Carbon superstructures with multiscale hierarchies and functional attributes represent an appealing cathode candidate for zinc hybrid capacitors,but their tailor-made design to optimize the capacitive activity remains...Carbon superstructures with multiscale hierarchies and functional attributes represent an appealing cathode candidate for zinc hybrid capacitors,but their tailor-made design to optimize the capacitive activity remains a confusing topic.Here we develop a hydrogen-bond-oriented interfacial super-assembly strategy to custom-tailor nanosheet-intertwined spherical carbon superstructures(SCSs)for Zn-ion storage with double-high capacitive activity and durability.Tetrachlorobenzoquinone(H-bond acceptor)and dimethylbenzidine(H-bond donator)can interact to form organic nanosheet modules,which are sequentially assembled,orientally compacted and densified into well-orchestrated superstructures through multiple H-bonds(N-H···O).Featured with rich surface-active heterodiatomic motifs,more exposed nanoporous channels,and successive charge migration paths,SCSs cathode promises high accessibility of built-in zincophilic sites and rapid ion diffusion with low energy barriers(3.3Ωs-0.5).Consequently,the assembled Zn||SCSs capacitor harvests all-round improvement in Zn-ion storage metrics,including high energy density(166 Wh kg-1),high-rate performance(172 m Ah g^(-1)at 20 A g^(-1)),and long-lasting cycling lifespan(95.5%capacity retention after 500,000 cycles).An opposite chargecarrier storage mechanism is rationalized for SCSs cathode to maximize spatial capacitive charge storage,involving high-kinetics physical Zn^(2+)/CF_(3)SO_(3)-adsorption and chemical Zn^(2+)redox with carbonyl/pyridine groups.This work gives insights into H-bond-guided interfacial superassembly design of superstructural carbons toward advanced energy storage.展开更多
Improving the surface atoms utilization efficiency of catalysts is extremely important for large-scale H_(2)production by electrochemical water splitting,but it remains a great challenge.Herein,we reported two kinds o...Improving the surface atoms utilization efficiency of catalysts is extremely important for large-scale H_(2)production by electrochemical water splitting,but it remains a great challenge.Herein,we reported two kinds of Mo O_(3)-polyoxometalate hybrid nanobelt superstructures(MoO_(3)-POM HNSs,POM=PW_(12)O_(40)and Si W_(12)O_(40))using a simple hydrothermal method.Such superstructure with highly uniform nanoparticles as building blocks can expose more surface atoms and emanate increased specific surface area.The incorporated POMs generated abundant oxygen vacancies,improved the electronic mobility,and modulated the surface electronic structure of MoO_(3),allowing to optimize the H^(*)adsorption/desorption and dehydrogenation kinetics of catalyst.Notably,the as-prepared MoO_(3)-PW_(12)O_(40)HNSs electrodes not only displayed the low overpotentials of 108 mV at 10 mA/cm^(2)current density in 0.5 mol/L H_(2)SO_(4)electrolyte but also displayed excellent long-term stability.The hydrogen evolution reaction(HER)performance of MoO_(3)-POM superstructures is significantly better than that of corresponding bulk materials MoO_(3)@PW_(12)O_(40)and Mo O_(3)@Si W_(12)O_(40),and the overpotentials are about 8.3 and 4.9 times lower than that of single Mo O_(3).This work opens an avenue for designing highly surface-exposed catalysts for electrocatalytic H_(2)production and other electrochemical applications.展开更多
Designing carbon materials with ideal stable hierarchical porous structures and fiexible functional properties for efficient and sustainable Zn2+ion storage still faces great challenges. Herein, the threedimensional c...Designing carbon materials with ideal stable hierarchical porous structures and fiexible functional properties for efficient and sustainable Zn2+ion storage still faces great challenges. Herein, the threedimensional carbon superstructures with spherical nanofiower-like structures were tailor-made by the self-assembly strategy. Specifically, organic polymer units(i.e., organic motifs) were formed by tetrachloro-p-benzoquinone(TBQ) and 2,6-diamino anthraquinone(DAQ) via a noble-metal-free catalyzed coupling reaction. Subsequently, the organic motifs assemble into spherical nanofiower-like superstructures induced by intermolecular hydrogen bonding and aromatic π-π stacking interactions. Welldesigned carbon superstructures can provide a stable backbone that effectively blocks structural stacking and collapse. Meanwhile, the hierarchical porous structures in 3D carbon superstructures provide continuous charge transport pathways to greatly shorten the ion diffusion distance, and as a result, the carbon superstructures-based zinc-ion hybrid capacitors(ZIHCs) provide a capacity of 245 m Ah/g at 0.5 A/g, a high energy density of 152 Wh/kg and an ultra-long life of 300,000 cycles at 20 A/g. The excellent electrochemical performance is also attributed to the corresponding charge storage mechanism, i.e., the alternate binding of Zn^(2+)/CF_(3)SO_(3)^(-) ions. Besides, the high-level N/O motifs improve the surface properties of the carbon superstructures and reduce the ion migration barriers for more efficient charge storage. This paper provides insights into the design of advanced carbon-based cathodes and presents a fundamental understanding of their charge storage mechanisms.展开更多
Pyrrhotite naturally occurs in various superstructures including magnetic(4C)and non-magnetic(5C,6C)types,each with distinct physicochemical properties and flotation behaviors.Challenges in accurately identifying and ...Pyrrhotite naturally occurs in various superstructures including magnetic(4C)and non-magnetic(5C,6C)types,each with distinct physicochemical properties and flotation behaviors.Challenges in accurately identifying and quantifying these superstructures hinder the optimization of pyrrhotite depression in flotation processes.To address this critical issue,synchrotron X-ray powder diffraction(S-XRPD)with Rietveld refinement was employed to quantify the distribution of superstructures in the feed and flotation concentrates of a copper–gold ore.To elucidate the mechanisms influencing depression,density functional theory(DFT)calculations were conducted to explore the electronic structures and surface reactivity of the pyrrhotite superstructures toward the adsorption of water,oxygen and hydroxyl ions(OH-)as dominant species present in the flotation process.S-XRPD analysis revealed that flotation recovery rates of pyrrhotite followed the order of 4C<6C<5C.DFT calculations indicated that the Fe 3d and S 3p orbital band centers exhibited a similar trend relative to the Fermi level with 4C being the closest.The Fe3d band center suggested that the 4C structure possessed a more reactive surface toward the oxygen reduction reaction,promoting the formation of hydrophilic Fe-OH sites.The S 3p band center order also implied that xanthate on the non-magnetic 5C and 6C surfaces could oxidize to dixanthogen,increasing hydrophobicity and floatability,while 4C formed less hydrophobic metal-xanthate complexes.Adsorption energy and charge transfer analyses of water,hydroxyl ions and molecular oxygen further supported the high reactivity and hydrophilic nature of 4C pyrrhotite.The strong bonding with hydroxyl ions indicated enhanced surface passivation by hydrophilic Fe–OOH complexes,aligning with the experimentally observed flotation order(4C<6C<5C).These findings provide a compelling correlation between experimental flotation results and electronic structure calculations,delivering crucial insights for optimizing flotation processes and improving pyrrhotite depression.This breakthrough opens up new opportunities to enhance the efficiency of flotation processes in the mining industry.展开更多
The novel fabrication of multiple components and unique heterostructure can inject infinite vitality into the electromagnetic wave(EMW)attenuation field.Herein,through the self-assembly of polyimide com-plexes and cat...The novel fabrication of multiple components and unique heterostructure can inject infinite vitality into the electromagnetic wave(EMW)attenuation field.Herein,through the self-assembly of polyimide com-plexes and catalytic chemical vapor deposition,porous carbon microflowers were synthesized accompa-nied by carbon nanotubes(CNTs).By regulating the metal ions,the composition and structure of the as-obtained hybrids are modified correspondingly,and thus the adjustable thermal management and EMW absorption capabilities are obtained.In detail,the rich pores and huge specific surface area endow the hierarchical structures with distinguished thermal insulation ability(λ<0.07).The carbon framework and CNTs are beneficial for consuming EMWs via conductive loss and defect polarization loss while reduc-ing the filling ratio and thickness.The doped heteroatoms and abundant heterointerfaces generate ample dipole polarization and interface polarization losses(supported by DFT calculation).The metal nanopar-ticles uniformly embedded in the carbon framework offer optimized impedance matching,proper de-fect polarization,and suitable magnetic loss.Accordingly,the synergy of magnetic-dielectric balance and flower-like superstructure enables FNCFN2 and NNCFN2 to accomplish remarkable microwave absorbing capacity with thin thickness(14 wt.%).Therefore,respectable specific reflection loss and specific effec-tive absorption bandwidth are acquired(215.39 dB mm^(-1) and 22.10 GHz mm^(-1),257.23 dB mm^(-1) and 22.12 GHz mm^(-1) respectively),superior to those of certain renowned carbon-based absorbers.The simu-lation results of electric field intensity distributions,power loss density,and radar cross section reduction(maximum value of 36.02 dBm2)also verify the prominent radar stealth capability.Moreover,the cus-tomizable approach can be applied to other metals to obtain fulfilling behaviors.Henceforth,this work provides profound insights into the relationship between structure and performance,and proposes an efficient path for mass-producing multifunctional and high-performance EMW absorbers with excellent thermal properties.展开更多
A[3+4]annulation of α-substituted allenes and Schiff bases is reported.This methodology serves as a conduit for the construction of a series of biologically important benzazepine derivatives in good to excellent yiel...A[3+4]annulation of α-substituted allenes and Schiff bases is reported.This methodology serves as a conduit for the construction of a series of biologically important benzazepine derivatives in good to excellent yields under mild conditions by an unprecedented mode involving β’-carbon of α-substituted allenes and the proposed mechanism is supported by capturing the intermediate.Moreover,this class of benzazepine derivatives exhibited potential ability of cytotoxicity toward cancer cells.展开更多
Improving the accuracy of the evaluation of the performance of wind farms in large wind power bases located in complex terrain under the actual atmosphere is crucial to the sustainable development of wind power.To thi...Improving the accuracy of the evaluation of the performance of wind farms in large wind power bases located in complex terrain under the actual atmosphere is crucial to the sustainable development of wind power.To this end,this study combined the Weather Research and Forecasting(WRF)model with the Wind Farm Parameterization(WFP)method to investigate the wake characteristics and operational performance of large onshore wind farms in the complex terrain of Jiuquan City,Gansu Province,China.The research results showed that after verification,the systematic error of the WRF simulations was less than 3%.The WRF model and the WFP scheme simulated a significant warming phenomenon within the wind power base area,while a cooling effect was observed outside.The analysis of the wake effects indicated that the impact of PhaseⅠconstruction on PhaseⅡconstruction of the wind power base was minimal.During the operation of the entire wind power base,the wind speed within the wind farm decreased by approximately 10%,and the influence range of the predominant wind direction extended over a hundred kilometers downwind.The research conclusions provide a powerful scientific basis for optimizing design and operation,improving efficiency,minimizing the negative impacts on adjacent wind turbines,and ensuring the sustainable development of wind energy through dynamic planning and scientific assessment.展开更多
Reversible data hiding(RDH)enables secret data embedding while preserving complete cover image recovery,making it crucial for applications requiring image integrity.The pixel value ordering(PVO)technique used in multi...Reversible data hiding(RDH)enables secret data embedding while preserving complete cover image recovery,making it crucial for applications requiring image integrity.The pixel value ordering(PVO)technique used in multi-stego images provides good image quality but often results in low embedding capability.To address these challenges,this paper proposes a high-capacity RDH scheme based on PVO that generates three stego images from a single cover image.The cover image is partitioned into non-overlapping blocks with pixels sorted in ascending order.Four secret bits are embedded into each block’s maximum pixel value,while three additional bits are embedded into the second-largest value when the pixel difference exceeds a predefined threshold.A similar embedding strategy is also applied to the minimum side of the block,including the second-smallest pixel value.This design enables each block to embed up to 14 bits of secret data.Experimental results demonstrate that the proposed method achieves significantly higher embedding capacity and improved visual quality compared to existing triple-stego RDH approaches,advancing the field of reversible steganography.展开更多
Conversational recommender systems(CRSs)focus on refining preferences and providing personalized recommendations through natural language interactions and dialogue history.Large language models(LLMs)have shown outstan...Conversational recommender systems(CRSs)focus on refining preferences and providing personalized recommendations through natural language interactions and dialogue history.Large language models(LLMs)have shown outstanding performance across various domains,thereby prompting researchers to investigate their applicability in recommendation systems.However,due to the lack of task-specific knowledge and an inefficient feature extraction process,LLMs still have suboptimal performance in recommendation tasks.Therefore,external knowledge sources,such as knowledge graphs(KGs)and knowledge bases(KBs),are often introduced to address the issue of data sparsity.Compared to KGs,KBs possess higher retrieval efficiency,making them more suitable for scenarios where LLMs serve as recommenders.To this end,we introduce a novel framework integrating LLMs with KBs for enhanced retrieval generation,namely LLMKB.LLMKB initially leverages structured knowledge to create mapping dictionaries,extracting entity-relation information from heterogeneous knowledge to construct KBs.Then,LLMKB achieves the embedding calibration between user information representations and documents in KBs through retrieval model fine-tuning.Finally,LLMKB employs retrievalaugmented generation to produce recommendations based on fused text inputs,followed by post-processing.Experiment results on two public CRS datasets demonstrate the effectiveness of our framework.Our code is publicly available at the link:https://anonymous.4open.science/r/LLMKB-6FD0.展开更多
Traveling wave(TW)fault location technology has been widely used in transmission systems due to its high accuracy and simplicity.Recently,there has been growing interest in applying this technology to medium voltage(M...Traveling wave(TW)fault location technology has been widely used in transmission systems due to its high accuracy and simplicity.Recently,there has been growing interest in applying this technology to medium voltage(MV)distribution lines.However,current practices in its deployment,signal measurement,and threshold setting are usually from the application experiences in transmission lines,despite significant differences in fault-induced wave characteristics between transmission and distribution systems.To address these issues,this paper investigates the feasibility and applicability of TW fault technology in MV overhead distribution lines through characteristic analysis of fault-induced TWs.The propagation characteristics of aerial mode and zero mode TWs on overhead distribution lines are studied.Furthermore,it evaluates the influence of critical distri-bution network components including distribution transformers,multi-branch configurations,and busbar structures on wave propagation characteristics.Deployment strategies for traveling wave fault location(TWFL)devices is proposed to address the unique challenges of distribution networks,while the fault location method is also improved.Field test results demonstrate the effectiveness of the proposed methodology,showing improved fault detection accuracy and system reliability in distri-bution network applications.This research provides practical implementation suggestions for TWFL technology in distribution networks.展开更多
Tau plays a crucial role in several neurodegenerative diseases,collectively referred to as tauopathies.Therefore,targeting potential pathological changes in tau could enable useful therapeutic interventions.However,ta...Tau plays a crucial role in several neurodegenerative diseases,collectively referred to as tauopathies.Therefore,targeting potential pathological changes in tau could enable useful therapeutic interventions.However,tau is not an easy target because it dynamically interacts with microtubules and other cellular components,which presents a challenge for tau-targeted drugs.New cellular models could aid the development of mechanism-based tau-targeted therapies.展开更多
Correction to:Journal of Forestry Research(2025)36:124 https://doi.org/10.1007/s11676-025-01918-8 In this article the author’s name Yasutomo Hoshika was incorrectly written as Yasutoma Hoshika.The original article ha...Correction to:Journal of Forestry Research(2025)36:124 https://doi.org/10.1007/s11676-025-01918-8 In this article the author’s name Yasutomo Hoshika was incorrectly written as Yasutoma Hoshika.The original article has been corrected.展开更多
This study investigated biomass allocation in young stands of European beech(Fagus sylvatica L.)and Norway spruce(Picea abies(L.)Karst.)across 31 forest sites in the Western Carpathians,Slovakia.A total of 541 trees a...This study investigated biomass allocation in young stands of European beech(Fagus sylvatica L.)and Norway spruce(Picea abies(L.)Karst.)across 31 forest sites in the Western Carpathians,Slovakia.A total of 541 trees aged 2–10 years,originating from natural regeneration and planting,were destructively sampled to quantify biomass in four components:foliage,branches,stems,and roots.Generalized non-linear least squares(GNLS)models with a weighing variance function outperformed log-transformed seemingly unrelated regression(SUR)models in terms of accuracy and robustness,especially for foliage and branch biomass.When using height as the predictor,SUR models tended to underestimate biomass in planted beech,leading to notable underprediction of aboveground and total biomass.Biomass allocation patterns varied significantly by species and regeneration origin.Using a non-linear system of equations and component ratio modelling,we found out that planted spruce displayed low variability and a consistent dominance of needle biomass,while naturally regenerated beech showed greater variability and a higher proportion of stem biomass,reflecting stronger competition-driven vertical growth.Interspecific differences in total biomass were more pronounced when using tree height,with spruce generally exhibiting greater biomass than beech at equivalent heights.Overall,stem base diameter marginally outperformed tree height as a predictor of biomass.However,tree height-based models showed strong performance and are particularly suitable for integration with remote sensing applications.These findings can directly support forest managers and modellers in comparing regeneration methods and biomass estimation approaches for early-stage stand development,carbon accounting,and remote sensing calibration.展开更多
Federated Learning(FL)enables joint training over distributed devices without data exchange but is highly vulnerable to attacks by adversaries in the form of model poisoning and malicious update injection.This work pr...Federated Learning(FL)enables joint training over distributed devices without data exchange but is highly vulnerable to attacks by adversaries in the form of model poisoning and malicious update injection.This work proposes Secured-FL,a blockchain-based defensive framework that combines smart contract-based authentication,clustering-driven outlier elimination,and dynamic threshold adjustment to defend against adversarial attacks.The framework was implemented on a private Ethereum network with a Proof-of-Authority consensus algorithm to ensure tamper-resistant and auditable model updates.Large-scale simulation on the Cyber Data dataset,under up to 50%malicious client settings,demonstrates Secured-FL achieves 6%-12%higher accuracy,9%-15%lower latency,and approximately 14%less computational expense compared to the PPSS benchmark framework.Additional tests,including confusion matrices,ROC and Precision-Recall curves,and ablation tests,confirm the interpretability and robustness of the defense.Tests for scalability also show consistent performance up to 500 clients,affirming appropriateness to reasonably large deployments.These results make Secured-FL a feasible,adversarially resilient FL paradigm with promising potential for application in smart cities,medicine,and other mission-critical IoT deployments.展开更多
Chalcogenide perovskites(CPs)based on zirconium(Zr)and hafnium(Hf)are becoming increasingly attractive as a new class of materials for next-generation solar cells.CPs with the ABX_(3) structure stand out due to their ...Chalcogenide perovskites(CPs)based on zirconium(Zr)and hafnium(Hf)are becoming increasingly attractive as a new class of materials for next-generation solar cells.CPs with the ABX_(3) structure stand out due to their attractive optical and electrical properties,such as efficient light absorption,direct bandgaps in the range of 1.1–2.1 eV,and remarkable defect tolerance,making them a compelling alternative to hybrid and double perovskites for solar energy conversion.Although theoretical studies have progressed rapidly,experimental verification still faces challenges such as the high synthesis temperatures required(>900℃),particularly in producing high-quality,phase-pure thin films and scalable solution-based processes.In this review,we aim to provide a comprehensive overview of the progress and remaining obstacles in advancing CP-based materials and devices.First,we describe the structure and composition as well as the different CPs in which the B site is occupied by Zr and Hf.Second,we summarize the methods used and the challenges that researchers face in producing an effective device.We highlight the main features that make CPs a preferred option for photovoltaic and other applications.Third,we look at the progress made in simulating solar cells that can achieve a power conversion efficiency(PCE)of over 30%using SCAPS-1D software.In the end,challenges and future research directions toward the development of CP materials and devices are provided.Overall,this review will serve as a valuable resource for researchers in selecting suitable strategies to achieve high-performance optoelectronic devices.展开更多
Federated learning is a decentralized model training paradigm with significant potential.However,the quality of Federated Network’s client updates can vary due to non-IID data distributions,leading to suboptimal glob...Federated learning is a decentralized model training paradigm with significant potential.However,the quality of Federated Network’s client updates can vary due to non-IID data distributions,leading to suboptimal global models.To address this issue,we propose a novel client selection strategy called FedPA(Performance-Based Federated Averaging).This proposed model selectively aggregates client updates based on a predefined performance threshold.Only clients whose local models achieve an F1 score of 70%or higher after training are included in the aggregation process.Clients below this threshold receive the updated global model but do not contribute their parameters.In this way,the low-performance clients are still in the process of learning and,after some rounds,will be able to contribute.If no client meets the performance threshold in a given round,the system falls back to standard FedAvg aggregation.This ensures the global model continues to improve even when most clients perform poorly.We evaluate FedPA on a subset of the MURA dataset for abnormality detection in radiographs of four bone types.Compared to baseline federated learning algorithms such as Federated Averaging(FedAvg),Federated Proximal(FedProx),Federated Stochastic Gradient Descent(FedSGD),and Federated Batch Normalization(FedBN),FedPA consistently ranks first or second across key performance metrics,particularly in accuracy,F1 score,and recall.Moreover,FedPA demonstrates notable efficiency,achieving the lowest average round time(≈2270 s)and minimal memory usage(≈645.58 MB),all without relying on GPU resources.These results highlight FedPA’s effectiveness in improving global model quality while reducing computational overhead,positioning it as a promising approach for real-world federated learning applications in resource-constrained environments.展开更多
The original online version of this article was revised:Several errors occurred in the published version of the article.These have now been corrected as follows:Page 2,section"2.2 Laser Texturing Procedure of Sur...The original online version of this article was revised:Several errors occurred in the published version of the article.These have now been corrected as follows:Page 2,section"2.2 Laser Texturing Procedure of Surfaces",line 2:The device name was corrected from"YDFLP-E-50-M8"to"YDFLP-50-M8."Page 3,Section 2.4:The phrase"95%confidence interval"has been corrected to"95%confidence level."Page 3,Figure 1 caption:The phrase"fandg"has been corrected to"f and g."The order"C4 and C12"has been reversed to"C12 and C4,"in accordance with the display order in the figure.Page 4,Figure reference:The phrase"Figs.4c and d"has been corrected to"Figs.5b and c."Page 5,paragraph starting with"The ANOVA results are presented...":The phrase"95%confidence interval"has been corrected to"95%confidence level."展开更多
Maize(Zea mays L.)is recognized as one of the most significant cereal crops worldwide,serving as a primary source of human food,animal feed,and industrial raw materials.With increasing diversification of market demand...Maize(Zea mays L.)is recognized as one of the most significant cereal crops worldwide,serving as a primary source of human food,animal feed,and industrial raw materials.With increasing diversification of market demands for specialty maize varieties,distinctive fresh produce cultivars characterized by unique textures have gained considerable popularity among consumers(Boyer and Shannon 1984).Notably,sweet maize is often referred to as the‘King of fruits and vegetables'due to its richness in polysaccharides,dietary fiber,trace elements,vitamins,linoleic acid,and other essential nutrients(Revilla et al.2021).展开更多
基金financially supported by the National Natural Science Foundation of China(Nos.22272118,22172111,and 22309134)the Science and Technology Commission of Shanghai Municipality,China(Nos.22ZR1464100,20ZR1460300,and 19DZ2271500)+2 种基金the China Postdoctoral Science Foundation(2022M712402),the Shanghai Rising-Star Program(23YF1449200)the Zhejiang Provincial Science and Technology Project(2022C01182)the Fundamental Research Funds for the Central Universities(2023-3-YB-07)。
文摘Carbon superstructures with multiscale hierarchies and functional attributes represent an appealing cathode candidate for zinc hybrid capacitors,but their tailor-made design to optimize the capacitive activity remains a confusing topic.Here we develop a hydrogen-bond-oriented interfacial super-assembly strategy to custom-tailor nanosheet-intertwined spherical carbon superstructures(SCSs)for Zn-ion storage with double-high capacitive activity and durability.Tetrachlorobenzoquinone(H-bond acceptor)and dimethylbenzidine(H-bond donator)can interact to form organic nanosheet modules,which are sequentially assembled,orientally compacted and densified into well-orchestrated superstructures through multiple H-bonds(N-H···O).Featured with rich surface-active heterodiatomic motifs,more exposed nanoporous channels,and successive charge migration paths,SCSs cathode promises high accessibility of built-in zincophilic sites and rapid ion diffusion with low energy barriers(3.3Ωs-0.5).Consequently,the assembled Zn||SCSs capacitor harvests all-round improvement in Zn-ion storage metrics,including high energy density(166 Wh kg-1),high-rate performance(172 m Ah g^(-1)at 20 A g^(-1)),and long-lasting cycling lifespan(95.5%capacity retention after 500,000 cycles).An opposite chargecarrier storage mechanism is rationalized for SCSs cathode to maximize spatial capacitive charge storage,involving high-kinetics physical Zn^(2+)/CF_(3)SO_(3)-adsorption and chemical Zn^(2+)redox with carbonyl/pyridine groups.This work gives insights into H-bond-guided interfacial superassembly design of superstructural carbons toward advanced energy storage.
基金financially supported by the Program for the Development of Science and Technology of Jilin Province(Nos.YDZJ202201ZYTS313,YDZJ202201ZYTS395,20240402072GH,and 20240101004JJ)the National Natural Science Foundation of China(Nos.22201097 and 52171210)。
文摘Improving the surface atoms utilization efficiency of catalysts is extremely important for large-scale H_(2)production by electrochemical water splitting,but it remains a great challenge.Herein,we reported two kinds of Mo O_(3)-polyoxometalate hybrid nanobelt superstructures(MoO_(3)-POM HNSs,POM=PW_(12)O_(40)and Si W_(12)O_(40))using a simple hydrothermal method.Such superstructure with highly uniform nanoparticles as building blocks can expose more surface atoms and emanate increased specific surface area.The incorporated POMs generated abundant oxygen vacancies,improved the electronic mobility,and modulated the surface electronic structure of MoO_(3),allowing to optimize the H^(*)adsorption/desorption and dehydrogenation kinetics of catalyst.Notably,the as-prepared MoO_(3)-PW_(12)O_(40)HNSs electrodes not only displayed the low overpotentials of 108 mV at 10 mA/cm^(2)current density in 0.5 mol/L H_(2)SO_(4)electrolyte but also displayed excellent long-term stability.The hydrogen evolution reaction(HER)performance of MoO_(3)-POM superstructures is significantly better than that of corresponding bulk materials MoO_(3)@PW_(12)O_(40)and Mo O_(3)@Si W_(12)O_(40),and the overpotentials are about 8.3 and 4.9 times lower than that of single Mo O_(3).This work opens an avenue for designing highly surface-exposed catalysts for electrocatalytic H_(2)production and other electrochemical applications.
基金financially supported by the National Natural Science Foundation of China (Nos. 22272118, 22172111, 21905207, and 22309134)the Science and Technology Commission of Shanghai Municipality (Nos. 22ZR1464100, 20ZR1460300, and 19DZ2271500)+2 种基金China Postdoctoral Science Foundation (No. 2022M712402), Shanghai Rising-Star Program (No. 23YF1449200)Zhejiang Provincial Science and Technology Project (No. 2022C01182)the Fundamental Research Funds for the Central Universities (Nos. 22120210529 and 2023–3-YB-07)。
文摘Designing carbon materials with ideal stable hierarchical porous structures and fiexible functional properties for efficient and sustainable Zn2+ion storage still faces great challenges. Herein, the threedimensional carbon superstructures with spherical nanofiower-like structures were tailor-made by the self-assembly strategy. Specifically, organic polymer units(i.e., organic motifs) were formed by tetrachloro-p-benzoquinone(TBQ) and 2,6-diamino anthraquinone(DAQ) via a noble-metal-free catalyzed coupling reaction. Subsequently, the organic motifs assemble into spherical nanofiower-like superstructures induced by intermolecular hydrogen bonding and aromatic π-π stacking interactions. Welldesigned carbon superstructures can provide a stable backbone that effectively blocks structural stacking and collapse. Meanwhile, the hierarchical porous structures in 3D carbon superstructures provide continuous charge transport pathways to greatly shorten the ion diffusion distance, and as a result, the carbon superstructures-based zinc-ion hybrid capacitors(ZIHCs) provide a capacity of 245 m Ah/g at 0.5 A/g, a high energy density of 152 Wh/kg and an ultra-long life of 300,000 cycles at 20 A/g. The excellent electrochemical performance is also attributed to the corresponding charge storage mechanism, i.e., the alternate binding of Zn^(2+)/CF_(3)SO_(3)^(-) ions. Besides, the high-level N/O motifs improve the surface properties of the carbon superstructures and reduce the ion migration barriers for more efficient charge storage. This paper provides insights into the design of advanced carbon-based cathodes and presents a fundamental understanding of their charge storage mechanisms.
基金supported by the Australian Research Council Linkage Project(No.LP200200717)co sponsored by Newmont Corporation(United States)and Vega Industries(India)+1 种基金the Powder Diffraction Beamline at the Australia’s Nuclear Science and Technology Organisation(No.PDR19870),Australiathe Centre for Microscopy and Microanalysis at the University of Queensland(No.1366),Australia。
文摘Pyrrhotite naturally occurs in various superstructures including magnetic(4C)and non-magnetic(5C,6C)types,each with distinct physicochemical properties and flotation behaviors.Challenges in accurately identifying and quantifying these superstructures hinder the optimization of pyrrhotite depression in flotation processes.To address this critical issue,synchrotron X-ray powder diffraction(S-XRPD)with Rietveld refinement was employed to quantify the distribution of superstructures in the feed and flotation concentrates of a copper–gold ore.To elucidate the mechanisms influencing depression,density functional theory(DFT)calculations were conducted to explore the electronic structures and surface reactivity of the pyrrhotite superstructures toward the adsorption of water,oxygen and hydroxyl ions(OH-)as dominant species present in the flotation process.S-XRPD analysis revealed that flotation recovery rates of pyrrhotite followed the order of 4C<6C<5C.DFT calculations indicated that the Fe 3d and S 3p orbital band centers exhibited a similar trend relative to the Fermi level with 4C being the closest.The Fe3d band center suggested that the 4C structure possessed a more reactive surface toward the oxygen reduction reaction,promoting the formation of hydrophilic Fe-OH sites.The S 3p band center order also implied that xanthate on the non-magnetic 5C and 6C surfaces could oxidize to dixanthogen,increasing hydrophobicity and floatability,while 4C formed less hydrophobic metal-xanthate complexes.Adsorption energy and charge transfer analyses of water,hydroxyl ions and molecular oxygen further supported the high reactivity and hydrophilic nature of 4C pyrrhotite.The strong bonding with hydroxyl ions indicated enhanced surface passivation by hydrophilic Fe–OOH complexes,aligning with the experimentally observed flotation order(4C<6C<5C).These findings provide a compelling correlation between experimental flotation results and electronic structure calculations,delivering crucial insights for optimizing flotation processes and improving pyrrhotite depression.This breakthrough opens up new opportunities to enhance the efficiency of flotation processes in the mining industry.
基金supported by the Natural Science Foundation of Shandong Province(Nos.ZR2021ME194,2022TSGC2448,and 2023TSGC0545)the Key Technology Research and Development Program of Shandong Province(No.2021ZLGX01).
文摘The novel fabrication of multiple components and unique heterostructure can inject infinite vitality into the electromagnetic wave(EMW)attenuation field.Herein,through the self-assembly of polyimide com-plexes and catalytic chemical vapor deposition,porous carbon microflowers were synthesized accompa-nied by carbon nanotubes(CNTs).By regulating the metal ions,the composition and structure of the as-obtained hybrids are modified correspondingly,and thus the adjustable thermal management and EMW absorption capabilities are obtained.In detail,the rich pores and huge specific surface area endow the hierarchical structures with distinguished thermal insulation ability(λ<0.07).The carbon framework and CNTs are beneficial for consuming EMWs via conductive loss and defect polarization loss while reduc-ing the filling ratio and thickness.The doped heteroatoms and abundant heterointerfaces generate ample dipole polarization and interface polarization losses(supported by DFT calculation).The metal nanopar-ticles uniformly embedded in the carbon framework offer optimized impedance matching,proper de-fect polarization,and suitable magnetic loss.Accordingly,the synergy of magnetic-dielectric balance and flower-like superstructure enables FNCFN2 and NNCFN2 to accomplish remarkable microwave absorbing capacity with thin thickness(14 wt.%).Therefore,respectable specific reflection loss and specific effec-tive absorption bandwidth are acquired(215.39 dB mm^(-1) and 22.10 GHz mm^(-1),257.23 dB mm^(-1) and 22.12 GHz mm^(-1) respectively),superior to those of certain renowned carbon-based absorbers.The simu-lation results of electric field intensity distributions,power loss density,and radar cross section reduction(maximum value of 36.02 dBm2)also verify the prominent radar stealth capability.Moreover,the cus-tomizable approach can be applied to other metals to obtain fulfilling behaviors.Henceforth,this work provides profound insights into the relationship between structure and performance,and proposes an efficient path for mass-producing multifunctional and high-performance EMW absorbers with excellent thermal properties.
基金financially supported by the National Natural Science Foundation of China(No.21572271).
文摘A[3+4]annulation of α-substituted allenes and Schiff bases is reported.This methodology serves as a conduit for the construction of a series of biologically important benzazepine derivatives in good to excellent yields under mild conditions by an unprecedented mode involving β’-carbon of α-substituted allenes and the proposed mechanism is supported by capturing the intermediate.Moreover,this class of benzazepine derivatives exhibited potential ability of cytotoxicity toward cancer cells.
基金funded by“The Factors Affecting the Accuracy of Wind Resource Assessment and Comprehensive Post-Evaluation Techniques for Operating Wind Power Projects,”grant number YJ24.002“The Research and Application of Future Medium to Long Term Wind Resource Assessment for Wind Farms Based on Artificial Intelligence Project,”grant number 2023021。
文摘Improving the accuracy of the evaluation of the performance of wind farms in large wind power bases located in complex terrain under the actual atmosphere is crucial to the sustainable development of wind power.To this end,this study combined the Weather Research and Forecasting(WRF)model with the Wind Farm Parameterization(WFP)method to investigate the wake characteristics and operational performance of large onshore wind farms in the complex terrain of Jiuquan City,Gansu Province,China.The research results showed that after verification,the systematic error of the WRF simulations was less than 3%.The WRF model and the WFP scheme simulated a significant warming phenomenon within the wind power base area,while a cooling effect was observed outside.The analysis of the wake effects indicated that the impact of PhaseⅠconstruction on PhaseⅡconstruction of the wind power base was minimal.During the operation of the entire wind power base,the wind speed within the wind farm decreased by approximately 10%,and the influence range of the predominant wind direction extended over a hundred kilometers downwind.The research conclusions provide a powerful scientific basis for optimizing design and operation,improving efficiency,minimizing the negative impacts on adjacent wind turbines,and ensuring the sustainable development of wind energy through dynamic planning and scientific assessment.
基金funded by University of Transport and Communications(UTC)under grant number T2025-CN-004.
文摘Reversible data hiding(RDH)enables secret data embedding while preserving complete cover image recovery,making it crucial for applications requiring image integrity.The pixel value ordering(PVO)technique used in multi-stego images provides good image quality but often results in low embedding capability.To address these challenges,this paper proposes a high-capacity RDH scheme based on PVO that generates three stego images from a single cover image.The cover image is partitioned into non-overlapping blocks with pixels sorted in ascending order.Four secret bits are embedded into each block’s maximum pixel value,while three additional bits are embedded into the second-largest value when the pixel difference exceeds a predefined threshold.A similar embedding strategy is also applied to the minimum side of the block,including the second-smallest pixel value.This design enables each block to embed up to 14 bits of secret data.Experimental results demonstrate that the proposed method achieves significantly higher embedding capacity and improved visual quality compared to existing triple-stego RDH approaches,advancing the field of reversible steganography.
文摘Conversational recommender systems(CRSs)focus on refining preferences and providing personalized recommendations through natural language interactions and dialogue history.Large language models(LLMs)have shown outstanding performance across various domains,thereby prompting researchers to investigate their applicability in recommendation systems.However,due to the lack of task-specific knowledge and an inefficient feature extraction process,LLMs still have suboptimal performance in recommendation tasks.Therefore,external knowledge sources,such as knowledge graphs(KGs)and knowledge bases(KBs),are often introduced to address the issue of data sparsity.Compared to KGs,KBs possess higher retrieval efficiency,making them more suitable for scenarios where LLMs serve as recommenders.To this end,we introduce a novel framework integrating LLMs with KBs for enhanced retrieval generation,namely LLMKB.LLMKB initially leverages structured knowledge to create mapping dictionaries,extracting entity-relation information from heterogeneous knowledge to construct KBs.Then,LLMKB achieves the embedding calibration between user information representations and documents in KBs through retrieval model fine-tuning.Finally,LLMKB employs retrievalaugmented generation to produce recommendations based on fused text inputs,followed by post-processing.Experiment results on two public CRS datasets demonstrate the effectiveness of our framework.Our code is publicly available at the link:https://anonymous.4open.science/r/LLMKB-6FD0.
基金supported by the National Natural Sci-ence Foundation of China(No.52107109).
文摘Traveling wave(TW)fault location technology has been widely used in transmission systems due to its high accuracy and simplicity.Recently,there has been growing interest in applying this technology to medium voltage(MV)distribution lines.However,current practices in its deployment,signal measurement,and threshold setting are usually from the application experiences in transmission lines,despite significant differences in fault-induced wave characteristics between transmission and distribution systems.To address these issues,this paper investigates the feasibility and applicability of TW fault technology in MV overhead distribution lines through characteristic analysis of fault-induced TWs.The propagation characteristics of aerial mode and zero mode TWs on overhead distribution lines are studied.Furthermore,it evaluates the influence of critical distri-bution network components including distribution transformers,multi-branch configurations,and busbar structures on wave propagation characteristics.Deployment strategies for traveling wave fault location(TWFL)devices is proposed to address the unique challenges of distribution networks,while the fault location method is also improved.Field test results demonstrate the effectiveness of the proposed methodology,showing improved fault detection accuracy and system reliability in distri-bution network applications.This research provides practical implementation suggestions for TWFL technology in distribution networks.
文摘Tau plays a crucial role in several neurodegenerative diseases,collectively referred to as tauopathies.Therefore,targeting potential pathological changes in tau could enable useful therapeutic interventions.However,tau is not an easy target because it dynamically interacts with microtubules and other cellular components,which presents a challenge for tau-targeted drugs.New cellular models could aid the development of mechanism-based tau-targeted therapies.
文摘Correction to:Journal of Forestry Research(2025)36:124 https://doi.org/10.1007/s11676-025-01918-8 In this article the author’s name Yasutomo Hoshika was incorrectly written as Yasutoma Hoshika.The original article has been corrected.
基金funded by the grant“EVA4.0”,No.Z.02.1.01/0.0/0.0/16_019/0000803 supported by OP RDE as well as by the projects APVV-19-0387,APVV-22-0056,and APVV-23-0293 from the Slovak Research and Development Agencyco-funded by the European Commission under the Horizon Europe Teaming for Excellence action+1 种基金project Ligno Silvagrant agreement No.101059552。
文摘This study investigated biomass allocation in young stands of European beech(Fagus sylvatica L.)and Norway spruce(Picea abies(L.)Karst.)across 31 forest sites in the Western Carpathians,Slovakia.A total of 541 trees aged 2–10 years,originating from natural regeneration and planting,were destructively sampled to quantify biomass in four components:foliage,branches,stems,and roots.Generalized non-linear least squares(GNLS)models with a weighing variance function outperformed log-transformed seemingly unrelated regression(SUR)models in terms of accuracy and robustness,especially for foliage and branch biomass.When using height as the predictor,SUR models tended to underestimate biomass in planted beech,leading to notable underprediction of aboveground and total biomass.Biomass allocation patterns varied significantly by species and regeneration origin.Using a non-linear system of equations and component ratio modelling,we found out that planted spruce displayed low variability and a consistent dominance of needle biomass,while naturally regenerated beech showed greater variability and a higher proportion of stem biomass,reflecting stronger competition-driven vertical growth.Interspecific differences in total biomass were more pronounced when using tree height,with spruce generally exhibiting greater biomass than beech at equivalent heights.Overall,stem base diameter marginally outperformed tree height as a predictor of biomass.However,tree height-based models showed strong performance and are particularly suitable for integration with remote sensing applications.These findings can directly support forest managers and modellers in comparing regeneration methods and biomass estimation approaches for early-stage stand development,carbon accounting,and remote sensing calibration.
文摘Federated Learning(FL)enables joint training over distributed devices without data exchange but is highly vulnerable to attacks by adversaries in the form of model poisoning and malicious update injection.This work proposes Secured-FL,a blockchain-based defensive framework that combines smart contract-based authentication,clustering-driven outlier elimination,and dynamic threshold adjustment to defend against adversarial attacks.The framework was implemented on a private Ethereum network with a Proof-of-Authority consensus algorithm to ensure tamper-resistant and auditable model updates.Large-scale simulation on the Cyber Data dataset,under up to 50%malicious client settings,demonstrates Secured-FL achieves 6%-12%higher accuracy,9%-15%lower latency,and approximately 14%less computational expense compared to the PPSS benchmark framework.Additional tests,including confusion matrices,ROC and Precision-Recall curves,and ablation tests,confirm the interpretability and robustness of the defense.Tests for scalability also show consistent performance up to 500 clients,affirming appropriateness to reasonably large deployments.These results make Secured-FL a feasible,adversarially resilient FL paradigm with promising potential for application in smart cities,medicine,and other mission-critical IoT deployments.
基金the“Initiative on Energy Research”,founded by the University Mohammed VI Polytechnic,for the financial support through the project“Toward efficient,stable,environmentally friendly,and scalable Perovskite Solar Cells”the financial support from DAAD and BMZ through the WE-AFRICA project+1 种基金the U.S.Department of Energy,Office of Science,Basic Energy Sciences,Early Career Program,under Award No.DOE DESC0025350the National Academies of Sciences,Engineering,and Medicine for their support through the U.S.-Africa Frontiers Fellowship。
文摘Chalcogenide perovskites(CPs)based on zirconium(Zr)and hafnium(Hf)are becoming increasingly attractive as a new class of materials for next-generation solar cells.CPs with the ABX_(3) structure stand out due to their attractive optical and electrical properties,such as efficient light absorption,direct bandgaps in the range of 1.1–2.1 eV,and remarkable defect tolerance,making them a compelling alternative to hybrid and double perovskites for solar energy conversion.Although theoretical studies have progressed rapidly,experimental verification still faces challenges such as the high synthesis temperatures required(>900℃),particularly in producing high-quality,phase-pure thin films and scalable solution-based processes.In this review,we aim to provide a comprehensive overview of the progress and remaining obstacles in advancing CP-based materials and devices.First,we describe the structure and composition as well as the different CPs in which the B site is occupied by Zr and Hf.Second,we summarize the methods used and the challenges that researchers face in producing an effective device.We highlight the main features that make CPs a preferred option for photovoltaic and other applications.Third,we look at the progress made in simulating solar cells that can achieve a power conversion efficiency(PCE)of over 30%using SCAPS-1D software.In the end,challenges and future research directions toward the development of CP materials and devices are provided.Overall,this review will serve as a valuable resource for researchers in selecting suitable strategies to achieve high-performance optoelectronic devices.
文摘Federated learning is a decentralized model training paradigm with significant potential.However,the quality of Federated Network’s client updates can vary due to non-IID data distributions,leading to suboptimal global models.To address this issue,we propose a novel client selection strategy called FedPA(Performance-Based Federated Averaging).This proposed model selectively aggregates client updates based on a predefined performance threshold.Only clients whose local models achieve an F1 score of 70%or higher after training are included in the aggregation process.Clients below this threshold receive the updated global model but do not contribute their parameters.In this way,the low-performance clients are still in the process of learning and,after some rounds,will be able to contribute.If no client meets the performance threshold in a given round,the system falls back to standard FedAvg aggregation.This ensures the global model continues to improve even when most clients perform poorly.We evaluate FedPA on a subset of the MURA dataset for abnormality detection in radiographs of four bone types.Compared to baseline federated learning algorithms such as Federated Averaging(FedAvg),Federated Proximal(FedProx),Federated Stochastic Gradient Descent(FedSGD),and Federated Batch Normalization(FedBN),FedPA consistently ranks first or second across key performance metrics,particularly in accuracy,F1 score,and recall.Moreover,FedPA demonstrates notable efficiency,achieving the lowest average round time(≈2270 s)and minimal memory usage(≈645.58 MB),all without relying on GPU resources.These results highlight FedPA’s effectiveness in improving global model quality while reducing computational overhead,positioning it as a promising approach for real-world federated learning applications in resource-constrained environments.
文摘The original online version of this article was revised:Several errors occurred in the published version of the article.These have now been corrected as follows:Page 2,section"2.2 Laser Texturing Procedure of Surfaces",line 2:The device name was corrected from"YDFLP-E-50-M8"to"YDFLP-50-M8."Page 3,Section 2.4:The phrase"95%confidence interval"has been corrected to"95%confidence level."Page 3,Figure 1 caption:The phrase"fandg"has been corrected to"f and g."The order"C4 and C12"has been reversed to"C12 and C4,"in accordance with the display order in the figure.Page 4,Figure reference:The phrase"Figs.4c and d"has been corrected to"Figs.5b and c."Page 5,paragraph starting with"The ANOVA results are presented...":The phrase"95%confidence interval"has been corrected to"95%confidence level."
基金supported by the Youth Research Foundation of Beijing Academy of Agriculture and Forestry Sciences,China(QNJJ202420)the Beijing Science and Technology Association Youth Lifting Project,Chinathe Beijing Municipal Rural Revitalization Agricultural Science and Technology Development Project,China(NY2401020224)。
文摘Maize(Zea mays L.)is recognized as one of the most significant cereal crops worldwide,serving as a primary source of human food,animal feed,and industrial raw materials.With increasing diversification of market demands for specialty maize varieties,distinctive fresh produce cultivars characterized by unique textures have gained considerable popularity among consumers(Boyer and Shannon 1984).Notably,sweet maize is often referred to as the‘King of fruits and vegetables'due to its richness in polysaccharides,dietary fiber,trace elements,vitamins,linoleic acid,and other essential nutrients(Revilla et al.2021).
