacted by energy efficiency.Solutions that satisfy application objectives while extending network life are needed to address severe energy constraints inWSNs.This paper presents an Adaptive Enhanced GreyWolf Optimizer(AEGWO)for energy-efficient cluster head(CH)selection that mitigates the exploration–exploitation imbalance,preserves population diversity,and avoids premature convergence inherent in baseline GWO.The AEGWO combines adaptive control of the parameter of the search pressure to accelerate convergence without stagnation,a hybrid velocity-momentum update based on the dynamics of PSO,and an intelligent mutation operator to maintain the diversity of the population.The search is guided by a multi-objective fitness,which aims at maximizing the residual energy,equal distribution of CH,minimizing the intra-cluster distance,desirable proximity to sinks,and enhancing the coverage.Simulations on 100 nodes homogeneousWSN Tested the proposed AEGWO under the same conditions with LEACH,GWO,IGWO,PSO,WOA,and GA,AEGWO significantly increases stability and lifetime compared to LEACHand other tested algorithms;it has the best first,half,and last node dead,and higher residual energy and smaller communication overhead.The findings prove that AEGWO provides sustainable energy management and better lifetime extension,which makes it a robust,flexible clustering protocol of large-scaleWSNs.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
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
Primordial germ cells(PGCs)are the stem-cell population of adult animal gametes,which develop into sperm or eggs.It can be propagated in vitro and injected into the host chicken for genome editing to obtain germline c...Primordial germ cells(PGCs)are the stem-cell population of adult animal gametes,which develop into sperm or eggs.It can be propagated in vitro and injected into the host chicken for genome editing to obtain germline chimeric chicken.However,it has the limitation that the host embryo contains endogenous PGCs,which raises complications,resultantly donor PGCs fail to compete,and transmission efficiency reduced.Therefore,to increase the transmission efficiency,we generated a novel sterile chicken with the inducible elimination of endogenous PGCs in the host.This is the first study that applied the herpes simplex virus thymidine kinase(HSV-TK)cell ablation system in avian.CRISPR/Cas9-mediated homology-directed repair was performed to localize the HSV-TK suicide gene to the last exon of the deleted in azoospermialike(DAZL)gene,and ganciclovir(GCV)was added to induce the apoptosis in the germ cells of the host embryo.The sterilized host embryo introduced genome-edited PGCs to produce chimeric chicken carrying exogenous germ cells only.It was observed that the germline transmission efficiency was 100%achieved,and the obtained chicks were purely from donor breeds.The technologies established in the current study have important applications in germplasm conservation and gene editing in chicken.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
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
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
The rational design of high-performance CO_(2)adsorbents remains a critical challenge in addressing global carbon emissions,with metal-organic frameworks(MOFs)emerging as promising candidates due to their tunable pore...The rational design of high-performance CO_(2)adsorbents remains a critical challenge in addressing global carbon emissions,with metal-organic frameworks(MOFs)emerging as promising candidates due to their tunable pore environments.However,the lack of systematic guidelines for functional group selection has hindered their practical implementation in carbon capture applications.Here,this gap was addressed by developing a comprehensive design framework through high-throughput computational screening.Through construction of a topology-directed database of 4797,integrating 10 metal centers with 144 functionalized ligands(18 ligands modified by–NH_(2),–NO_(2),–CH_(3),–CF_(3),–SH_(2),–SO_(2),–OH,and–OLi)across 36 topologies,the fundamental structure–property relationships governing CO_(2)capture performance was established.Multi-metric evaluation reveals that–NO_(2),–SO_(2),and–OLi dramatically enhance CO_(2)selectivity over CH_4/N_(2)via selectivity(S_(ads)),working capacity(ΔN),adsorbent performance score(APS),sorbent selection parameter(S_(sp)),and renewability R.Specially,ΔN rises from 2.34(pristine)to 5.91–7.94 mmol g^(-1)and S_(ads)surges from 24.94/40.36 to 121.11/176.87(–NO_(2)),149.94/215.54(–SO_(2)),and 58.64/267.44(–OLi).Besides,the critical trade-off between adsorption strength and renewability demonstrates that enhanced performance comes at the cost of reduced renewability,where stronger CO_(2)affinity(isosteric heat of-29.15,-29.96,and-30.09 for–NO_(2),–SO_(2),and–OLi)compromises renewability(R reduced by -50%).To resolve this trade-off,a novel energy efficiency(η)metric was introduced,which holistically evaluates both adsorption performance(S_(ads),ΔN,APS,S_(sp),and R)and energy inputs(desorption heat,pressure-swing energy,net loss).This leads to the identification of–SO_(2)as the optimal functional group that balances exceptional CO_(2)capture(η=6.17/12.78 for CO_(2)over CH_4/N_(2)),surpassing the second higher of 4.74/8.80 in–CF_(3)and 0.99/2.18 in non-functionalized counterparts.Adopting high-throughput computational screening methods,this work provides both fundamental insights into host–vip interactions in functionalized MOFs and a practical framework for designing next-generation adsorbents,bridging the gap between materials discovery and process engineering considerations in carbon capture technologies.展开更多
Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain limitations.Conversely,deep learning techniques have gained promine...Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain limitations.Conversely,deep learning techniques have gained prominence as a central focus of research in the field of fault diagnosis by strong fault feature extraction ability and end-to-end fault diagnosis efficiency.Recently,utilizing the respective advantages of convolution neural network(CNN)and Transformer in local and global feature extraction,research on cooperating the two have demonstrated promise in the field of fault diagnosis.However,the cross-channel convolution mechanism in CNN and the self-attention calculations in Transformer contribute to excessive complexity in the cooperative model.This complexity results in high computational costs and limited industrial applicability.To tackle the above challenges,this paper proposes a lightweight CNN-Transformer named as SEFormer for rotating machinery fault diagnosis.First,a separable multiscale depthwise convolution block is designed to extract and integrate multiscale feature information from different channel dimensions of vibration signals.Then,an efficient self-attention block is developed to capture critical fine-grained features of the signal from a global perspective.Finally,experimental results on the planetary gearbox dataset and themotor roller bearing dataset prove that the proposed framework can balance the advantages of robustness,generalization and lightweight compared to recent state-of-the-art fault diagnosis models based on CNN and Transformer.This study presents a feasible strategy for developing a lightweight rotating machinery fault diagnosis framework aimed at economical deployment.展开更多
Generating dynamically feasible trajectory for fixed-wing Unmanned Aerial Vehicles(UAVs)in dense obstacle environments remains computationally intractable.This paper proposes a Safe Flight Corridor constrained Sequent...Generating dynamically feasible trajectory for fixed-wing Unmanned Aerial Vehicles(UAVs)in dense obstacle environments remains computationally intractable.This paper proposes a Safe Flight Corridor constrained Sequential Convex Programming(SFC-SCP)to improve the computation efficiency and reliability of trajectory generation.SFC-SCP combines the front-end convex polyhedron SFC construction and back-end SCP-based trajectory optimization.A Sparse A^(*)Search(SAS)driven SFC construction method is designed to efficiently generate polyhedron SFC according to the geometric relation among obstacles and collision-free waypoints.Via transforming the nonconvex obstacle-avoidance constraints to linear inequality constraints,SFC can mitigate infeasibility of trajectory planning and reduce computation complexity.Then,SCP casts the nonlinear trajectory optimization subject to SFC into convex programming subproblems to decrease the problem complexity.In addition,a convex optimizer based on interior point method is customized,where the search direction is calculated via successive elimination to further improve efficiency.Simulation experiments on dense obstacle scenarios show that SFC-SCP can generate dynamically feasible safe trajectory rapidly.Comparative studies with state-of-the-art SCP-based methods demonstrate the efficiency and reliability merits of SFC-SCP.Besides,the customized convex optimizer outperforms off-the-shelf optimizers in terms of computation time.展开更多
With the rise of remote collaboration,the demand for advanced storage and collaboration tools has rapidly increased.However,traditional collaboration tools primarily rely on access control,leaving data stored on cloud...With the rise of remote collaboration,the demand for advanced storage and collaboration tools has rapidly increased.However,traditional collaboration tools primarily rely on access control,leaving data stored on cloud servers vulnerable due to insufficient encryption.This paper introduces a novel mechanism that encrypts data in‘bundle’units,designed to meet the dual requirements of efficiency and security for frequently updated collaborative data.Each bundle includes updated information,allowing only the updated portions to be reencrypted when changes occur.The encryption method proposed in this paper addresses the inefficiencies of traditional encryption modes,such as Cipher Block Chaining(CBC)and Counter(CTR),which require decrypting and re-encrypting the entire dataset whenever updates occur.The proposed method leverages update-specific information embedded within data bundles and metadata that maps the relationship between these bundles and the plaintext data.By utilizing this information,the method accurately identifies the modified portions and applies algorithms to selectively re-encrypt only those sections.This approach significantly enhances the efficiency of data updates while maintaining high performance,particularly in large-scale data environments.To validate this approach,we conducted experiments measuring execution time as both the size of the modified data and the total dataset size varied.Results show that the proposed method significantly outperforms CBC and CTR modes in execution speed,with greater performance gains as data size increases.Additionally,our security evaluation confirms that this method provides robust protection against both passive and active attacks.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.
基金supported in part by the National Natural Science Foundation of China under Grants 62025110,62271093sponsored by Natural Science Foundation of Chongqing,China,under Grant CSTB2023NSCQ-LZX0108.
文摘Efficient energy utilization in covert communication sustains covertness while assuring communication quality and efficiency.This paper investigates covert communication energy efficiency(EE)in direct uplink satellite-ground communications,focusing on enhancing system EE via optimized transmit beamforming and satellite orbit altitude selection.This paper first establishes an optimization problem to maximize system EE in a direct uplink satelliteground covert communication scenario.To solve this non-convex optimization problem,it is decomposed into two subproblems and solved using the successive convex approximation(SCA)method.Based on the above methods,this paper proposes an overall iterative optimization algorithm.Simulation results demonstrate that the proposed algorithm surpasses the conventional baseline algorithms in terms of system EE.Furthermore,they elucidate the correlation between the amount of information received by the receiver and the variations in the satellite’s orbital altitude.
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.
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The Open Access publication fee for this article was fully covered by Abu Dhabi University.
文摘In Wireless Sensor Networks(WSNs),survivability is a crucial issue that is greatly impacted by energy efficiency.Solutions that satisfy application objectives while extending network life are needed to address severe energy constraints inWSNs.This paper presents an Adaptive Enhanced GreyWolf Optimizer(AEGWO)for energy-efficient cluster head(CH)selection that mitigates the exploration–exploitation imbalance,preserves population diversity,and avoids premature convergence inherent in baseline GWO.The AEGWO combines adaptive control of the parameter of the search pressure to accelerate convergence without stagnation,a hybrid velocity-momentum update based on the dynamics of PSO,and an intelligent mutation operator to maintain the diversity of the population.The search is guided by a multi-objective fitness,which aims at maximizing the residual energy,equal distribution of CH,minimizing the intra-cluster distance,desirable proximity to sinks,and enhancing the coverage.Simulations on 100 nodes homogeneousWSN Tested the proposed AEGWO under the same conditions with LEACH,GWO,IGWO,PSO,WOA,and GA,AEGWO significantly increases stability and lifetime compared to LEACHand other tested algorithms;it has the best first,half,and last node dead,and higher residual energy and smaller communication overhead.The findings prove that AEGWO provides sustainable energy management and better lifetime extension,which makes it a robust,flexible clustering protocol of large-scaleWSNs.
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supported by the National Key R&D Program of China(2021YFD1300100)Guangxi Key R&D Program,China(AB21220005)+1 种基金Reproductive Medicine,Guangxi Medical and Health Key Discipline Construction Project of the Affiliated Hospitalthe National Natural Science Foundation of China(32360180)。
文摘Primordial germ cells(PGCs)are the stem-cell population of adult animal gametes,which develop into sperm or eggs.It can be propagated in vitro and injected into the host chicken for genome editing to obtain germline chimeric chicken.However,it has the limitation that the host embryo contains endogenous PGCs,which raises complications,resultantly donor PGCs fail to compete,and transmission efficiency reduced.Therefore,to increase the transmission efficiency,we generated a novel sterile chicken with the inducible elimination of endogenous PGCs in the host.This is the first study that applied the herpes simplex virus thymidine kinase(HSV-TK)cell ablation system in avian.CRISPR/Cas9-mediated homology-directed repair was performed to localize the HSV-TK suicide gene to the last exon of the deleted in azoospermialike(DAZL)gene,and ganciclovir(GCV)was added to induce the apoptosis in the germ cells of the host embryo.The sterilized host embryo introduced genome-edited PGCs to produce chimeric chicken carrying exogenous germ cells only.It was observed that the germline transmission efficiency was 100%achieved,and the obtained chicks were purely from donor breeds.The technologies established in the current study have important applications in germplasm conservation and gene editing in chicken.
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.
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 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supported by The National Natural Science Foundation of China(22471289 and 22478430)Shandong Natural Science Foundation(ZR2022ME105 and ZR2023ME004)+4 种基金Qingdao Natural Science Foundation(23-2-1-232-zyyd-jch)Geological body description and key technologies of reservoir engineering of CCUS oil displacement(2021ZZ01-03)Science and Technology Major Project on New Oil and Gas Exploration and Development:Research on Comprehensive Control Technology for CO_(2)-Enhanced Miscible and Immiscible Displacement(2024ZD1406601)State Key Laboratory of Enhanced Oil Recovery of Open Fund Funded Project(2024-KFKT-19)the Fundamental Research Funds for the Central Universities(24CX06042A and 24CX06070A)。
文摘The rational design of high-performance CO_(2)adsorbents remains a critical challenge in addressing global carbon emissions,with metal-organic frameworks(MOFs)emerging as promising candidates due to their tunable pore environments.However,the lack of systematic guidelines for functional group selection has hindered their practical implementation in carbon capture applications.Here,this gap was addressed by developing a comprehensive design framework through high-throughput computational screening.Through construction of a topology-directed database of 4797,integrating 10 metal centers with 144 functionalized ligands(18 ligands modified by–NH_(2),–NO_(2),–CH_(3),–CF_(3),–SH_(2),–SO_(2),–OH,and–OLi)across 36 topologies,the fundamental structure–property relationships governing CO_(2)capture performance was established.Multi-metric evaluation reveals that–NO_(2),–SO_(2),and–OLi dramatically enhance CO_(2)selectivity over CH_4/N_(2)via selectivity(S_(ads)),working capacity(ΔN),adsorbent performance score(APS),sorbent selection parameter(S_(sp)),and renewability R.Specially,ΔN rises from 2.34(pristine)to 5.91–7.94 mmol g^(-1)and S_(ads)surges from 24.94/40.36 to 121.11/176.87(–NO_(2)),149.94/215.54(–SO_(2)),and 58.64/267.44(–OLi).Besides,the critical trade-off between adsorption strength and renewability demonstrates that enhanced performance comes at the cost of reduced renewability,where stronger CO_(2)affinity(isosteric heat of-29.15,-29.96,and-30.09 for–NO_(2),–SO_(2),and–OLi)compromises renewability(R reduced by -50%).To resolve this trade-off,a novel energy efficiency(η)metric was introduced,which holistically evaluates both adsorption performance(S_(ads),ΔN,APS,S_(sp),and R)and energy inputs(desorption heat,pressure-swing energy,net loss).This leads to the identification of–SO_(2)as the optimal functional group that balances exceptional CO_(2)capture(η=6.17/12.78 for CO_(2)over CH_4/N_(2)),surpassing the second higher of 4.74/8.80 in–CF_(3)and 0.99/2.18 in non-functionalized counterparts.Adopting high-throughput computational screening methods,this work provides both fundamental insights into host–vip interactions in functionalized MOFs and a practical framework for designing next-generation adsorbents,bridging the gap between materials discovery and process engineering considerations in carbon capture technologies.
基金supported by the National Natural Science Foundation of China(No.52277055).
文摘Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain limitations.Conversely,deep learning techniques have gained prominence as a central focus of research in the field of fault diagnosis by strong fault feature extraction ability and end-to-end fault diagnosis efficiency.Recently,utilizing the respective advantages of convolution neural network(CNN)and Transformer in local and global feature extraction,research on cooperating the two have demonstrated promise in the field of fault diagnosis.However,the cross-channel convolution mechanism in CNN and the self-attention calculations in Transformer contribute to excessive complexity in the cooperative model.This complexity results in high computational costs and limited industrial applicability.To tackle the above challenges,this paper proposes a lightweight CNN-Transformer named as SEFormer for rotating machinery fault diagnosis.First,a separable multiscale depthwise convolution block is designed to extract and integrate multiscale feature information from different channel dimensions of vibration signals.Then,an efficient self-attention block is developed to capture critical fine-grained features of the signal from a global perspective.Finally,experimental results on the planetary gearbox dataset and themotor roller bearing dataset prove that the proposed framework can balance the advantages of robustness,generalization and lightweight compared to recent state-of-the-art fault diagnosis models based on CNN and Transformer.This study presents a feasible strategy for developing a lightweight rotating machinery fault diagnosis framework aimed at economical deployment.
基金supported by the National Natural Science Foundation of China(No.62203256)。
文摘Generating dynamically feasible trajectory for fixed-wing Unmanned Aerial Vehicles(UAVs)in dense obstacle environments remains computationally intractable.This paper proposes a Safe Flight Corridor constrained Sequential Convex Programming(SFC-SCP)to improve the computation efficiency and reliability of trajectory generation.SFC-SCP combines the front-end convex polyhedron SFC construction and back-end SCP-based trajectory optimization.A Sparse A^(*)Search(SAS)driven SFC construction method is designed to efficiently generate polyhedron SFC according to the geometric relation among obstacles and collision-free waypoints.Via transforming the nonconvex obstacle-avoidance constraints to linear inequality constraints,SFC can mitigate infeasibility of trajectory planning and reduce computation complexity.Then,SCP casts the nonlinear trajectory optimization subject to SFC into convex programming subproblems to decrease the problem complexity.In addition,a convex optimizer based on interior point method is customized,where the search direction is calculated via successive elimination to further improve efficiency.Simulation experiments on dense obstacle scenarios show that SFC-SCP can generate dynamically feasible safe trajectory rapidly.Comparative studies with state-of-the-art SCP-based methods demonstrate the efficiency and reliability merits of SFC-SCP.Besides,the customized convex optimizer outperforms off-the-shelf optimizers in terms of computation time.
基金supported by the Institute of Information&communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(RS-2024-00399401,Development of Quantum-Safe Infrastructure Migration and Quantum Security Verification Technologies).
文摘With the rise of remote collaboration,the demand for advanced storage and collaboration tools has rapidly increased.However,traditional collaboration tools primarily rely on access control,leaving data stored on cloud servers vulnerable due to insufficient encryption.This paper introduces a novel mechanism that encrypts data in‘bundle’units,designed to meet the dual requirements of efficiency and security for frequently updated collaborative data.Each bundle includes updated information,allowing only the updated portions to be reencrypted when changes occur.The encryption method proposed in this paper addresses the inefficiencies of traditional encryption modes,such as Cipher Block Chaining(CBC)and Counter(CTR),which require decrypting and re-encrypting the entire dataset whenever updates occur.The proposed method leverages update-specific information embedded within data bundles and metadata that maps the relationship between these bundles and the plaintext data.By utilizing this information,the method accurately identifies the modified portions and applies algorithms to selectively re-encrypt only those sections.This approach significantly enhances the efficiency of data updates while maintaining high performance,particularly in large-scale data environments.To validate this approach,we conducted experiments measuring execution time as both the size of the modified data and the total dataset size varied.Results show that the proposed method significantly outperforms CBC and CTR modes in execution speed,with greater performance gains as data size increases.Additionally,our security evaluation confirms that this method provides robust protection against both passive and active attacks.
