This paper takes Zoomlion （Changsha Zoomlion Heavy Industry Science and Technology Development Co., Ltd） as an example and illustrates the reasons why traditional theories of stock dividends and stock splits cannot ...This paper takes Zoomlion （Changsha Zoomlion Heavy Industry Science and Technology Development Co., Ltd） as an example and illustrates the reasons why traditional theories of stock dividends and stock splits cannot rationally explain the large stock dividend and stock split behavior among Chinese listed companies. The paper offers the following points after analyzing the current situation of China＇s capital market： As many investors seek after the stocks with large stock dividends and stock splits and form a ＂herd effect＂, it greatly pushes up the price of these stocks. Thus, companies＇ managers can cater these investors＇ irrational behavior, and help their companies get more funds from secondary equity offerings, or help their large shareholders and institutional investors to obtain more returns after lifting the sell restriction on their shares.展开更多
Electrochemical water splitting represents a sustainable technology for hydrogen(H_(2))production.However,its large-scale implementation is hindered by the high overpotentials required for both the cathodic hydrogen e...Electrochemical water splitting represents a sustainable technology for hydrogen(H_(2))production.However,its large-scale implementation is hindered by the high overpotentials required for both the cathodic hydrogen evolution reaction(HER)and the anodic oxygen evolution reaction(OER).Transition metal-based catalysts have garnered significant research interest as promising alternatives to noble-metal catalysts,owing to their low cost,tunable composition,and noble-metal-like catalytic activity.Nevertheless,systematic reviews on their application as bifunctional catalysts for overall water splitting(OWS)are still limited.This review comprehensively outlines the principal categories of bifunctional transition metal electrocatalysts derived from electrospun nanofibers(NFs),including metals,oxides,phosphides,sulfides,and carbides.Key strategies for enhancing their catalytic performance are systematically summarized,such as heterointerface engineering,heteroatom doping,metal-nonmetal-metal bridging architectures,and single-atom site design.Finally,current challenges and future research directions are discussed,aiming to provide insightful perspectives for the rational design of high-performance electrocatalysts for OWS.展开更多
Split Learning(SL)has been promoted as a promising collaborative machine learning technique designed to address data privacy and resource efficiency.Specifically,neural networks are divided into client and server subn...Split Learning(SL)has been promoted as a promising collaborative machine learning technique designed to address data privacy and resource efficiency.Specifically,neural networks are divided into client and server subnetworks in order to mitigate the exposure of sensitive data and reduce the overhead on client devices,thereby making SL particularly suitable for resource-constrained devices.Although SL prevents the direct transmission of raw data,it does not alleviate entirely the risk of privacy breaches.In fact,the data intermediately transmitted to the server sub-model may include patterns or information that could reveal sensitive data.Moreover,achieving a balance between model utility and data privacy has emerged as a challenging problem.In this article,we propose a novel defense approach that combines:(i)Adversarial learning,and(ii)Network channel pruning.In particular,the proposed adversarial learning approach is specifically designed to reduce the risk of private data exposure while maintaining high performance for the utility task.On the other hand,the suggested channel pruning enables the model to adaptively adjust and reactivate pruned channels while conducting adversarial training.The integration of these two techniques reduces the informativeness of the intermediate data transmitted by the client sub-model,thereby enhancing its robustness against attribute inference attacks without adding significant computational overhead,making it wellsuited for IoT devices,mobile platforms,and Internet of Vehicles(IoV)scenarios.The proposed defense approach was evaluated using EfficientNet-B0,a widely adopted compact model,along with three benchmark datasets.The obtained results showcased its superior defense capability against attribute inference attacks compared to existing state-of-the-art methods.This research’s findings demonstrated the effectiveness of the proposed channel pruning-based adversarial training approach in achieving the intended compromise between utility and privacy within SL frameworks.In fact,the classification accuracy attained by the attackers witnessed a drastic decrease of 70%.展开更多
Herein,we have developed a straightforward wet-chemical method to synthesize a series of Pd-based alloy nanowires(NWs),including Pd Pt NWs,Pd Au NWs,Pd Ir NWs,and Pd Ru NWs,which exhibits high mass activity and turnov...Herein,we have developed a straightforward wet-chemical method to synthesize a series of Pd-based alloy nanowires(NWs),including Pd Pt NWs,Pd Au NWs,Pd Ir NWs,and Pd Ru NWs,which exhibits high mass activity and turnover frequency(TOF) for HER,surpassing Pt/C by 4.6-fold and 1.5-fold in acidic and alkaline electrolytes,respectively.It also demonstrates high stability in alkaline electrolyte at a current density of 220 m A/cm^(2) for 280 h,highlighting its potential for practical applications under industrial current conditions.Pd Pt NWs exhibited ultrathin structures with head-to-tail kinks and inherent defects,significantly increasing the density of active sites and precisely tuning the electronic structure,which could accelerate reaction kinetics and boost water-splitting electrocatalytic performance.This study highlights the potential of Pd Pt NWs as highly efficient catalysts,offering outstanding catalytic performance and stability for practical applications.展开更多
The fast solution of linear equations has always been one of the hot spots in scientific computing.A kind of the diagonal matrix splitting iteration methods are provided,which is different from the classical matrix sp...The fast solution of linear equations has always been one of the hot spots in scientific computing.A kind of the diagonal matrix splitting iteration methods are provided,which is different from the classical matrix splitting methods.Taking the decomposition of the diagonal elements for coefficient matrix as the key point,some new preconditioners are constructed.Taking the tri-diagonal coefficient matrix as an example,the convergence domains and optimal relaxation factor of the new method are analyzed theoretically.The presented new iteration methods are applied to solve linear algebraic equations,even 2D and 3D diffusion problems with the fully implicit discretization.The results of numerical experiments are matched with the theoretical analysis,and show that the iteration numbers are reduced greatly.The superiorities of presented iteration methods exceed some classical iteration methods dramatically.展开更多
The Internet of Vehicles,or IoV,is expected to lessen pollution,ease traffic,and increase road safety.IoV entities’interconnectedness,however,raises the possibility of cyberattacks,which can have detrimental effects....The Internet of Vehicles,or IoV,is expected to lessen pollution,ease traffic,and increase road safety.IoV entities’interconnectedness,however,raises the possibility of cyberattacks,which can have detrimental effects.IoV systems typically send massive volumes of raw data to central servers,which may raise privacy issues.Additionally,model training on IoV devices with limited resources normally leads to slower training times and reduced service quality.We discuss a privacy-preserving Federated Split Learning with Tiny Machine Learning(TinyML)approach,which operates on IoV edge devices without sharing sensitive raw data.Specifically,we focus on integrating split learning(SL)with federated learning(FL)and TinyML models.FL is a decentralisedmachine learning(ML)technique that enables numerous edge devices to train a standard model while retaining data locally collectively.The article intends to thoroughly discuss the architecture and challenges associated with the increasing prevalence of SL in the IoV domain,coupled with FL and TinyML.The approach starts with the IoV learning framework,which includes edge computing,FL,SL,and TinyML,and then proceeds to discuss how these technologies might be integrated.We elucidate the comprehensive operational principles of Federated and split learning by examining and addressingmany challenges.We subsequently examine the integration of SL with FL and various applications of TinyML.Finally,exploring the potential integration of FL and SL with TinyML in the IoV domain is referred to as FSL-TM.It is a superior method for preserving privacy as it conducts model training on individual devices or edge nodes,thereby obviating the necessity for centralised data aggregation,which presents considerable privacy threats.The insights provided aim to help both researchers and practitioners understand the complicated terrain of FL and SL,hence facilitating advancement in this swiftly progressing domain.展开更多
Drilling and blasting tunneling is a cyclic process in which tunnel rock undergoes repeated blast loading,affecting its dynamic characteristics,energy evolution,and damage progression.To explore the dynamic mechanical...Drilling and blasting tunneling is a cyclic process in which tunnel rock undergoes repeated blast loading,affecting its dynamic characteristics,energy evolution,and damage progression.To explore the dynamic mechanical properties and damage mechanisms of carbonaceous slate under cyclic impact loads of varying intensities,cyclic dynamic tests are conducted using a triaxial split Hopkinson pressure bar.This study analyzes the stress-strain relationship,energy damage evolution,and macro-to-micro failure characteristics.The results show that peak stress and strain are significantly influenced by impact intensity and the number of impacts.The initial dynamic stress is positively correlated with the impact intensity,but with more impact,the dynamic stress decreases while the peak strain increases.Energy evolution follows a pattern of"slow growthfluctuating growthrapid growth,"with the crack initiation stress and its proportion decreasing.CT and SEM analyses reveal that as the impact intensity increases,failure becomes more chaotic,the fracture volume increases,and the fracture mode shifts from interlayer and intergranular to through-layer and trans-granular fractures.These findings provide an experimental basis for soft rock tunnel stability analysis.展开更多
High‐entropy amorphous catalysts(HEACs)integrate multielement synergy with structural disorder,making them promising candidates for water splitting.Their distinctive features—including flexible coordination environm...High‐entropy amorphous catalysts(HEACs)integrate multielement synergy with structural disorder,making them promising candidates for water splitting.Their distinctive features—including flexible coordination environments,tunable electronic structures,abundant unsaturated active sites,and dynamic structural reassembly—collectively enhance electrochemical activity and durability under operating conditions.This review summarizes recent advances in HEACs for hydrogen evolution,oxygen evolution,and overall water splitting,highlighting their disorder-driven advantages over crystalline counterparts.Catalytic performance benchmarks are presented,and mechanistic insights are discussed,focusing on how multimetallic synergy,amorphization effect,and in‐situ reconstruction cooperatively regulate reaction pathways.These insights provide guidance for the rational design of next‐generation amorphous high‐entropy electrocatalysts with improved efficiency and durability.展开更多
The personalized fine-tuning of large languagemodels(LLMs)on edge devices is severely constrained by limited computation resources.Although split federated learning alleviates on-device burdens,its effectiveness dimin...The personalized fine-tuning of large languagemodels(LLMs)on edge devices is severely constrained by limited computation resources.Although split federated learning alleviates on-device burdens,its effectiveness diminishes in few-shot reasoning scenarios due to the low data efficiency of conventional supervised fine-tuning,which leads to excessive communication overhead.To address this,we propose Language-Empowered Split Fine-Tuning(LESFT),a framework that integrates split architectures with a contrastive-inspired fine-tuning paradigm.LESFT simultaneously learns frommultiple logically equivalent but linguistically diverse reasoning chains,providing richer supervisory signals and improving data efficiency.This process-oriented training allows more effective reasoning adaptation with fewer samples.Extensive experiments demonstrate that LESFT consistently outperforms strong baselines such as SplitLoRA in task accuracy.LESFT consistently outperforms strong baselines on GSM8K,CommonsenseQA,and AQUA_RAT,with the largest gains observed on Qwen2.5-3B.These results indicate that LESFT can effectively adapt large language models for reasoning tasks under the computational and communication constraints of edge environments.展开更多
Highly active and stable FeOOH cocatalysts are essential for achieving optimal performance of BiVO_(4)(BVO)photoanodes.Despite offering remarkable structural stability,widely used thick FeOOH cocatalysts often suffer ...Highly active and stable FeOOH cocatalysts are essential for achieving optimal performance of BiVO_(4)(BVO)photoanodes.Despite offering remarkable structural stability,widely used thick FeOOH cocatalysts often suffer from insufficient hole transport capability,which hinders the overall activity.The present study demonstrates that a simple photoetching strategy is able to introduce gradient distributed oxygen vacancies(GO_(V))in the thick FeOOH layer and significantly enhances the photogenerated holes transport dynamics.The incorporation of GO_(V)within FeOOH not only realizes the“relay transport”of photogenerated hole through the progressive upward shift of the valence band in the spatial distribution,but also provides abundant oxidation active sites by efficient hole trapping.These improvements effectively improve the oxygen evolution reaction(OER)activities and mitigate photocorrosion by the instantaneous hole extraction.Consequently,the FeOOH-GO_(V)layer enables the BVO/FeOOH-GO_(V)photoanode to achieve an impressive photocurrent density of 5.37 mA cm^(-2)and a robust operational stability up to 160 h at 1.23 VRHE,setting new benchmarks for current density and stability in FeOOH-based BVO photoanodes.This work provides an effective avenue to optimize OER cocatalysts for constructing highly efficient and stable photoelectrochemical water splitting devices.展开更多
Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers of...Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers offer advantages such as reduced material usage,lower refrigerant charge,and compact structure.However,they also face challenges,including increased refrigerant pressure drop and smaller heat transfer area inside the tubes.This paper combines the advantages and disadvantages of both small and large-diameter tubes and proposes a combined-diameter heat exchanger,consisting of large and small diameters,for use in the indoor units of split-type air conditioners.There are relatively few studies in this area.In this paper,A theoretical and numerical computation method is employed to establish a theoretical-numerical calculation model,and its reliability is verified through experiments.Using this model,the optimal combined diameters and flow path design for a combined-diameter heat exchanger using R32 as the working fluid are derived.The results show that the heat transfer performance of all combined diameter configurations improves by 2.79%to 8.26%compared to the baseline design,with the coefficient of performance(COP)increasing from 4.15 to 4.27~4.5.These designs can save copper material,but at the cost of an increase in pressure drop by 66.86%to 131.84%.The scheme IIIH,using R32,is the optimal combined-diameter and flow path configuration that balances both heat transfer performance and economic cost.展开更多
This study examines the viscoelastic-plastic behavior of thermoplastic resin poly-ether-ether-ketone(PEEK)under high temperature and strain rate conditions,highlighting its potential in aerospace applications due to i...This study examines the viscoelastic-plastic behavior of thermoplastic resin poly-ether-ether-ketone(PEEK)under high temperature and strain rate conditions,highlighting its potential in aerospace applications due to its impact resistance.A dualhardening constitutive model that combines physical and phenomenological approaches is developed to simulate the mechanical behavior of PEEK.The model explicitly incorporates its marked tension-compression asymmetry in plasticity and relaxation,along with thermal softening at high strain rates,enabling accurate predictions over a wide range of temperatures and strain rates with minimal parameters.This study establishes a comprehensive workflow from experimentation to finite element(FE)simulation for thermoplastic resins.Uniaxial tensile and compression tests(23℃-180℃,0.00229s^(-1)-0,19361s^(-1))and split Hopkinson pressure bar(SHPB)tests(1094.08s^(-1)-5957.88s^(-1))are performed to capture stress-strain responses across various conditions,with small-scale specimens enhancing fracture strain measurement accuracy,and quantify the Taylor-Quinney factor of the PEEK material during the adiabatic heating process.The findings demonstrate that the proposed constitutive model effectively predicts yield points across different strain rates and temperatures,with parameters easily obtainable through simple experimental methods,enhancing its practical applications.展开更多
The current technical standards primarily relied on experience to judge the interfacial bonding properties between the self-compacting concrete filling layer and the steam-cured concrete precast slab in CRTS Ⅲ slab b...The current technical standards primarily relied on experience to judge the interfacial bonding properties between the self-compacting concrete filling layer and the steam-cured concrete precast slab in CRTS Ⅲ slab ballastless track structure.This study sought to enhance technical standards for evaluating interfacial bonding properties by suggesting the use of the splitting tensile strength to evaluate the impact of bubble defects.Specimens were fabricated through on-site experiment.The percent of each area of 6 cm^(2)or more bubble defect was 0 in most of specimens.When the cumulative area of all bub-ble defects reached 12%,the splitting tensile strength value was 0.67 MPa,which exceeded the minimum required value of 0.5 MPa for ensuring bonding interface adhesion.Furthermore,when the cumulative area of all bubble defects reached 8%,the splitting tensile strength value was 0.85 MPa,which exceeded the minimum required value of 0.8 MPa,thereby over-coming the negative impact of each area of 10 cm^(2) or more bubble defect.Additionally,keeping the cumulative area of each area of 6 cm^(2) or more bubble defect below 6%ensured adequate bonding strength and reduced the occurrence of specimens with lower splitting tensile strength values.展开更多
Deep rock engineering is affected by coupled thermo-hydro-mechanical(THM)-dynamic fields,necessitating the elucidation of the dynamic mechanical behavior and failure mechanisms.This study utilized a Multi-field Couple...Deep rock engineering is affected by coupled thermo-hydro-mechanical(THM)-dynamic fields,necessitating the elucidation of the dynamic mechanical behavior and failure mechanisms.This study utilized a Multi-field Coupled Controlled Split Hopkinson Pressure Bar(MCC-SHPB)system to elucidate the cross-scale dynamic responses of rocks and the boundaries of failure modes under THM coupling.Impact tests were conducted on green sandstone under coupled conditions of temperature(25℃-80℃),confining pressure(0-15 MPa),and seepage water pressure(0-15 MPa).Scanning electron microscopy(SEM)microstructural characterization and COMSOL Multiphysics numerical simulations were conducted,and a dynamic constitutive theoretical framework and failure-prediction methodology were established.We investigated the impact toughness index(I_(t)),dynamic modulus(E_(d)),dynamic triaxial compressive strength(TCS_(d)),fragmentation degree(W),and failure modes of green sandstone under thermo-confining pressure-seepage-impact loading conditions.The key findings reveal that the(I_(t))reflects different energy regulation mechanisms across different confining pressure regimes.Thermal-microcrack interactions dominate at low pressure,and energy absorption prevails at high pressure.A triphasic dynamic modulus model captures stiffness evolution under energy-driven conditions,revealing cross-scale crack nucleation-propagation and fragment reorganization.The TCSd inflection point signifies energy dissipation shifts,causing nonlinear skeleton bearing-capacity degradation.A critical criterion based on the W was established to distinguish between the two failure modes and predict the unstable failure initiation.Numerical simulations were used to elucidate the effects of inertia-dominated crack propagation and stress wave interference,validating the critical criterion and the predictive accuracy of the theoretical model during cross-scale failure.This study provides a theoretical foundation for assessing the dynamic stability of rock masses subjected to multi-field coupling during deep resource exploitation.展开更多
The paper first analyzes price change due to stock splits in Chinese stock markets,which shows stock prices typically go up for stock splits.Then theoretical analyses based on risk theory are presented to explain the ...The paper first analyzes price change due to stock splits in Chinese stock markets,which shows stock prices typically go up for stock splits.Then theoretical analyses based on risk theory are presented to explain the reason,where the method comes from a new perspective and obtained theoretical conclusions show that stock splits typically make stock price go up if risk-compensation function is convex,and go down if risk-compensation function is concave.Stock prices typically go up for stock splits because risk-compensation functions are mainly convex.The obtained conclusions are consistent with the known results in the last three decades.展开更多
The unique wave-manipulation capabilities of zero-index metamaterials(ZIMs)offer a new opportunity for realizing bound states in the continuum(BICs).However,the relationship between anomalous scattering and BICs remai...The unique wave-manipulation capabilities of zero-index metamaterials(ZIMs)offer a new opportunity for realizing bound states in the continuum(BICs).However,the relationship between anomalous scattering and BICs remains underexplored when parity–time(PT)symmetry is introduced.In this work,we demonstrate that a BIC splits into a pair of lasing modes carrying opposite topological charges by introducing PT symmetry through gain-loss cylinders embedded in ZIM layers.Theoretical analysis and numerical simulations reveal that lasing and unidirectional transparency phenomena result from the singularities and exceptional points of the scattering matrix.Moreover,exceptional points can be tuned via propagation phase modulation in the air gap,and their coalescence produces quasi-BICs with symmetric responses.This work provides a framework for manipulating BICs and topological lasing modes in non-Hermitian systems,offering new insights for designing non-Hermitian photonic devices.展开更多
Green hydrogen from water splitting has emerged as a critical energy vector with the potential to spearhead the global transition to a fossil fuel-independent society.The field of catalysis has been revolutionized by ...Green hydrogen from water splitting has emerged as a critical energy vector with the potential to spearhead the global transition to a fossil fuel-independent society.The field of catalysis has been revolutionized by single-atom catalysts(SACs),which exhibit unique and intricate interactions between atomically dispersed metal atoms and their supports.Recently,bimetallic SACs(bimSACs)have garnered significant attention for leveraging the synergistic functions of two metal ions coordinated on appropriately designed supports.BimSACs offer an avenue for rich metal–metal and metal–support cooperativity,potentially addressing current limitations of SACs in effectively furnishing transformations which involve synchronous proton–electron exchanges,substrate activation with reversible redox cycles,simultaneous multi-electron transfer,regulation of spin states,tuning of electronic properties,and cyclic transition states with low activation energies.This review aims to encapsulate the growing advancements in bimSACs,with an emphasis on their pivotal role in hydrogen generation via water splitting.We subsequently delve into advanced experimental methodologies for the elaborate characterization of SACs,elucidate their electronic properties,and discuss their local coordination environment.Overall,we present comprehensive discussion on the deployment of bimSACs in both hydrogen evolution reaction and oxygen evolution reaction,the two half-reactions of the water electrolysis process.展开更多
文摘This paper takes Zoomlion （Changsha Zoomlion Heavy Industry Science and Technology Development Co., Ltd） as an example and illustrates the reasons why traditional theories of stock dividends and stock splits cannot rationally explain the large stock dividend and stock split behavior among Chinese listed companies. The paper offers the following points after analyzing the current situation of China＇s capital market： As many investors seek after the stocks with large stock dividends and stock splits and form a ＂herd effect＂, it greatly pushes up the price of these stocks. Thus, companies＇ managers can cater these investors＇ irrational behavior, and help their companies get more funds from secondary equity offerings, or help their large shareholders and institutional investors to obtain more returns after lifting the sell restriction on their shares.
基金Supported by the National Natural Science Foundation of China(No.52273056)the Science and Technology Development Program of Jilin Province,China(No.YDZJ202501ZYTS305)。
文摘Electrochemical water splitting represents a sustainable technology for hydrogen(H_(2))production.However,its large-scale implementation is hindered by the high overpotentials required for both the cathodic hydrogen evolution reaction(HER)and the anodic oxygen evolution reaction(OER).Transition metal-based catalysts have garnered significant research interest as promising alternatives to noble-metal catalysts,owing to their low cost,tunable composition,and noble-metal-like catalytic activity.Nevertheless,systematic reviews on their application as bifunctional catalysts for overall water splitting(OWS)are still limited.This review comprehensively outlines the principal categories of bifunctional transition metal electrocatalysts derived from electrospun nanofibers(NFs),including metals,oxides,phosphides,sulfides,and carbides.Key strategies for enhancing their catalytic performance are systematically summarized,such as heterointerface engineering,heteroatom doping,metal-nonmetal-metal bridging architectures,and single-atom site design.Finally,current challenges and future research directions are discussed,aiming to provide insightful perspectives for the rational design of high-performance electrocatalysts for OWS.
基金supported by a grant(No.CRPG-25-2054)under the Cybersecurity Research and Innovation Pioneers Initiative,provided by the National Cybersecurity Authority(NCA)in the Kingdom of Saudi Arabia.
文摘Split Learning(SL)has been promoted as a promising collaborative machine learning technique designed to address data privacy and resource efficiency.Specifically,neural networks are divided into client and server subnetworks in order to mitigate the exposure of sensitive data and reduce the overhead on client devices,thereby making SL particularly suitable for resource-constrained devices.Although SL prevents the direct transmission of raw data,it does not alleviate entirely the risk of privacy breaches.In fact,the data intermediately transmitted to the server sub-model may include patterns or information that could reveal sensitive data.Moreover,achieving a balance between model utility and data privacy has emerged as a challenging problem.In this article,we propose a novel defense approach that combines:(i)Adversarial learning,and(ii)Network channel pruning.In particular,the proposed adversarial learning approach is specifically designed to reduce the risk of private data exposure while maintaining high performance for the utility task.On the other hand,the suggested channel pruning enables the model to adaptively adjust and reactivate pruned channels while conducting adversarial training.The integration of these two techniques reduces the informativeness of the intermediate data transmitted by the client sub-model,thereby enhancing its robustness against attribute inference attacks without adding significant computational overhead,making it wellsuited for IoT devices,mobile platforms,and Internet of Vehicles(IoV)scenarios.The proposed defense approach was evaluated using EfficientNet-B0,a widely adopted compact model,along with three benchmark datasets.The obtained results showcased its superior defense capability against attribute inference attacks compared to existing state-of-the-art methods.This research’s findings demonstrated the effectiveness of the proposed channel pruning-based adversarial training approach in achieving the intended compromise between utility and privacy within SL frameworks.In fact,the classification accuracy attained by the attackers witnessed a drastic decrease of 70%.
基金the financial support from the National Natural Science Foundation of China (Nos.21805170,22172093)Natural Science Foundation of Shandong Province (Nos.ZR2023QB219,ZR2021QB161)Qingdao Postdoctoral Innovation Project (No.QDBSH20220202031)。
文摘Herein,we have developed a straightforward wet-chemical method to synthesize a series of Pd-based alloy nanowires(NWs),including Pd Pt NWs,Pd Au NWs,Pd Ir NWs,and Pd Ru NWs,which exhibits high mass activity and turnover frequency(TOF) for HER,surpassing Pt/C by 4.6-fold and 1.5-fold in acidic and alkaline electrolytes,respectively.It also demonstrates high stability in alkaline electrolyte at a current density of 220 m A/cm^(2) for 280 h,highlighting its potential for practical applications under industrial current conditions.Pd Pt NWs exhibited ultrathin structures with head-to-tail kinks and inherent defects,significantly increasing the density of active sites and precisely tuning the electronic structure,which could accelerate reaction kinetics and boost water-splitting electrocatalytic performance.This study highlights the potential of Pd Pt NWs as highly efficient catalysts,offering outstanding catalytic performance and stability for practical applications.
基金The National Natural Science Foundations of China (12202219)the Natural Science Foundations of Ningxia (2024AAC02009, 2023AAC05001)the Ningxia Youth Top Talents Training Project。
文摘The fast solution of linear equations has always been one of the hot spots in scientific computing.A kind of the diagonal matrix splitting iteration methods are provided,which is different from the classical matrix splitting methods.Taking the decomposition of the diagonal elements for coefficient matrix as the key point,some new preconditioners are constructed.Taking the tri-diagonal coefficient matrix as an example,the convergence domains and optimal relaxation factor of the new method are analyzed theoretically.The presented new iteration methods are applied to solve linear algebraic equations,even 2D and 3D diffusion problems with the fully implicit discretization.The results of numerical experiments are matched with the theoretical analysis,and show that the iteration numbers are reduced greatly.The superiorities of presented iteration methods exceed some classical iteration methods dramatically.
文摘The Internet of Vehicles,or IoV,is expected to lessen pollution,ease traffic,and increase road safety.IoV entities’interconnectedness,however,raises the possibility of cyberattacks,which can have detrimental effects.IoV systems typically send massive volumes of raw data to central servers,which may raise privacy issues.Additionally,model training on IoV devices with limited resources normally leads to slower training times and reduced service quality.We discuss a privacy-preserving Federated Split Learning with Tiny Machine Learning(TinyML)approach,which operates on IoV edge devices without sharing sensitive raw data.Specifically,we focus on integrating split learning(SL)with federated learning(FL)and TinyML models.FL is a decentralisedmachine learning(ML)technique that enables numerous edge devices to train a standard model while retaining data locally collectively.The article intends to thoroughly discuss the architecture and challenges associated with the increasing prevalence of SL in the IoV domain,coupled with FL and TinyML.The approach starts with the IoV learning framework,which includes edge computing,FL,SL,and TinyML,and then proceeds to discuss how these technologies might be integrated.We elucidate the comprehensive operational principles of Federated and split learning by examining and addressingmany challenges.We subsequently examine the integration of SL with FL and various applications of TinyML.Finally,exploring the potential integration of FL and SL with TinyML in the IoV domain is referred to as FSL-TM.It is a superior method for preserving privacy as it conducts model training on individual devices or edge nodes,thereby obviating the necessity for centralised data aggregation,which presents considerable privacy threats.The insights provided aim to help both researchers and practitioners understand the complicated terrain of FL and SL,hence facilitating advancement in this swiftly progressing domain.
基金support from the Joint Funds of the National Natural Science Foundation of China(Grant No.U23A2060)the National Natural Science Foundation of China(Grant Nos.42177143 and 52474150).
文摘Drilling and blasting tunneling is a cyclic process in which tunnel rock undergoes repeated blast loading,affecting its dynamic characteristics,energy evolution,and damage progression.To explore the dynamic mechanical properties and damage mechanisms of carbonaceous slate under cyclic impact loads of varying intensities,cyclic dynamic tests are conducted using a triaxial split Hopkinson pressure bar.This study analyzes the stress-strain relationship,energy damage evolution,and macro-to-micro failure characteristics.The results show that peak stress and strain are significantly influenced by impact intensity and the number of impacts.The initial dynamic stress is positively correlated with the impact intensity,but with more impact,the dynamic stress decreases while the peak strain increases.Energy evolution follows a pattern of"slow growthfluctuating growthrapid growth,"with the crack initiation stress and its proportion decreasing.CT and SEM analyses reveal that as the impact intensity increases,failure becomes more chaotic,the fracture volume increases,and the fracture mode shifts from interlayer and intergranular to through-layer and trans-granular fractures.These findings provide an experimental basis for soft rock tunnel stability analysis.
基金supported by the Australian Research Council(ARC)Projects(DP220101139,DP220101142,and LP240100542).
文摘High‐entropy amorphous catalysts(HEACs)integrate multielement synergy with structural disorder,making them promising candidates for water splitting.Their distinctive features—including flexible coordination environments,tunable electronic structures,abundant unsaturated active sites,and dynamic structural reassembly—collectively enhance electrochemical activity and durability under operating conditions.This review summarizes recent advances in HEACs for hydrogen evolution,oxygen evolution,and overall water splitting,highlighting their disorder-driven advantages over crystalline counterparts.Catalytic performance benchmarks are presented,and mechanistic insights are discussed,focusing on how multimetallic synergy,amorphization effect,and in‐situ reconstruction cooperatively regulate reaction pathways.These insights provide guidance for the rational design of next‐generation amorphous high‐entropy electrocatalysts with improved efficiency and durability.
基金supported in part by the National Natural Science Foundation of China(NSFC)under Grant 62276109The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through the Research Group Project number(ORF-2025-585).
文摘The personalized fine-tuning of large languagemodels(LLMs)on edge devices is severely constrained by limited computation resources.Although split federated learning alleviates on-device burdens,its effectiveness diminishes in few-shot reasoning scenarios due to the low data efficiency of conventional supervised fine-tuning,which leads to excessive communication overhead.To address this,we propose Language-Empowered Split Fine-Tuning(LESFT),a framework that integrates split architectures with a contrastive-inspired fine-tuning paradigm.LESFT simultaneously learns frommultiple logically equivalent but linguistically diverse reasoning chains,providing richer supervisory signals and improving data efficiency.This process-oriented training allows more effective reasoning adaptation with fewer samples.Extensive experiments demonstrate that LESFT consistently outperforms strong baselines such as SplitLoRA in task accuracy.LESFT consistently outperforms strong baselines on GSM8K,CommonsenseQA,and AQUA_RAT,with the largest gains observed on Qwen2.5-3B.These results indicate that LESFT can effectively adapt large language models for reasoning tasks under the computational and communication constraints of edge environments.
基金supported by the State Key Laboratory of Solidification Processing in NWPU(SKLSP202407)the National Natural Science Foundation of China(52402130)+2 种基金the Natural Science Basis Research Plan in Shaanxi Province of China(2024JC-YBQN-0384)the Shaanxi Science and Technology Innovation Team(2023-CX-TD-44)the National Natural Science Foundation of China(52301015).
文摘Highly active and stable FeOOH cocatalysts are essential for achieving optimal performance of BiVO_(4)(BVO)photoanodes.Despite offering remarkable structural stability,widely used thick FeOOH cocatalysts often suffer from insufficient hole transport capability,which hinders the overall activity.The present study demonstrates that a simple photoetching strategy is able to introduce gradient distributed oxygen vacancies(GO_(V))in the thick FeOOH layer and significantly enhances the photogenerated holes transport dynamics.The incorporation of GO_(V)within FeOOH not only realizes the“relay transport”of photogenerated hole through the progressive upward shift of the valence band in the spatial distribution,but also provides abundant oxidation active sites by efficient hole trapping.These improvements effectively improve the oxygen evolution reaction(OER)activities and mitigate photocorrosion by the instantaneous hole extraction.Consequently,the FeOOH-GO_(V)layer enables the BVO/FeOOH-GO_(V)photoanode to achieve an impressive photocurrent density of 5.37 mA cm^(-2)and a robust operational stability up to 160 h at 1.23 VRHE,setting new benchmarks for current density and stability in FeOOH-based BVO photoanodes.This work provides an effective avenue to optimize OER cocatalysts for constructing highly efficient and stable photoelectrochemical water splitting devices.
基金supported by Supported by the Scientific Research Foundation for High-Level Talents of Zhoukou Normal University(ZKNUC2024018).
文摘Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers offer advantages such as reduced material usage,lower refrigerant charge,and compact structure.However,they also face challenges,including increased refrigerant pressure drop and smaller heat transfer area inside the tubes.This paper combines the advantages and disadvantages of both small and large-diameter tubes and proposes a combined-diameter heat exchanger,consisting of large and small diameters,for use in the indoor units of split-type air conditioners.There are relatively few studies in this area.In this paper,A theoretical and numerical computation method is employed to establish a theoretical-numerical calculation model,and its reliability is verified through experiments.Using this model,the optimal combined diameters and flow path design for a combined-diameter heat exchanger using R32 as the working fluid are derived.The results show that the heat transfer performance of all combined diameter configurations improves by 2.79%to 8.26%compared to the baseline design,with the coefficient of performance(COP)increasing from 4.15 to 4.27~4.5.These designs can save copper material,but at the cost of an increase in pressure drop by 66.86%to 131.84%.The scheme IIIH,using R32,is the optimal combined-diameter and flow path configuration that balances both heat transfer performance and economic cost.
文摘This study examines the viscoelastic-plastic behavior of thermoplastic resin poly-ether-ether-ketone(PEEK)under high temperature and strain rate conditions,highlighting its potential in aerospace applications due to its impact resistance.A dualhardening constitutive model that combines physical and phenomenological approaches is developed to simulate the mechanical behavior of PEEK.The model explicitly incorporates its marked tension-compression asymmetry in plasticity and relaxation,along with thermal softening at high strain rates,enabling accurate predictions over a wide range of temperatures and strain rates with minimal parameters.This study establishes a comprehensive workflow from experimentation to finite element(FE)simulation for thermoplastic resins.Uniaxial tensile and compression tests(23℃-180℃,0.00229s^(-1)-0,19361s^(-1))and split Hopkinson pressure bar(SHPB)tests(1094.08s^(-1)-5957.88s^(-1))are performed to capture stress-strain responses across various conditions,with small-scale specimens enhancing fracture strain measurement accuracy,and quantify the Taylor-Quinney factor of the PEEK material during the adiabatic heating process.The findings demonstrate that the proposed constitutive model effectively predicts yield points across different strain rates and temperatures,with parameters easily obtainable through simple experimental methods,enhancing its practical applications.
基金supported by a grant from China railway corporation science and technology research and development plan project(Grant No.2017G005-B)funding support by Wuyi University’s Hong Kong and Macao Joint Research and Development Fund(Grants No.2021WGALH15)funding support by the Innovation and Technology Commission of Hong Kong SAR Government to the Hong Kong Branch of National Rail Transit Electrification and Automation Engineering Technology Research Center(Grant No.K-BBY1).
文摘The current technical standards primarily relied on experience to judge the interfacial bonding properties between the self-compacting concrete filling layer and the steam-cured concrete precast slab in CRTS Ⅲ slab ballastless track structure.This study sought to enhance technical standards for evaluating interfacial bonding properties by suggesting the use of the splitting tensile strength to evaluate the impact of bubble defects.Specimens were fabricated through on-site experiment.The percent of each area of 6 cm^(2)or more bubble defect was 0 in most of specimens.When the cumulative area of all bub-ble defects reached 12%,the splitting tensile strength value was 0.67 MPa,which exceeded the minimum required value of 0.5 MPa for ensuring bonding interface adhesion.Furthermore,when the cumulative area of all bubble defects reached 8%,the splitting tensile strength value was 0.85 MPa,which exceeded the minimum required value of 0.8 MPa,thereby over-coming the negative impact of each area of 10 cm^(2) or more bubble defect.Additionally,keeping the cumulative area of each area of 6 cm^(2) or more bubble defect below 6%ensured adequate bonding strength and reduced the occurrence of specimens with lower splitting tensile strength values.
基金supported by the National Natural Science Foundation of China(Grant Nos.12272411 and 42007259).
文摘Deep rock engineering is affected by coupled thermo-hydro-mechanical(THM)-dynamic fields,necessitating the elucidation of the dynamic mechanical behavior and failure mechanisms.This study utilized a Multi-field Coupled Controlled Split Hopkinson Pressure Bar(MCC-SHPB)system to elucidate the cross-scale dynamic responses of rocks and the boundaries of failure modes under THM coupling.Impact tests were conducted on green sandstone under coupled conditions of temperature(25℃-80℃),confining pressure(0-15 MPa),and seepage water pressure(0-15 MPa).Scanning electron microscopy(SEM)microstructural characterization and COMSOL Multiphysics numerical simulations were conducted,and a dynamic constitutive theoretical framework and failure-prediction methodology were established.We investigated the impact toughness index(I_(t)),dynamic modulus(E_(d)),dynamic triaxial compressive strength(TCS_(d)),fragmentation degree(W),and failure modes of green sandstone under thermo-confining pressure-seepage-impact loading conditions.The key findings reveal that the(I_(t))reflects different energy regulation mechanisms across different confining pressure regimes.Thermal-microcrack interactions dominate at low pressure,and energy absorption prevails at high pressure.A triphasic dynamic modulus model captures stiffness evolution under energy-driven conditions,revealing cross-scale crack nucleation-propagation and fragment reorganization.The TCSd inflection point signifies energy dissipation shifts,causing nonlinear skeleton bearing-capacity degradation.A critical criterion based on the W was established to distinguish between the two failure modes and predict the unstable failure initiation.Numerical simulations were used to elucidate the effects of inertia-dominated crack propagation and stress wave interference,validating the critical criterion and the predictive accuracy of the theoretical model during cross-scale failure.This study provides a theoretical foundation for assessing the dynamic stability of rock masses subjected to multi-field coupling during deep resource exploitation.
基金Supported by the National Natural Science Foundation of China(11471120)the Science and Technology Commission of Shanghai Municipality(19JC1420100)。
文摘The paper first analyzes price change due to stock splits in Chinese stock markets,which shows stock prices typically go up for stock splits.Then theoretical analyses based on risk theory are presented to explain the reason,where the method comes from a new perspective and obtained theoretical conclusions show that stock splits typically make stock price go up if risk-compensation function is convex,and go down if risk-compensation function is concave.Stock prices typically go up for stock splits because risk-compensation functions are mainly convex.The obtained conclusions are consistent with the known results in the last three decades.
基金supported by the National Natural Science Foundation of China(Grant Nos.12504361,12274313,and 62465005)the Natural Science Foundation of Guangxi(Grant No.2025GXNSFBA069179)the Guangxi Colleges and Universities Young and Middle-aged Teachers’Basic Scientific Research Ability Enhancement Project(Grant No.2025KY0093)。
文摘The unique wave-manipulation capabilities of zero-index metamaterials(ZIMs)offer a new opportunity for realizing bound states in the continuum(BICs).However,the relationship between anomalous scattering and BICs remains underexplored when parity–time(PT)symmetry is introduced.In this work,we demonstrate that a BIC splits into a pair of lasing modes carrying opposite topological charges by introducing PT symmetry through gain-loss cylinders embedded in ZIM layers.Theoretical analysis and numerical simulations reveal that lasing and unidirectional transparency phenomena result from the singularities and exceptional points of the scattering matrix.Moreover,exceptional points can be tuned via propagation phase modulation in the air gap,and their coalescence produces quasi-BICs with symmetric responses.This work provides a framework for manipulating BICs and topological lasing modes in non-Hermitian systems,offering new insights for designing non-Hermitian photonic devices.
基金support from the Czech Science Foundation,project EXPRO,No 19-27454Xsupport by the European Union under the REFRESH—Research Excellence For Region Sustainability and High-tech Industries project number CZ.10.03.01/00/22_003/0000048 via the Operational Programme Just Transition from the Ministry of the Environment of the Czech Republic+1 种基金Horizon Europe project EIC Pathfinder Open 2023,“GlaS-A-Fuels”(No.101130717)supported from ERDF/ESF,project TECHSCALE No.CZ.02.01.01/00/22_008/0004587).
文摘Green hydrogen from water splitting has emerged as a critical energy vector with the potential to spearhead the global transition to a fossil fuel-independent society.The field of catalysis has been revolutionized by single-atom catalysts(SACs),which exhibit unique and intricate interactions between atomically dispersed metal atoms and their supports.Recently,bimetallic SACs(bimSACs)have garnered significant attention for leveraging the synergistic functions of two metal ions coordinated on appropriately designed supports.BimSACs offer an avenue for rich metal–metal and metal–support cooperativity,potentially addressing current limitations of SACs in effectively furnishing transformations which involve synchronous proton–electron exchanges,substrate activation with reversible redox cycles,simultaneous multi-electron transfer,regulation of spin states,tuning of electronic properties,and cyclic transition states with low activation energies.This review aims to encapsulate the growing advancements in bimSACs,with an emphasis on their pivotal role in hydrogen generation via water splitting.We subsequently delve into advanced experimental methodologies for the elaborate characterization of SACs,elucidate their electronic properties,and discuss their local coordination environment.Overall,we present comprehensive discussion on the deployment of bimSACs in both hydrogen evolution reaction and oxygen evolution reaction,the two half-reactions of the water electrolysis process.
