This paper presents a proper splitting iterative method for comparing the general restricted linear euqations Ax=b, x ∈T （where, b ∈AT, and T is an arbitrary but fixed subspace of C<sup>m</sup>） and th...This paper presents a proper splitting iterative method for comparing the general restricted linear euqations Ax=b, x ∈T （where, b ∈AT, and T is an arbitrary but fixed subspace of C<sup>m</sup>） and the generalized in A<sub>T,S</sub> For the special case when b ∈AT and dim（T）=dim（AT）, this splitting iterative methverse A<sub>T,S</sub> hod converges to A<sub>T,S</sub>b （the unique solution of the general restricted system Ax=bx ∈T）.展开更多
Let A=M-N be a regular splitting of an M-matrix. We study the spectral properties of the ineration matrix M-1N. Under a mild assumption on M-1 N. some necessary and sufficent conditions such that p(M-1N)=1 are obtaine...Let A=M-N be a regular splitting of an M-matrix. We study the spectral properties of the ineration matrix M-1N. Under a mild assumption on M-1 N. some necessary and sufficent conditions such that p(M-1N)=1 are obtained and the algebraic multiplicity and the index associated with eigenvalue 1 in M-1N are considered.展开更多
We report the experimental results on measuring the isotope shifts and hyperfine splittings of all ytterbium isotopes for a 399-nm transition by using a quite simple and novel method. It benefits from the advantages o...We report the experimental results on measuring the isotope shifts and hyperfine splittings of all ytterbium isotopes for a 399-nm transition by using a quite simple and novel method. It benefits from the advantages of the modulation transfer spectroscopy in an ytterbium hollow cathode lamp and the Doppler-free spectroscopy in a collimated ytterbium atomic beam. The key technique in this experiment is simultaneously measuring the frequency separations of the two spectra twice, and the separation difference between two measurements is solely determined by the well-defined frequency of an acousto-optics modulator. Compared with the most of previously reported experimental results, ours are more accurate and completed, which will provide the useful information for developing a more accurate theoretical model to describe the interaction inside an ytterbium atom.展开更多
Let M be a 3-manifold, F= ／{F1,F2,／…,Fn} be a collection of essential closed surfaces in M （for any i,j ∈ {1,...,n}, if i≠j, Fi is not parallel to Fj and Fi∩ Fj=Ф） and 0M be a collection of components of ...Let M be a 3-manifold, F= ／{F1,F2,／…,Fn} be a collection of essential closed surfaces in M （for any i,j ∈ {1,...,n}, if i≠j, Fi is not parallel to Fj and Fi∩ Fj=Ф） and 0M be a collection of components of M. Suppose M- ∪Fi∈F Fi×（-1,1） contains k components M1,M2…,Mk. If each Mi has a Heegaard splitting Vi ∪Si Wi with d（Si） 〉 4（g（M1）＋ … ＋g（Mk））, then any minimal Heegaard splitting of M relative to 0M is obtained by doing amalgamations and self-amalgamations from minimal Heegaard splittings or -stabilization of minimal Heegaard splittings of M1,M2…,Mk.展开更多
Suppose V∪S W is a genus-g weakly reducible Heegaard splitting of a closed 3-manifold with finitely many pairs of disjoint compression disks on distinct sides up to isotopy and g>2.We show V∪_(S) W admits an unte...Suppose V∪S W is a genus-g weakly reducible Heegaard splitting of a closed 3-manifold with finitely many pairs of disjoint compression disks on distinct sides up to isotopy and g>2.We show V∪_(S) W admits an untelescoping:(V_(1)∪_(S1) W_(1))∪F(W_(2)∪_(S2) V_(2))such that Wi has a unique separating compressing disk and d(S_(i))≥2,for i=1,2.If there exist more than one but finitely many pairs of disjoint compression disks,at least one of d(S_(i))is 2 and S is a critical Heegaard surface.展开更多
The word theorem states that x can be denoted as a rotation inserting word of A if x is in the normal closure of A in F(X). As an application of the theorem, in this note a condition that guarantees reducing the genus...The word theorem states that x can be denoted as a rotation inserting word of A if x is in the normal closure of A in F(X). As an application of the theorem, in this note a condition that guarantees reducing the genus of Heegaard splitting of 3-manifolds is given. This leads Poincare conjecture to a new formulation.展开更多
In this paper we introduce the sign matrix of a nonlinear system of equations x = Gx to characterize its hybrid and asynchronous monotonicity as well as convexity. Based on the configuration of the matrix, we define a...In this paper we introduce the sign matrix of a nonlinear system of equations x = Gx to characterize its hybrid and asynchronous monotonicity as well as convexity. Based on the configuration of the matrix, we define a new type of regular splittings of the system with which the solvability and construction of solutions for the system are transformed to those of the couple systems of the splitting formIt is shown that this couple systems is a general model for developing monotonic enclosure methods of solutions for various types of nonlinear system of equations.展开更多
Recently, M. Hanke and M. Neumann([4]) have derived a necessary and sufficient condition on a splitting of A = U-V, which leads to a fixed point system, such that the iterative sequence converges to the least squares ...Recently, M. Hanke and M. Neumann([4]) have derived a necessary and sufficient condition on a splitting of A = U-V, which leads to a fixed point system, such that the iterative sequence converges to the least squares solution of minimum a-norm of the system Ax = b. In this paper, we give a necessary and sufficient condition on the splitting such that the iterative sequence converges to the weighted Moore-Penrose solution of the system Ax = b for every to is an element of C-n and every b is an element of C-m. We also provide a necessary and sufficient condition such that the iterative sequence is convergent for every to x(0) is an element of C-n.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
Designing a highly active and stable bifunctional catalyst is essential for achieving superior overall water splitting(OWS).In this study,a three-dimensional(3D)core-shell structure Co_(3)S_(4)/CuS@NiFe LDH nanocoral ...Designing a highly active and stable bifunctional catalyst is essential for achieving superior overall water splitting(OWS).In this study,a three-dimensional(3D)core-shell structure Co_(3)S_(4)/CuS@NiFe LDH nanocoral spheres electrocatalyst was constructed on nickel foam(NF)via an interfacial engineering strategy.This 3D core-shell heterostructure maximizes the exposure of active sites,optimizes the charge transport pathway and accelerates gas release rates.The protective shell strategy of NiFe LDH provides favorable stability,which contributes to inhibiting the electrochemical corrosion of the electrocatalyst and mitigating the toxic effects of Cl−and other microorganisms during the seawater splitting process.Moreover,the introduction of NiFe LDH induces a change in the OER mechanism from an adsorption evolution mechanism(AEM)to a lattice oxygen mechanism(LOM),which improves the intrinsic activity of the catalyst.Consequently,Co_(3)S_(4)/CuS@NiFe LDH demonstrates exceptional performance in the oxygen evolution reaction(OER)(η100=251 mV)and in the hydrogen evolution reaction(HER)(η100=254 mV),alongside remarkable stability over 100 h.For OWS,it exhibits a voltage of 1.46 V at 10 mA/cm^(2) and maintain stability for 100 h.Impressively,Co_(3)S_(4)/CuS@NiFe LDH still possesses outstanding activity and stability in natural alkaline seawater.This work proposes interfacial engineering to construct bifunctional catalysts with core-shell heterostructures,providing instructive guidelines for the design of highly efficient electrocatalysts toward seawater electrolysis.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
This insightful review explores the electrochemical principles and energy potential of electrocatalytic water splitting(EWS).It highlights recent advancements,identifies key challenges,and underscores the pivotal role...This insightful review explores the electrochemical principles and energy potential of electrocatalytic water splitting(EWS).It highlights recent advancements,identifies key challenges,and underscores the pivotal role of EWS in enabling the transition to sustainable energy systems.This work contextualizes the significance of green hydrogen in global decarbonization pathways and examines the historical progression of electrocatalysis.The fundamental thermodynamics and mechanistic pathways governing both the hydrogen and oxygen evolution reactions(HER and OER)are analyzed,highlighting energy barriers and rate-determining steps.Various electrode architectures and electrochemical cell configurations are evaluated,including a comparative assessment of key electrolyzer technologies and their performance characteristics.Furthermore,we critically examine recent advances and persistent limitations across the landscape of electrocatalysts,spanning noble metal-based materials,earth-abundant transition metal compounds,and emerging materials.Design principles and mechanistic insights drawn from electronic structu re modulation,defect engineering,doping strategies,and na noscale morphology control are elucidated to establish robust structure-property-performance relationships.Major challenges including sluggish oxygen evolution kinetics,catalyst degradation mechanisms,and the integration of devices with intermittent renewable energy sources are thoroughly examined.This work also debates advanced strategies such as hybrid photoelectrochemical systems,flexible device architectures,and the direct utilization of non-traditional water sources(e.g.,seawater,wastewater)as promising pathways for future development.Finally,it is specifically distinguished by its critical focus on bridging the gap between fundamental electrocatalysts development and practical system-level integration,addressing the challenges of scalability and deployment under industrially relevant conditions.This comprehensive review provides a strategic outlook and identifies key scientific priorities for optimizing EWS systems toward efficient,robust,and scalable hydrogen generation.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
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
基金This project is supported by Science and Technology Foundation of Shanghai Higher Eduction,Doctoral Program Foundation of Higher Education in China.National Nature Science Foundation of China and Youth Science Foundation of Universities in Shanghai.
文摘This paper presents a proper splitting iterative method for comparing the general restricted linear euqations Ax=b, x ∈T （where, b ∈AT, and T is an arbitrary but fixed subspace of C<sup>m</sup>） and the generalized in A<sub>T,S</sub> For the special case when b ∈AT and dim（T）=dim（AT）, this splitting iterative methverse A<sub>T,S</sub> hod converges to A<sub>T,S</sub>b （the unique solution of the general restricted system Ax=bx ∈T）.
基金Supported by National Natural Science Foundation of China
文摘Let A=M-N be a regular splitting of an M-matrix. We study the spectral properties of the ineration matrix M-1N. Under a mild assumption on M-1 N. some necessary and sufficent conditions such that p(M-1N)=1 are obtained and the algebraic multiplicity and the index associated with eigenvalue 1 in M-1N are considered.
基金Project supported by the National Natural Science Foundation of China(Grant No.10774044)the National Key Basic Research and Development Program of China(Grant No.2010CB922903)+1 种基金the Science Foundation of the Science and Technology Commission of Shanghai Municipality of China(Grant No.07JC14019)the Shanghai Pujiang Talent Program of China(Grant No.07PJ14038)
文摘We report the experimental results on measuring the isotope shifts and hyperfine splittings of all ytterbium isotopes for a 399-nm transition by using a quite simple and novel method. It benefits from the advantages of the modulation transfer spectroscopy in an ytterbium hollow cathode lamp and the Doppler-free spectroscopy in a collimated ytterbium atomic beam. The key technique in this experiment is simultaneously measuring the frequency separations of the two spectra twice, and the separation difference between two measurements is solely determined by the well-defined frequency of an acousto-optics modulator. Compared with the most of previously reported experimental results, ours are more accurate and completed, which will provide the useful information for developing a more accurate theoretical model to describe the interaction inside an ytterbium atom.
基金Supported by the National Natural Science Foundation of China(Grant No.10901029)
文摘Let M be a 3-manifold, F= ／{F1,F2,／…,Fn} be a collection of essential closed surfaces in M （for any i,j ∈ {1,...,n}, if i≠j, Fi is not parallel to Fj and Fi∩ Fj=Ф） and 0M be a collection of components of M. Suppose M- ∪Fi∈F Fi×（-1,1） contains k components M1,M2…,Mk. If each Mi has a Heegaard splitting Vi ∪Si Wi with d（Si） 〉 4（g（M1）＋ … ＋g（Mk））, then any minimal Heegaard splitting of M relative to 0M is obtained by doing amalgamations and self-amalgamations from minimal Heegaard splittings or -stabilization of minimal Heegaard splittings of M1,M2…,Mk.
基金Supported by the National Natural Science Foundation of China(Grant No.11671064)。
文摘Suppose V∪S W is a genus-g weakly reducible Heegaard splitting of a closed 3-manifold with finitely many pairs of disjoint compression disks on distinct sides up to isotopy and g>2.We show V∪_(S) W admits an untelescoping:(V_(1)∪_(S1) W_(1))∪F(W_(2)∪_(S2) V_(2))such that Wi has a unique separating compressing disk and d(S_(i))≥2,for i=1,2.If there exist more than one but finitely many pairs of disjoint compression disks,at least one of d(S_(i))is 2 and S is a critical Heegaard surface.
文摘The word theorem states that x can be denoted as a rotation inserting word of A if x is in the normal closure of A in F(X). As an application of the theorem, in this note a condition that guarantees reducing the genus of Heegaard splitting of 3-manifolds is given. This leads Poincare conjecture to a new formulation.
文摘In this paper we introduce the sign matrix of a nonlinear system of equations x = Gx to characterize its hybrid and asynchronous monotonicity as well as convexity. Based on the configuration of the matrix, we define a new type of regular splittings of the system with which the solvability and construction of solutions for the system are transformed to those of the couple systems of the splitting formIt is shown that this couple systems is a general model for developing monotonic enclosure methods of solutions for various types of nonlinear system of equations.
文摘Recently, M. Hanke and M. Neumann([4]) have derived a necessary and sufficient condition on a splitting of A = U-V, which leads to a fixed point system, such that the iterative sequence converges to the least squares solution of minimum a-norm of the system Ax = b. In this paper, we give a necessary and sufficient condition on the splitting such that the iterative sequence converges to the weighted Moore-Penrose solution of the system Ax = b for every to is an element of C-n and every b is an element of C-m. We also provide a necessary and sufficient condition such that the iterative sequence is convergent for every to x(0) is an element of C-n.
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supported by the National Natural Science Foundation of China(No.52274304).
文摘Designing a highly active and stable bifunctional catalyst is essential for achieving superior overall water splitting(OWS).In this study,a three-dimensional(3D)core-shell structure Co_(3)S_(4)/CuS@NiFe LDH nanocoral spheres electrocatalyst was constructed on nickel foam(NF)via an interfacial engineering strategy.This 3D core-shell heterostructure maximizes the exposure of active sites,optimizes the charge transport pathway and accelerates gas release rates.The protective shell strategy of NiFe LDH provides favorable stability,which contributes to inhibiting the electrochemical corrosion of the electrocatalyst and mitigating the toxic effects of Cl−and other microorganisms during the seawater splitting process.Moreover,the introduction of NiFe LDH induces a change in the OER mechanism from an adsorption evolution mechanism(AEM)to a lattice oxygen mechanism(LOM),which improves the intrinsic activity of the catalyst.Consequently,Co_(3)S_(4)/CuS@NiFe LDH demonstrates exceptional performance in the oxygen evolution reaction(OER)(η100=251 mV)and in the hydrogen evolution reaction(HER)(η100=254 mV),alongside remarkable stability over 100 h.For OWS,it exhibits a voltage of 1.46 V at 10 mA/cm^(2) and maintain stability for 100 h.Impressively,Co_(3)S_(4)/CuS@NiFe LDH still possesses outstanding activity and stability in natural alkaline seawater.This work proposes interfacial engineering to construct bifunctional catalysts with core-shell heterostructures,providing instructive guidelines for the design of highly efficient electrocatalysts toward seawater electrolysis.
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Higher Education Commission(HEC)of Pakistan for financial support under grants#377-IPFP-Ⅱ/Batch-1st/SRGP-NAHE/HEC-2022-27 along with ASIP-Support Award Letter#ASIP/R&D/HEC/2024/10006/83387/127。
文摘This insightful review explores the electrochemical principles and energy potential of electrocatalytic water splitting(EWS).It highlights recent advancements,identifies key challenges,and underscores the pivotal role of EWS in enabling the transition to sustainable energy systems.This work contextualizes the significance of green hydrogen in global decarbonization pathways and examines the historical progression of electrocatalysis.The fundamental thermodynamics and mechanistic pathways governing both the hydrogen and oxygen evolution reactions(HER and OER)are analyzed,highlighting energy barriers and rate-determining steps.Various electrode architectures and electrochemical cell configurations are evaluated,including a comparative assessment of key electrolyzer technologies and their performance characteristics.Furthermore,we critically examine recent advances and persistent limitations across the landscape of electrocatalysts,spanning noble metal-based materials,earth-abundant transition metal compounds,and emerging materials.Design principles and mechanistic insights drawn from electronic structu re modulation,defect engineering,doping strategies,and na noscale morphology control are elucidated to establish robust structure-property-performance relationships.Major challenges including sluggish oxygen evolution kinetics,catalyst degradation mechanisms,and the integration of devices with intermittent renewable energy sources are thoroughly examined.This work also debates advanced strategies such as hybrid photoelectrochemical systems,flexible device architectures,and the direct utilization of non-traditional water sources(e.g.,seawater,wastewater)as promising pathways for future development.Finally,it is specifically distinguished by its critical focus on bridging the gap between fundamental electrocatalysts development and practical system-level integration,addressing the challenges of scalability and deployment under industrially relevant conditions.This comprehensive review provides a strategic outlook and identifies key scientific priorities for optimizing EWS systems toward efficient,robust,and scalable hydrogen generation.
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 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.
