This work contributes to the theoretical foundation for pricing in data markets and offers practical insights for managing digital data exchanges in the era of big data.We propose a structured pricing model for data e...This work contributes to the theoretical foundation for pricing in data markets and offers practical insights for managing digital data exchanges in the era of big data.We propose a structured pricing model for data exchanges transitioning from quasi-public to marketoriented operations.To address the complex dynamics among data exchanges,suppliers,and consumers,the authors develop a threestage Stackelberg game framework.In this model,the data exchange acts as a leader setting transaction commission rates,suppliers are intermediate leaders determining unit prices,and consumers are followers making purchasing decisions.Two pricing strategies are examined:the Independent Pricing Approach(IPA)and the novel Perfectly Competitive Pricing Approach(PCPA),which accounts for competition among data providers.Using backward induction,the study derives subgame-perfect equilibria and proves the existence and uniqueness of Stackelberg equilibria under both approaches.Extensive numerical simulations are carried out in the model,demonstrating that PCPA enhances data demander utility,encourages supplier competition,increases transaction volume,and improves the overall profitability and sustainability of data exchanges.Social welfare analysis further confirms PCPA’s superiority in promoting efficient and fair data markets.展开更多
Secure and automated sharing of medical information among different medical entities/stakeholders like patients,hospitals,doctors,law enforcement agencies,health insurance companies etc.,in a standard format has alway...Secure and automated sharing of medical information among different medical entities/stakeholders like patients,hospitals,doctors,law enforcement agencies,health insurance companies etc.,in a standard format has always been a challenging problem.Current methods for ensuring compliance with medical privacy laws require specialists who are deeply familiar with these laws'complex requirements to verify the lawful exchange of medical information.This article introduces a Smart Medical Data Exchange Engine(SDEE)designed to automate the extracting of logical rules from medical privacy legislation using advanced techniques.These rules facilitate the secure extraction of information,safeguarding patient privacy and confidentiality.In addition,SMDEE can generate standardised clinical documents according to Health Level 7(HL7)standards and also standardise the nomenclature of requested medical data,enabling accurate decision-making when accessing patient data.All access requests to patient information are processed through SMDEE to ensure authorised access.The proposed system's efficacy is evaluated using the Health Insurance Portability and Accountability Act(HIPAA),a fundamental privacy law in the United States.However,SMDEE's flexibility allows its application worldwide,accommodating various medical privacy laws.Beyond facilitating global information exchange,SMDEE aims to enhance international patients'timely and appropriate treatment.展开更多
This paper employs Granger causality analysis and the generalized impulse response function(GIRF)to study the higher-order moment spillover effects among Bitcoin,stock markets,and foreign exchange markets in the U.S.U...This paper employs Granger causality analysis and the generalized impulse response function(GIRF)to study the higher-order moment spillover effects among Bitcoin,stock markets,and foreign exchange markets in the U.S.Using intraday high-frequency data,the research focuses on the interactions across higher-order moments,including volatility,jumps,skewness,and kurtosis.The results reveal significant bidirectional spillover effects between Bitcoin and traditional financial assets,particularly in terms of volatility and jump behavior,indicating that the cryptocurrency market has become a crucial component of global financial risk transmission.This study provides new theoretical perspectives and policy recommendations for global asset allocation,market regulation,and risk management,underscoring the importance of proactive management measures in addressing the complex risk interactions between cryptocurrencies and traditional financial markets.展开更多
The ionothermal reaction between CuCl_(2),1,4-bis(1,2,4-triazol-1-ylmethyl)benzene(BBTZ),and(NH_(4))_(6)Mo_(7)O_(24) in 1-ethyl-3-methylimidazolium bromide((Emim)Br)led to a new octamolybdate-based coordination polyme...The ionothermal reaction between CuCl_(2),1,4-bis(1,2,4-triazol-1-ylmethyl)benzene(BBTZ),and(NH_(4))_(6)Mo_(7)O_(24) in 1-ethyl-3-methylimidazolium bromide((Emim)Br)led to a new octamolybdate-based coordination polymer(Emim)2[Cu(BBTZ)_(2)(β-Mo_(8)O_(26))](Mo_(8)-CP).Mo_(8)-CP was characterized by elemental analysis,thermogravime-try,IR,powder X-ray diffraction,and single-crystal X-ray diffraction.In Mo_(8)-CP,structural analysis reveals that Cu coordinates with BBTZ ligands to form an interlocked 1D chain.These chains are further bridged by(β-Mo_(8)O_(26))^(4-)to construct a 3D coordination polymer.Notably,(Emim)^(+)acts as a structure-directing agent,occupying the channels of the 3D coordination polymer.Based on this unique structure,the ion exchange properties of Mo_(8)-CP toward rare-earth ions were investigated.It has been found that the luminescent color of the material can be successfully regulat-ed by introducing Eu^(3+)or Tb^(3+)through ion exchange.CCDC:2475110,Mo_(8)-CP.展开更多
Earthquakes are highly destructive spatio-temporal phenomena whose analysis is essential for disaster preparedness and risk mitigation.Modern seismological research produces vast volumes of heterogeneous data from sei...Earthquakes are highly destructive spatio-temporal phenomena whose analysis is essential for disaster preparedness and risk mitigation.Modern seismological research produces vast volumes of heterogeneous data from seismic networks,satellite observations,and geospatial repositories,creating the need for scalable infrastructures capable of integrating and analyzing such data to support intelligent decision-making.Data warehousing technologies provide a robust foundation for this purpose;however,existing earthquake-oriented data warehouses remain limited,often relying on simplified schemas,domain-specific analytics,or cataloguing efforts.This paper presents the design and implementation of a spatio-temporal data warehouse for seismic activity.The framework integrates spatial and temporal dimensions in a unified schema and introduces a novel array-based approach for managing many-to-many relationships between facts and dimensions without intermediate bridge tables.A comparative evaluation against a conventional bridge-table schema demonstrates that the array-based design improves fact-centric query performance,while the bridge-table schema remains advantageous for dimension-centric queries.To reconcile these trade-offs,a hybrid schema is proposed that retains both representations,ensuring balanced efficiency across heterogeneous workloads.The proposed framework demonstrates how spatio-temporal data warehousing can address schema complexity,improve query performance,and support multidimensional visualization.In doing so,it provides a foundation for integrating seismic analysis into broader big data-driven intelligent decision systems for disaster resilience,risk mitigation,and emergency management.展开更多
Proton exchange membrane fuel cells(PEMFCs)are considered as a promising renewable power source.However,the massive commercial application of PEMFCs has been greatly hindered by their high expense and less-satisfied p...Proton exchange membrane fuel cells(PEMFCs)are considered as a promising renewable power source.However,the massive commercial application of PEMFCs has been greatly hindered by their high expense and less-satisfied performance mainly due to the sluggish oxygen reduction reaction(ORR)kinetics even on state-of-the-art Pt catalyst.Octahedral PtNi nanoparticles(oct-PtNi NPs)with excellent ORR activity in a half-cell have been widely studied,while their performance in membrane electrode assembly(MEA)has much less reported.Herein,we investigated the MEA performance using the carbon supported oct-PtNi NPs(oct-PtNi/C)as the cathode catalyst.Under the mild acid washing condition,the surface Ni atoms of oct-PtNi/C were largely removed,and the performance of the MEA using the acid-leaching oct-PtNi/C(PNC-A)as the cathode catalyst was greatly improved.The maximum power density of the MEA reached 1.0 W·cm^(-2) with the cath-ode Pt loading of 0.2 mg·cm^(-2),which is 15%higher than that using Pt/C as the catalyst.After 30k cycles in the accelerated degradation test(ADT),the MEA using PNC-A as the catalyst showed a performance retention of 82%,higher than that of Pt/C(74%).The results reported here verify the possibility of using PNC-A as an advanced cathode catalyst in PEMFCs,thus enhancing the performance of PEMFCs while lowering the amount of expensive Pt.展开更多
A Tibetan art form bridges the past and present and connects cultures around the world.THANGKA,a unique form of Tibetan sacred painting,is gaining prominence globally due to its vibrant colors,exquisite craftsmanship,...A Tibetan art form bridges the past and present and connects cultures around the world.THANGKA,a unique form of Tibetan sacred painting,is gaining prominence globally due to its vibrant colors,exquisite craftsmanship,and profound religious and cultural significance.With the acceleration of globalization,this symbol of Tibetan culture that combines artistic expression with spirituality has become a bridge for cultural exchange between the East and the West.Recently,China Today spoke to Yixi Puncog,art collector and council member of the China Association for Preservation and Development of Tibetan Culture,to learn more about Thangka art,its role in international exchange,and how it is enhancing China’s cultural soft power.展开更多
Ningxia is an ethnic gathering area boasting abundant tourism and cultural resources.Developing the cause of tourism and culture is an important way to encourage all ethnic groups to respect differences,embrace divers...Ningxia is an ethnic gathering area boasting abundant tourism and cultural resources.Developing the cause of tourism and culture is an important way to encourage all ethnic groups to respect differences,embrace diversity,and demonstrate their interactions,exchanges,and integration in tourism activities.As an important preserve of the distinctive cultures of the Chinese nation and a prominent world tourist destination,Ningxia should strive to foster and consolidate the sense of a community with a shared future for the Chinese nation in developing its tourism and culture under the new historical conditions.It is imperative to advance the prosperity and development of tourism and culture in boosting ethnic interactions,exchanges,and integration through the formulation of tourism and cultural policies and plans,as well as the development and design of tourism and cultural projects.展开更多
Ovarian cancer(OC)is one of the leading causes of death related to gynecological cancer,with the main difficulty of its early diagnosis and a heterogeneous nature of tumor biomarkers.Machine learning(ML)has the potent...Ovarian cancer(OC)is one of the leading causes of death related to gynecological cancer,with the main difficulty of its early diagnosis and a heterogeneous nature of tumor biomarkers.Machine learning(ML)has the potential to process complex datasets and support decision-making in OC diagnosis.Nevertheless,traditional ML models tend to be biased,overfitting,noisy,and less generalized.Moreover,their black-box nature reduces interpretability and limits their practical clinical applicability.In this study,we introduce an explainable ensemble learning(EL)model,TreeX-Stack,based on a stacking architecture that employs tree-based learners such as Decision Tree(DT),Random Forest(RF),Gradient Boosting(GB),and Extreme Gradient Boosting(XGBoost)as base learners,and Logistic Regression(LR)as the meta-learner to enhance ovarian cancer(OC)diagnosis.Local Interpretable ModelAgnostic Explanations(LIME)are used to explain individual predictions,making the model outputs more clinically interpretable and applicable.The model is trained on the dataset that includes demographic information,blood test,general chemistry,and tumor markers.Extensive preprocessing includes handling missing data using iterative imputation with Bayesian Ridge and addressing multicollinearity by removing features with correlation coefficients above 0.7.Relevant features are then selected using the Boruta feature selection method.To obtain robust and unbiased performance estimates during hyperparameter tuning,nested cross-validation(CV)with grid search is employed,and all experiments are repeated five times to ensure statistical reliability.TreeX-Stack demonstrates excellent diagnostic performance,achieving an accuracy of 0.9027,a precision of 0.8673,a recall of 0.9391,and an F1-score of 0.9012.Feature-importance analyses using LIME and permutation importance highlight Human Epididymis Protein 4(HE4)as the most significant biomarker for OC.The combination of high predictive performance and interpretability makes TreeX-Stack a reliable tool for clinical decision support in OC diagnosis.展开更多
Accurately assessing the relationship between tree growth and climatic factors is of great importance in dendrochronology.This study evaluated the consistency between alternative climate datasets(including station and...Accurately assessing the relationship between tree growth and climatic factors is of great importance in dendrochronology.This study evaluated the consistency between alternative climate datasets(including station and gridded data)and actual climate data(fixed-point observations near the sampling sites),in northeastern China’s warm temperate zone and analyzed differences in their correlations with tree-ring width index.The results were:(1)Gridded temperature data,as well as precipitation and relative humidity data from the Huailai meteorological station,was more consistent with the actual climate data;in contrast,gridded soil moisture content data showed significant discrepancies.(2)Horizontal distance had a greater impact on the representativeness of actual climate conditions than vertical elevation differences.(3)Differences in consistency between alternative and actual climate data also affected their correlations with tree-ring width indices.In some growing season months,correlation coefficients,both in magnitude and sign,differed significantly from those based on actual data.The selection of different alternative climate datasets can lead to biased results in assessing forest responses to climate change,which is detrimental to the management of forest ecosystems in harsh environments.Therefore,the scientific and rational selection of alternative climate data is essential for dendroecological and climatological research.展开更多
To address the severe challenges of PM_(2.5) and ozone co-control during the"14^(th) Five-Year Plan"period and to enhance the precision and intelligence level of air environment governance,it is imperative t...To address the severe challenges of PM_(2.5) and ozone co-control during the"14^(th) Five-Year Plan"period and to enhance the precision and intelligence level of air environment governance,it is imperative to build an efficient comprehensive management platform for regional air quality.In this paper,the specific practice in Zibo City,Shandong Province is as an example to systematically analyze the top-level design,technical implementation,and innovative application of a comprehensive management platform for regional air quality integrating"perception monitoring,data fusion,research judgment of early warnings,analysis of sources,collaborative dispatching,and evaluation assessment".Through the construction of an"sky-air-ground"integrated three-dimensional monitoring network,the platform integrates multi-source heterogeneous environmental data,and employs big data,cloud computing,artificial intelligence,CALPUFF/CMAQ,and other numerical model technologies to achieve comprehensive perception,precise prediction,intelligent source tracing,and closed-loop management of air pollution.The platform innovatively establishes a full-process closed-loop management mechanism of"data-early warning-disposition-evaluation",and achieves a fundamental transformation from passive response to active anticipation and from experience-based judgment to data driving in environmental supervision.The application results show that this platform significantly improves the scientific decision-making ability and collaborative execution efficiency of air pollution governance in Zibo City,providing a replicable and scalable comprehensive solution for similar industrial cities to achieve the continuous improvement of air quality.展开更多
We successfully incorporated phenyl groups into a small-molecule quaternary ammonium cross-linker and synthesized cross-linked polybenzimidazole membranes via a one-step cross-linking process.Compared with conventiona...We successfully incorporated phenyl groups into a small-molecule quaternary ammonium cross-linker and synthesized cross-linked polybenzimidazole membranes via a one-step cross-linking process.Compared with conventional quaternary ammonium-crosslinked benzimidazole membranes,the introduction of phenyl groups significantly increases the free volume within the membrane.After phosphoric acid doping,the benzimidazole membrane with larger free volume retains more phosphoric acid compared to conventional quaternary ammonium-crosslinked membranes,forming an extensive hydrogen-bonding network that effectively enhances its anhydrous proton conductivity.The anhydrous proton conductivity reaches 91 mS·cm^(-1)at 160℃,substantially higher than that of conventional quaternary ammonium-crosslinked membranes with the same mass fraction.Benefiting from the improved conductivity,the membrane electrode assembly exhibits reduced ohmic polarization,achieving a peak power density of 792 mW·cm^(-2)at 160℃.展开更多
tRNA-derived small RNAs(tsRNAs),as a class of regulatory small noncoding RNA,have been implicated in a wide variety of human diseases.Large amounts of tsRNA–disease associations have been identified in recent years f...tRNA-derived small RNAs(tsRNAs),as a class of regulatory small noncoding RNA,have been implicated in a wide variety of human diseases.Large amounts of tsRNA–disease associations have been identified in recent years from accumulating studies.However,repositories for cataloging the detailed information on tsRNA–disease associations are scarce.In this study,we provide a tsRNADisease database by integrating experimentally and computationally supported tsRNA–disease associations from manual curation of literatures and other related resources.tsRNADisease contains 5571 manually curated associations between 4759 tsRNAs and 166 diseases with experimental evidence from 346 studies.In addition,it also contains 5013 predicted associations between 1297 tsRNAs and 111 diseases.tsRNADisease provides a user-friendly interface to browse,retrieve,and download data conveniently.This database can improve our understanding of tsRNA deregulation in diseases and serve as a valuable resource for investigating the mechanism of disease-related tsRNAs.tsRNADisease is freely available at http://www.compgenelab.info/tsRNADisease.展开更多
0 INTRODUCTION Earth science is a natural science concerned with the composition,dynamics,spatiotemporal evolution,and formation mechanisms of Earth materials(Chen and Yang,2023).Traditional Earth science research has...0 INTRODUCTION Earth science is a natural science concerned with the composition,dynamics,spatiotemporal evolution,and formation mechanisms of Earth materials(Chen and Yang,2023).Traditional Earth science research has largely been discipline-based,relying on field investigations,data collection,experimental analyses,and data interpretation to study individual components of the Earth system.展开更多
Unmanned Aerial Vehicles(UAVs)in Flying Ad-Hoc Networks(FANETs)are widely used in both civilian and military fields,but they face severe security,trust,and privacy vulnerabilities due to their high mobility,dynamic to...Unmanned Aerial Vehicles(UAVs)in Flying Ad-Hoc Networks(FANETs)are widely used in both civilian and military fields,but they face severe security,trust,and privacy vulnerabilities due to their high mobility,dynamic topology,and open wireless channels.Existing security protocols for Mobile Ad-Hoc Networks(MANETs)cannot be directly applied to FANETs,as FANETs require lightweight,high real-time performance,and strong anonymity.The current FANETs security protocol cannot simultaneously meet the requirements of strong anonymity,high security,and low overhead in high dynamic and resource-constrained scenarios.To address these challenges,this paper proposes an Anonymous Authentication and Key Exchange Protocol(AAKE-OWA)for UAVs in FANETs based on OneWay Accumulators(OWA).During the UAV registration phase,the Key Management Center(KMC)generates an identity ticket for each UAV using OWA and transmits it securely to the UAV’s on-board tamper-proof module.In the key exchange phase,UAVs generate temporary authentication tickets with random numbers and compute the same session key leveraging the quasi-commutativity of OWA.For mutual anonymous authentication,UAVs encrypt random numbers with the session key and verify identities by comparing computed values with authentication values.Formal analysis using the Scyther tool confirms that the protocol resists identity spoofing,man-in-the-middle,and replay attacks.Through Burrows Abadi Needham(BAN)logic proof,it achieves mutual anonymity,prevents simulation and physical capture attacks,and ensures secure connectivity of 1.Experimental comparisons with existing protocols prove that the AAKE-OWA protocol has lower computational overhead,communication overhead,and storage overhead,making it more suitable for resource-constrained FANET scenarios.Performance comparison experiments show that,compared with other schemes,this scheme only requires 8 one-way accumulator operations and 4 symmetric encryption/decryption operations,with a total computational overhead as low as 2.3504 ms,a communication overhead of merely 1216 bits,and a storage overhead of 768 bits.We have achieved a reduction in computational costs from 6.3%to 90.3%,communication costs from 5.0%to 69.1%,and overall storage costs from 33%to 68%compared to existing solutions.It can meet the performance requirements of lightweight,real-time,and anonymity for unmanned aerial vehicles(UAVs)networks.展开更多
Photoacoustic-computed tomography is a novel imaging technique that combines high absorption contrast and deep tissue penetration capability,enabling comprehensive three-dimensional imaging of biological targets.Howev...Photoacoustic-computed tomography is a novel imaging technique that combines high absorption contrast and deep tissue penetration capability,enabling comprehensive three-dimensional imaging of biological targets.However,the increasing demand for higher resolution and real-time imaging results in significant data volume,limiting data storage,transmission and processing efficiency of system.Therefore,there is an urgent need for an effective method to compress the raw data without compromising image quality.This paper presents a photoacoustic-computed tomography 3D data compression method and system based on Wavelet-Transformer.This method is based on the cooperative compression framework that integrates wavelet hard coding with deep learning-based soft decoding.It combines the multiscale analysis capability of wavelet transforms with the global feature modeling advantage of Transformers,achieving high-quality data compression and reconstruction.Experimental results using k-wave simulation suggest that the proposed compression system has advantages under extreme compression conditions,achieving a raw data compression ratio of up to 1:40.Furthermore,three-dimensional data compression experiment using in vivo mouse demonstrated that the maximum peak signal-to-noise ratio(PSNR)and structural similarity index(SSIM)values of reconstructed images reached 38.60 and 0.9583,effectively overcoming detail loss and artifacts introduced by raw data compression.All the results suggest that the proposed system can significantly reduce storage requirements and hardware cost,enhancing computational efficiency and image quality.These advantages support the development of photoacoustic-computed tomography toward higher efficiency,real-time performance and intelligent functionality.展开更多
Clean energy devices have the potential to change the world and avoid future energy crises.The development of new energyefficient technologies helps reduce our dependence on limited fossil fuel resources.Hydrogen ener...Clean energy devices have the potential to change the world and avoid future energy crises.The development of new energyefficient technologies helps reduce our dependence on limited fossil fuel resources.Hydrogen energy is the key to achieving clean energy transition goals.Proton exchange membrane fuel cells play a critical role.Research and development of new hightech proton exchange membranes(PEMs)provide new horizons for the development of hydrogen energy.The use of carbon nanomaterials to improve PEM efficiency is one of the modern trends.The modification of modern membranes with fullerenes and their derivatives is an innovative strategy for increasing proton conductivity.This paper discusses the key principles of proton transport in PEMs modified with individual fullerenols,sulfofullerenes,carboxylated fullerenes,phosphofullerenes,and cianohydrofullerenes.The introduction of fullerene nanoparticles into polymer PEM induces an improvement in key properties.Summary information covers existing research on the use of fullerenes as nanoscale modifiers of proton-conducting materials.This review will help researchers to surpass the achieved results in the field of modern proton-conducting materials and stimulate the development of hydrogen energy.展开更多
Covalent organic framework ionomers enable synergistic efficient transport of protons and oxygen in medium-temperature proton exchange membrane fuel cells Proton exchange membrane fuel cells(PEMFCs),as clean and effic...Covalent organic framework ionomers enable synergistic efficient transport of protons and oxygen in medium-temperature proton exchange membrane fuel cells Proton exchange membrane fuel cells(PEMFCs),as clean and efficient energy technologies,are constrained in their performance enhancement by the sluggish oxygen reduction reaction(ORR)kinetics at the cathode,anode CO poisoning(e.g.,from methanol crossover)and intricate water management dilemmas[1].展开更多
The intractable trade-off between proton conductivity and vanadium ion selectivity,known as the‘transmission paradox’is a critical bottleneck hindering the commercialization of vanadium flow batteries(VFBs).Inspired...The intractable trade-off between proton conductivity and vanadium ion selectivity,known as the‘transmission paradox’is a critical bottleneck hindering the commercialization of vanadium flow batteries(VFBs).Inspired by the multi-stage,synergistic filtration mechanism of the mammalian glomerular filtration barrier,a novel,biomimetic hierarchical composite membrane has been fabricated via a precise layer-by-layer strategy on a polyethylene(PE)substrate.This membrane integrates a polydopamine(PDA)adhesion layer,a sulfonated Zr-MOF ion-sieving layer,and a synergistic polybenzimidazole(PBI)matrix.Spectroscopic analysis confirmed the formation of a critical bifunctional acid-base interface(-SO_(3)^(−)…H^(+)N-)between the MOF and PBI,which densifies the structure and optimizes ion pathways.The resulting composite membrane exhibits excellent mechanical robustness,superior chemical stability,and exceptional dimensional stability.Most significantly,this architecture successfully decouples the performance trade-off,demonstrating both high proton conductivity(11.11 mS·cm^(-1))and remarkably suppressed vanadium ion permeability(2.4×10^(−8) cm^(2)·min^(-1)).This combination yields an outstanding ion selectivity of 46.29×10^(4) S·min·cm^(-3).When tested in a VFB single cell,the membrane enabled a high energy efficiency of 81.6%at 200 mA·cm^(-2),an ultra-long self-discharge time of 2700 min,and excellent long-term cycling stability.This biomimetic design strategy effectively resolves the core‘transmission paradox’offering a promising pathway for next-generation high-performance flow batteries.展开更多
Anion exchange membranes(AEMs)are pivotal for advancing fuel cells and water electrolysis.However,their widespread adoption is hindered by the sluggish ion transport and inadequate durability.Herein,by tuning the numb...Anion exchange membranes(AEMs)are pivotal for advancing fuel cells and water electrolysis.However,their widespread adoption is hindered by the sluggish ion transport and inadequate durability.Herein,by tuning the number of conjugated aromatic rings and the branching sites within the monomers,a series of hyperbranched poly(aryl piperidinium)AEMs with coplanar polycyclic aromatic units are prepared to address the poor mechanical properties of rigid conjugated AEMs.The results indicate that the introduction of planar-conjugated triphenylene(TY)units in the polymer backbone facilitates ordered interchain aggregation driven byπ-πstacking interaction to form well-defined ion-conductive channels while suppressing excessive swelling and enhancing the membrane stability.The hyperbranched AEM containing the TY units(QTPTY)possesses excellent mechanical properties with 55.9 MPa of stress and 60.3%of strain.Additionally,the QTPTY membrane achieves an exceptional OH-conductivity of 146.4 m S cm^(-1)at 80℃,with 94.7%conductivity retention and mechanical properties reduction below 2%after 1600 h in 2 M Na OH.In an H_(2)/O_(2) fuel cell,QTPTY delivers a peak power density of 1.43 W cm^(-2),surpassing linear and the other twoπ-conjugated hyperbranched analogs.In water electrolysis,the AEM exhibits a current density of 2.30 A cm^(-2)at 1.80 V,exceeding the 2026 targets of the U.S.Department of Energy.This work demonstrates that planar-conjugated hyperbranched architectures have a significant potential in designing robust,high-performance AEMs for sustainable energy technologies.展开更多
基金supported by the National Natural Science Foundation of China[grant numbers 12171158,12371474 and 12571510]Fundamental Research Funds for the Central Universities[grant number 2025ECNU-WLJC006].
文摘This work contributes to the theoretical foundation for pricing in data markets and offers practical insights for managing digital data exchanges in the era of big data.We propose a structured pricing model for data exchanges transitioning from quasi-public to marketoriented operations.To address the complex dynamics among data exchanges,suppliers,and consumers,the authors develop a threestage Stackelberg game framework.In this model,the data exchange acts as a leader setting transaction commission rates,suppliers are intermediate leaders determining unit prices,and consumers are followers making purchasing decisions.Two pricing strategies are examined:the Independent Pricing Approach(IPA)and the novel Perfectly Competitive Pricing Approach(PCPA),which accounts for competition among data providers.Using backward induction,the study derives subgame-perfect equilibria and proves the existence and uniqueness of Stackelberg equilibria under both approaches.Extensive numerical simulations are carried out in the model,demonstrating that PCPA enhances data demander utility,encourages supplier competition,increases transaction volume,and improves the overall profitability and sustainability of data exchanges.Social welfare analysis further confirms PCPA’s superiority in promoting efficient and fair data markets.
基金fully supported by the University of Vaasa and VTT Technical Research Centre of Finland.
文摘Secure and automated sharing of medical information among different medical entities/stakeholders like patients,hospitals,doctors,law enforcement agencies,health insurance companies etc.,in a standard format has always been a challenging problem.Current methods for ensuring compliance with medical privacy laws require specialists who are deeply familiar with these laws'complex requirements to verify the lawful exchange of medical information.This article introduces a Smart Medical Data Exchange Engine(SDEE)designed to automate the extracting of logical rules from medical privacy legislation using advanced techniques.These rules facilitate the secure extraction of information,safeguarding patient privacy and confidentiality.In addition,SMDEE can generate standardised clinical documents according to Health Level 7(HL7)standards and also standardise the nomenclature of requested medical data,enabling accurate decision-making when accessing patient data.All access requests to patient information are processed through SMDEE to ensure authorised access.The proposed system's efficacy is evaluated using the Health Insurance Portability and Accountability Act(HIPAA),a fundamental privacy law in the United States.However,SMDEE's flexibility allows its application worldwide,accommodating various medical privacy laws.Beyond facilitating global information exchange,SMDEE aims to enhance international patients'timely and appropriate treatment.
文摘This paper employs Granger causality analysis and the generalized impulse response function(GIRF)to study the higher-order moment spillover effects among Bitcoin,stock markets,and foreign exchange markets in the U.S.Using intraday high-frequency data,the research focuses on the interactions across higher-order moments,including volatility,jumps,skewness,and kurtosis.The results reveal significant bidirectional spillover effects between Bitcoin and traditional financial assets,particularly in terms of volatility and jump behavior,indicating that the cryptocurrency market has become a crucial component of global financial risk transmission.This study provides new theoretical perspectives and policy recommendations for global asset allocation,market regulation,and risk management,underscoring the importance of proactive management measures in addressing the complex risk interactions between cryptocurrencies and traditional financial markets.
文摘The ionothermal reaction between CuCl_(2),1,4-bis(1,2,4-triazol-1-ylmethyl)benzene(BBTZ),and(NH_(4))_(6)Mo_(7)O_(24) in 1-ethyl-3-methylimidazolium bromide((Emim)Br)led to a new octamolybdate-based coordination polymer(Emim)2[Cu(BBTZ)_(2)(β-Mo_(8)O_(26))](Mo_(8)-CP).Mo_(8)-CP was characterized by elemental analysis,thermogravime-try,IR,powder X-ray diffraction,and single-crystal X-ray diffraction.In Mo_(8)-CP,structural analysis reveals that Cu coordinates with BBTZ ligands to form an interlocked 1D chain.These chains are further bridged by(β-Mo_(8)O_(26))^(4-)to construct a 3D coordination polymer.Notably,(Emim)^(+)acts as a structure-directing agent,occupying the channels of the 3D coordination polymer.Based on this unique structure,the ion exchange properties of Mo_(8)-CP toward rare-earth ions were investigated.It has been found that the luminescent color of the material can be successfully regulat-ed by introducing Eu^(3+)or Tb^(3+)through ion exchange.CCDC:2475110,Mo_(8)-CP.
文摘Earthquakes are highly destructive spatio-temporal phenomena whose analysis is essential for disaster preparedness and risk mitigation.Modern seismological research produces vast volumes of heterogeneous data from seismic networks,satellite observations,and geospatial repositories,creating the need for scalable infrastructures capable of integrating and analyzing such data to support intelligent decision-making.Data warehousing technologies provide a robust foundation for this purpose;however,existing earthquake-oriented data warehouses remain limited,often relying on simplified schemas,domain-specific analytics,or cataloguing efforts.This paper presents the design and implementation of a spatio-temporal data warehouse for seismic activity.The framework integrates spatial and temporal dimensions in a unified schema and introduces a novel array-based approach for managing many-to-many relationships between facts and dimensions without intermediate bridge tables.A comparative evaluation against a conventional bridge-table schema demonstrates that the array-based design improves fact-centric query performance,while the bridge-table schema remains advantageous for dimension-centric queries.To reconcile these trade-offs,a hybrid schema is proposed that retains both representations,ensuring balanced efficiency across heterogeneous workloads.The proposed framework demonstrates how spatio-temporal data warehousing can address schema complexity,improve query performance,and support multidimensional visualization.In doing so,it provides a foundation for integrating seismic analysis into broader big data-driven intelligent decision systems for disaster resilience,risk mitigation,and emergency management.
基金supported by grants from the Natural Science Foundation of China(22362031 and 21805121)the Science and Technology Project of Yunnan Province(2019FD137)。
文摘Proton exchange membrane fuel cells(PEMFCs)are considered as a promising renewable power source.However,the massive commercial application of PEMFCs has been greatly hindered by their high expense and less-satisfied performance mainly due to the sluggish oxygen reduction reaction(ORR)kinetics even on state-of-the-art Pt catalyst.Octahedral PtNi nanoparticles(oct-PtNi NPs)with excellent ORR activity in a half-cell have been widely studied,while their performance in membrane electrode assembly(MEA)has much less reported.Herein,we investigated the MEA performance using the carbon supported oct-PtNi NPs(oct-PtNi/C)as the cathode catalyst.Under the mild acid washing condition,the surface Ni atoms of oct-PtNi/C were largely removed,and the performance of the MEA using the acid-leaching oct-PtNi/C(PNC-A)as the cathode catalyst was greatly improved.The maximum power density of the MEA reached 1.0 W·cm^(-2) with the cath-ode Pt loading of 0.2 mg·cm^(-2),which is 15%higher than that using Pt/C as the catalyst.After 30k cycles in the accelerated degradation test(ADT),the MEA using PNC-A as the catalyst showed a performance retention of 82%,higher than that of Pt/C(74%).The results reported here verify the possibility of using PNC-A as an advanced cathode catalyst in PEMFCs,thus enhancing the performance of PEMFCs while lowering the amount of expensive Pt.
文摘A Tibetan art form bridges the past and present and connects cultures around the world.THANGKA,a unique form of Tibetan sacred painting,is gaining prominence globally due to its vibrant colors,exquisite craftsmanship,and profound religious and cultural significance.With the acceleration of globalization,this symbol of Tibetan culture that combines artistic expression with spirituality has become a bridge for cultural exchange between the East and the West.Recently,China Today spoke to Yixi Puncog,art collector and council member of the China Association for Preservation and Development of Tibetan Culture,to learn more about Thangka art,its role in international exchange,and how it is enhancing China’s cultural soft power.
文摘Ningxia is an ethnic gathering area boasting abundant tourism and cultural resources.Developing the cause of tourism and culture is an important way to encourage all ethnic groups to respect differences,embrace diversity,and demonstrate their interactions,exchanges,and integration in tourism activities.As an important preserve of the distinctive cultures of the Chinese nation and a prominent world tourist destination,Ningxia should strive to foster and consolidate the sense of a community with a shared future for the Chinese nation in developing its tourism and culture under the new historical conditions.It is imperative to advance the prosperity and development of tourism and culture in boosting ethnic interactions,exchanges,and integration through the formulation of tourism and cultural policies and plans,as well as the development and design of tourism and cultural projects.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)under the grant number IMSIU-DDRSP2601.
文摘Ovarian cancer(OC)is one of the leading causes of death related to gynecological cancer,with the main difficulty of its early diagnosis and a heterogeneous nature of tumor biomarkers.Machine learning(ML)has the potential to process complex datasets and support decision-making in OC diagnosis.Nevertheless,traditional ML models tend to be biased,overfitting,noisy,and less generalized.Moreover,their black-box nature reduces interpretability and limits their practical clinical applicability.In this study,we introduce an explainable ensemble learning(EL)model,TreeX-Stack,based on a stacking architecture that employs tree-based learners such as Decision Tree(DT),Random Forest(RF),Gradient Boosting(GB),and Extreme Gradient Boosting(XGBoost)as base learners,and Logistic Regression(LR)as the meta-learner to enhance ovarian cancer(OC)diagnosis.Local Interpretable ModelAgnostic Explanations(LIME)are used to explain individual predictions,making the model outputs more clinically interpretable and applicable.The model is trained on the dataset that includes demographic information,blood test,general chemistry,and tumor markers.Extensive preprocessing includes handling missing data using iterative imputation with Bayesian Ridge and addressing multicollinearity by removing features with correlation coefficients above 0.7.Relevant features are then selected using the Boruta feature selection method.To obtain robust and unbiased performance estimates during hyperparameter tuning,nested cross-validation(CV)with grid search is employed,and all experiments are repeated five times to ensure statistical reliability.TreeX-Stack demonstrates excellent diagnostic performance,achieving an accuracy of 0.9027,a precision of 0.8673,a recall of 0.9391,and an F1-score of 0.9012.Feature-importance analyses using LIME and permutation importance highlight Human Epididymis Protein 4(HE4)as the most significant biomarker for OC.The combination of high predictive performance and interpretability makes TreeX-Stack a reliable tool for clinical decision support in OC diagnosis.
基金supported by the International Partnership program of the Chinese Academy of Sciences(170GJHZ2023074GC)National Natural Science Foundation of China(42425706 and 42488201)+1 种基金National Key Research and Development Program of China(2024YFF0807902)Beijing Natural Science Foundation(8242041),and China Postdoctoral Science Foundation(2025M770353).
文摘Accurately assessing the relationship between tree growth and climatic factors is of great importance in dendrochronology.This study evaluated the consistency between alternative climate datasets(including station and gridded data)and actual climate data(fixed-point observations near the sampling sites),in northeastern China’s warm temperate zone and analyzed differences in their correlations with tree-ring width index.The results were:(1)Gridded temperature data,as well as precipitation and relative humidity data from the Huailai meteorological station,was more consistent with the actual climate data;in contrast,gridded soil moisture content data showed significant discrepancies.(2)Horizontal distance had a greater impact on the representativeness of actual climate conditions than vertical elevation differences.(3)Differences in consistency between alternative and actual climate data also affected their correlations with tree-ring width indices.In some growing season months,correlation coefficients,both in magnitude and sign,differed significantly from those based on actual data.The selection of different alternative climate datasets can lead to biased results in assessing forest responses to climate change,which is detrimental to the management of forest ecosystems in harsh environments.Therefore,the scientific and rational selection of alternative climate data is essential for dendroecological and climatological research.
文摘To address the severe challenges of PM_(2.5) and ozone co-control during the"14^(th) Five-Year Plan"period and to enhance the precision and intelligence level of air environment governance,it is imperative to build an efficient comprehensive management platform for regional air quality.In this paper,the specific practice in Zibo City,Shandong Province is as an example to systematically analyze the top-level design,technical implementation,and innovative application of a comprehensive management platform for regional air quality integrating"perception monitoring,data fusion,research judgment of early warnings,analysis of sources,collaborative dispatching,and evaluation assessment".Through the construction of an"sky-air-ground"integrated three-dimensional monitoring network,the platform integrates multi-source heterogeneous environmental data,and employs big data,cloud computing,artificial intelligence,CALPUFF/CMAQ,and other numerical model technologies to achieve comprehensive perception,precise prediction,intelligent source tracing,and closed-loop management of air pollution.The platform innovatively establishes a full-process closed-loop management mechanism of"data-early warning-disposition-evaluation",and achieves a fundamental transformation from passive response to active anticipation and from experience-based judgment to data driving in environmental supervision.The application results show that this platform significantly improves the scientific decision-making ability and collaborative execution efficiency of air pollution governance in Zibo City,providing a replicable and scalable comprehensive solution for similar industrial cities to achieve the continuous improvement of air quality.
基金Funded in part by the National Key Research and Development Program of China(No.2023YFB4006302)。
文摘We successfully incorporated phenyl groups into a small-molecule quaternary ammonium cross-linker and synthesized cross-linked polybenzimidazole membranes via a one-step cross-linking process.Compared with conventional quaternary ammonium-crosslinked benzimidazole membranes,the introduction of phenyl groups significantly increases the free volume within the membrane.After phosphoric acid doping,the benzimidazole membrane with larger free volume retains more phosphoric acid compared to conventional quaternary ammonium-crosslinked membranes,forming an extensive hydrogen-bonding network that effectively enhances its anhydrous proton conductivity.The anhydrous proton conductivity reaches 91 mS·cm^(-1)at 160℃,substantially higher than that of conventional quaternary ammonium-crosslinked membranes with the same mass fraction.Benefiting from the improved conductivity,the membrane electrode assembly exhibits reduced ohmic polarization,achieving a peak power density of 792 mW·cm^(-2)at 160℃.
基金supported by the National Natural Science Foundation of China(91959106)the Foundation of the Shanghai Municipal Education Commission(24RGZNC02)+4 种基金Shanghai Key Laboratory of Intelligent Information Processing,Fudan University(IIPL-2025-RD3-02)Key University Science Research Project of Anhui Province(2023AH030108)Climbing Peak Training Program for Innovative Technology team of Yijishan Hospital,Wannan Medical College(PF201904)Peak Training Program for Scientific Research of Yijishan Hospital,Wannan Medical College(GF2019G15)the talent project of the First Affiliated Hospital of Wannan Medical College(Yijishan Hospital of Wannan Medical College)(YR202422).
文摘tRNA-derived small RNAs(tsRNAs),as a class of regulatory small noncoding RNA,have been implicated in a wide variety of human diseases.Large amounts of tsRNA–disease associations have been identified in recent years from accumulating studies.However,repositories for cataloging the detailed information on tsRNA–disease associations are scarce.In this study,we provide a tsRNADisease database by integrating experimentally and computationally supported tsRNA–disease associations from manual curation of literatures and other related resources.tsRNADisease contains 5571 manually curated associations between 4759 tsRNAs and 166 diseases with experimental evidence from 346 studies.In addition,it also contains 5013 predicted associations between 1297 tsRNAs and 111 diseases.tsRNADisease provides a user-friendly interface to browse,retrieve,and download data conveniently.This database can improve our understanding of tsRNA deregulation in diseases and serve as a valuable resource for investigating the mechanism of disease-related tsRNAs.tsRNADisease is freely available at http://www.compgenelab.info/tsRNADisease.
基金supported by National Key R&D Program of China(No.2021YFF0501301)the National Natural Science Foundation of China(No.42172231)。
文摘0 INTRODUCTION Earth science is a natural science concerned with the composition,dynamics,spatiotemporal evolution,and formation mechanisms of Earth materials(Chen and Yang,2023).Traditional Earth science research has largely been discipline-based,relying on field investigations,data collection,experimental analyses,and data interpretation to study individual components of the Earth system.
基金supported in part by National Natural Science Foundation of China(under Grant 61902163)the Jiangsu“Qing Lan Project”,Natural Science Foundation of the Jiangsu Higher Education Institutions of China(Major Research Project:23KJA520007)Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.SJCX25_1303).
文摘Unmanned Aerial Vehicles(UAVs)in Flying Ad-Hoc Networks(FANETs)are widely used in both civilian and military fields,but they face severe security,trust,and privacy vulnerabilities due to their high mobility,dynamic topology,and open wireless channels.Existing security protocols for Mobile Ad-Hoc Networks(MANETs)cannot be directly applied to FANETs,as FANETs require lightweight,high real-time performance,and strong anonymity.The current FANETs security protocol cannot simultaneously meet the requirements of strong anonymity,high security,and low overhead in high dynamic and resource-constrained scenarios.To address these challenges,this paper proposes an Anonymous Authentication and Key Exchange Protocol(AAKE-OWA)for UAVs in FANETs based on OneWay Accumulators(OWA).During the UAV registration phase,the Key Management Center(KMC)generates an identity ticket for each UAV using OWA and transmits it securely to the UAV’s on-board tamper-proof module.In the key exchange phase,UAVs generate temporary authentication tickets with random numbers and compute the same session key leveraging the quasi-commutativity of OWA.For mutual anonymous authentication,UAVs encrypt random numbers with the session key and verify identities by comparing computed values with authentication values.Formal analysis using the Scyther tool confirms that the protocol resists identity spoofing,man-in-the-middle,and replay attacks.Through Burrows Abadi Needham(BAN)logic proof,it achieves mutual anonymity,prevents simulation and physical capture attacks,and ensures secure connectivity of 1.Experimental comparisons with existing protocols prove that the AAKE-OWA protocol has lower computational overhead,communication overhead,and storage overhead,making it more suitable for resource-constrained FANET scenarios.Performance comparison experiments show that,compared with other schemes,this scheme only requires 8 one-way accumulator operations and 4 symmetric encryption/decryption operations,with a total computational overhead as low as 2.3504 ms,a communication overhead of merely 1216 bits,and a storage overhead of 768 bits.We have achieved a reduction in computational costs from 6.3%to 90.3%,communication costs from 5.0%to 69.1%,and overall storage costs from 33%to 68%compared to existing solutions.It can meet the performance requirements of lightweight,real-time,and anonymity for unmanned aerial vehicles(UAVs)networks.
基金supported by the National Key R&D Program of China[Grant No.2023YFF0713600]the National Natural Science Foundation of China[Grant No.62275062]+3 种基金Project of Shandong Innovation and Startup Community of High-end Medical Apparatus and Instruments[Grant No.2023-SGTTXM-002 and 2024-SGTTXM-005]the Shandong Province Technology Innovation Guidance Plan(Central Leading Local Science and Technology Development Fund)[Grant No.YDZX2023115]the Taishan Scholar Special Funding Project of Shandong Provincethe Shandong Laboratory of Advanced Biomaterials and Medical Devices in Weihai[Grant No.ZL202402].
文摘Photoacoustic-computed tomography is a novel imaging technique that combines high absorption contrast and deep tissue penetration capability,enabling comprehensive three-dimensional imaging of biological targets.However,the increasing demand for higher resolution and real-time imaging results in significant data volume,limiting data storage,transmission and processing efficiency of system.Therefore,there is an urgent need for an effective method to compress the raw data without compromising image quality.This paper presents a photoacoustic-computed tomography 3D data compression method and system based on Wavelet-Transformer.This method is based on the cooperative compression framework that integrates wavelet hard coding with deep learning-based soft decoding.It combines the multiscale analysis capability of wavelet transforms with the global feature modeling advantage of Transformers,achieving high-quality data compression and reconstruction.Experimental results using k-wave simulation suggest that the proposed compression system has advantages under extreme compression conditions,achieving a raw data compression ratio of up to 1:40.Furthermore,three-dimensional data compression experiment using in vivo mouse demonstrated that the maximum peak signal-to-noise ratio(PSNR)and structural similarity index(SSIM)values of reconstructed images reached 38.60 and 0.9583,effectively overcoming detail loss and artifacts introduced by raw data compression.All the results suggest that the proposed system can significantly reduce storage requirements and hardware cost,enhancing computational efficiency and image quality.These advantages support the development of photoacoustic-computed tomography toward higher efficiency,real-time performance and intelligent functionality.
基金supported by the Russian Science Foundation Project(23-13-00328)。
文摘Clean energy devices have the potential to change the world and avoid future energy crises.The development of new energyefficient technologies helps reduce our dependence on limited fossil fuel resources.Hydrogen energy is the key to achieving clean energy transition goals.Proton exchange membrane fuel cells play a critical role.Research and development of new hightech proton exchange membranes(PEMs)provide new horizons for the development of hydrogen energy.The use of carbon nanomaterials to improve PEM efficiency is one of the modern trends.The modification of modern membranes with fullerenes and their derivatives is an innovative strategy for increasing proton conductivity.This paper discusses the key principles of proton transport in PEMs modified with individual fullerenols,sulfofullerenes,carboxylated fullerenes,phosphofullerenes,and cianohydrofullerenes.The introduction of fullerene nanoparticles into polymer PEM induces an improvement in key properties.Summary information covers existing research on the use of fullerenes as nanoscale modifiers of proton-conducting materials.This review will help researchers to surpass the achieved results in the field of modern proton-conducting materials and stimulate the development of hydrogen energy.
文摘Covalent organic framework ionomers enable synergistic efficient transport of protons and oxygen in medium-temperature proton exchange membrane fuel cells Proton exchange membrane fuel cells(PEMFCs),as clean and efficient energy technologies,are constrained in their performance enhancement by the sluggish oxygen reduction reaction(ORR)kinetics at the cathode,anode CO poisoning(e.g.,from methanol crossover)and intricate water management dilemmas[1].
基金supported by the Natural Science Foundation of Liaoning Province(Grant Nos:2025-BSLH-247,2025-BSLH-246)Liaoning Provincial Department of Education Foundation(Grant Nos:LJ212410148012,LJ242510148002)+1 种基金Inner Mongolia’s Key R&D and Achievement Industrialization Program(Grant No:2025YFHH0017)China Postdoctoral Science Foundation(Grant Nos:2025MD774148,2025M770082).
文摘The intractable trade-off between proton conductivity and vanadium ion selectivity,known as the‘transmission paradox’is a critical bottleneck hindering the commercialization of vanadium flow batteries(VFBs).Inspired by the multi-stage,synergistic filtration mechanism of the mammalian glomerular filtration barrier,a novel,biomimetic hierarchical composite membrane has been fabricated via a precise layer-by-layer strategy on a polyethylene(PE)substrate.This membrane integrates a polydopamine(PDA)adhesion layer,a sulfonated Zr-MOF ion-sieving layer,and a synergistic polybenzimidazole(PBI)matrix.Spectroscopic analysis confirmed the formation of a critical bifunctional acid-base interface(-SO_(3)^(−)…H^(+)N-)between the MOF and PBI,which densifies the structure and optimizes ion pathways.The resulting composite membrane exhibits excellent mechanical robustness,superior chemical stability,and exceptional dimensional stability.Most significantly,this architecture successfully decouples the performance trade-off,demonstrating both high proton conductivity(11.11 mS·cm^(-1))and remarkably suppressed vanadium ion permeability(2.4×10^(−8) cm^(2)·min^(-1)).This combination yields an outstanding ion selectivity of 46.29×10^(4) S·min·cm^(-3).When tested in a VFB single cell,the membrane enabled a high energy efficiency of 81.6%at 200 mA·cm^(-2),an ultra-long self-discharge time of 2700 min,and excellent long-term cycling stability.This biomimetic design strategy effectively resolves the core‘transmission paradox’offering a promising pathway for next-generation high-performance flow batteries.
基金the financial support from the National Natural Science Foundation of China(Grant Nos.22278340&22078272)。
文摘Anion exchange membranes(AEMs)are pivotal for advancing fuel cells and water electrolysis.However,their widespread adoption is hindered by the sluggish ion transport and inadequate durability.Herein,by tuning the number of conjugated aromatic rings and the branching sites within the monomers,a series of hyperbranched poly(aryl piperidinium)AEMs with coplanar polycyclic aromatic units are prepared to address the poor mechanical properties of rigid conjugated AEMs.The results indicate that the introduction of planar-conjugated triphenylene(TY)units in the polymer backbone facilitates ordered interchain aggregation driven byπ-πstacking interaction to form well-defined ion-conductive channels while suppressing excessive swelling and enhancing the membrane stability.The hyperbranched AEM containing the TY units(QTPTY)possesses excellent mechanical properties with 55.9 MPa of stress and 60.3%of strain.Additionally,the QTPTY membrane achieves an exceptional OH-conductivity of 146.4 m S cm^(-1)at 80℃,with 94.7%conductivity retention and mechanical properties reduction below 2%after 1600 h in 2 M Na OH.In an H_(2)/O_(2) fuel cell,QTPTY delivers a peak power density of 1.43 W cm^(-2),surpassing linear and the other twoπ-conjugated hyperbranched analogs.In water electrolysis,the AEM exhibits a current density of 2.30 A cm^(-2)at 1.80 V,exceeding the 2026 targets of the U.S.Department of Energy.This work demonstrates that planar-conjugated hyperbranched architectures have a significant potential in designing robust,high-performance AEMs for sustainable energy technologies.
