Objectives This study aimed to explore the lagged and cumulative effects of risk factors on disability in older adults using distributed lag non-linear models(DLNMs).Methods We utilized data from the China Health and ...Objectives This study aimed to explore the lagged and cumulative effects of risk factors on disability in older adults using distributed lag non-linear models(DLNMs).Methods We utilized data from the China Health and Retirement Longitudinal Study(CHARLS).After feature selection via Elastic Net Regularization,we applied DLNMs to evaluate the lagged effects of risk factors.Disability was defined as the presence of any difficulties in basic activities of daily living(BADL).The cumulative relative risk(CRR)was calculated by summing the lag-specific risk estimates,representing the cumulative disability risk over the specified lag period.Effect modifications and sensitivity analyses were also performed.Results This study included a total of 2,318 participants.Early-phase lag factors,such as the difficulty in stooping(CRR=3.58;95%CI:2.31-5.55;P<0.001)and walking(CRR=2.77;95%CI:1.39-5.55;P<0.001),exerted the strongest effects immediately upon occurrence.Mid-phase lag factors,such as arthritis(CRR=1.51;95%CI:1.10-2.06;P=0.001),showed a resurgence in disability risk within 2-3 years.Late-phase lag factors,including depressive symptoms(CRR=2.38;95%CI:1.30-4.35;P<0.001)and elevated systolic blood pressure(CRR=1.64;95%CI:1.06-2.79;P=0.02),exhibited significant long-term cumulative risks.Conversely,grip strength(CRR=0.80;95%CI:0.54-0.95;P=0.02)and social participation(CRR=0.89;95%CI:0.73-0.99;P=0.04)were significant protective factors.Conclusions The findings underscore the importance of tailored interventions that account for various lag characteristics of different factors to effectively mitigate disability risk.Future studies should explore the underlying biological and sociological mechanisms of these lagged effects,identify intervention strategies that target risk factors with different lagged patterns,and evaluate their effectiveness.展开更多
To investigate the damage evolution caused by stress-driven and sub-critical crack propagation within the Beishan granite under multi-creep triaxial compressive conditions,the distributed optical fiber sensing and X-r...To investigate the damage evolution caused by stress-driven and sub-critical crack propagation within the Beishan granite under multi-creep triaxial compressive conditions,the distributed optical fiber sensing and X-ray computed tomography were combined to obtain the strain distribution over the sample surface and internal fractures of the samples.The Gini and skewness(G-S)coefficients were used to quantify strain localization during tests,where the Gini coefficient reflects the degree of clustering of elements with high strain values,i.e.,strain localization/delocalization.The strain localization-induced asymmetry of data distribution is quantified by the skewness coefficient.A precursor to granite failure is defined by the rapid and simultaneous increase of the G-S coefficients,which are calculated from strain increment,giving an earlier warning of failure by about 8%peak stress than those from absolute strain values.Moreover,the process of damage accumulation due to stress-driven crack propagation in Beishan granite is different at various confining pressures as the stress exceeds the crack initiation stress.Concretely,strain localization is continuous until brittle failure at higher confining pressure,while both strain localization and delocalization occur at lower confining pressure.Despite the different stress conditions,a similar statistical characteristic of strain localization during the creep stage is observed.The Gini coefficient increases,and the skewness coefficient decreases slightly as the creep stress is below 95%peak stress.When the accelerated strain localization begins,the Gini and skewness coefficients increase rapidly and simultaneously.展开更多
A multi-stage stress relaxation test was performed on a granodiorite sample to understand the deformation process prior to the macroscopic failure of brittle rocks,as well as the transient response during stress relax...A multi-stage stress relaxation test was performed on a granodiorite sample to understand the deformation process prior to the macroscopic failure of brittle rocks,as well as the transient response during stress relaxation.Distributed optical fiber sensing was used to measure strains across the sample surface by helically wrapping the single-mode fiber around the cylindrical sample.Close agreement was observed between the circumferential strains obtained from the optical fibers and the extensometer.The reconstructed full-field strain contours show strain heterogeneity from the crack closure phase,and the strains in the later deformation phase are dominantly localized within the former high-strain zone.The Gini coefficient was used to quantify the degree of strain localization and shows an initial increase during the crack closure phase,a decrease during the linear elastic phase,and a subsequent increase during the post-yielding phase.This behavior corresponds to a process of initial localization from an imperfect boundary condition,homogenization,and eventual relocalization prior to the macroscopic failure of the sample.The transient strain rate decay during the stress relaxation phase was quantified using the p-value in the“Omori-like"power law function.A higher initial stress at the onset of relaxation results in a lower p-value,indicating a slower strain rate decay.As the sample approaches macroscopic failure,the lowest p-value shifts from the most damaged zone to adjacent areas,suggesting stress redistribution or crack propagation in deformed crystalline rocks under stress relaxation conditions.展开更多
Dear Editor,The letter deals with the distributed state and fault estimation of the whole physical layer for cyber-physical systems(CPSs) when the cyber layer suffers from DoS attacks. With the advancement of embedded...Dear Editor,The letter deals with the distributed state and fault estimation of the whole physical layer for cyber-physical systems(CPSs) when the cyber layer suffers from DoS attacks. With the advancement of embedded computing, communication and related hardware technologies, CPSs have attracted extensive attention and have been widely used in power system, traffic network, refrigeration system and other fields.展开更多
Curved geostructures,such as tunnels,are commonly encountered in geotechnical engineering and are critical to maintaining structural stability.Ensuring their proper performance through field monitoring during their se...Curved geostructures,such as tunnels,are commonly encountered in geotechnical engineering and are critical to maintaining structural stability.Ensuring their proper performance through field monitoring during their service life is essential for the overall functionality of geotechnical infrastructure.Distributed Brillouin sensing(DBS)is increasingly applied in geotechnical projects due to its ability to acquire spatially continuous strain and temperature distributions over distances of up to 150 km using a single optical fibre.However,limited by the complex operations of distributed optic fibre sensing(DFOS)sensors in curved structures,previous reports about exploiting DBS in geotechnical structural health monitoring(SHM)have mostly been focused on flat surfaces.The lack of suitable DFOS installation methods matched to the spatial characteristics of continuous monitoring is one of the major factors that hinder the further application of this technique in curved structures.This review paper starts with a brief introduction of the fundamental working principle of DBS and the inherent limitations of DBS being used on monitoring curved surfaces.Subsequently,the state-of-the-art installation methods of optical fibres in curved structures are reviewed and compared to address the most suitable scenario of each method and their advantages and disadvantages.The installation challenges of optical fibres that can highly affect measurement accuracy are also discussed in the paper.展开更多
Dear Editor,This letter focuses on the distributed cooperative regulation problem for a class of networked re-entrant manufacturing systems(RMSs).The networked system is structured with a three-tier architecture:the p...Dear Editor,This letter focuses on the distributed cooperative regulation problem for a class of networked re-entrant manufacturing systems(RMSs).The networked system is structured with a three-tier architecture:the production line,the manufacturing layer and the workshop layer.The dynamics of re-entrant production lines are governed by hyperbolic partial differential equations(PDEs)based on the law of mass conservation.展开更多
With the increasing popularity of blockchain applications, the security of data sources on the blockchain is gradually receiving attention. Providing reliable data for the blockchain safely and efficiently has become ...With the increasing popularity of blockchain applications, the security of data sources on the blockchain is gradually receiving attention. Providing reliable data for the blockchain safely and efficiently has become a research hotspot, and the security of the oracle responsible for providing reliable data has attracted much attention. The most widely used centralized oracles in blockchain, such as Provable and Town Crier, all rely on a single oracle to obtain data, which suffers from a single point of failure and limits the large-scale development of blockchain. To this end, the distributed oracle scheme is put forward, but the existing distributed oracle schemes such as Chainlink and Augur generally have low execution efficiency and high communication overhead, which leads to their poor applicability. To solve the above problems, this paper proposes a trusted distributed oracle scheme based on a share recovery threshold signature. First, a data verification method of distributed oracles is designed based on threshold signature. By aggregating the signatures of oracles, data from different data sources can be mutually verified, leading to a more efficient data verification and aggregation process. Then, a credibility-based cluster head election algorithm is designed, which reduces the communication overhead by clarifying the function distribution and building a hierarchical structure. Considering the good performance of the BLS threshold signature in large-scale applications, this paper combines it with distributed oracle technology and proposes a BLS threshold signature algorithm that supports share recovery in distributed oracles. The share recovery mechanism enables the proposed scheme to solve the key loss issue, and the setting of the threshold value enables the proposed scheme to complete signature aggregation with only a threshold number of oracles, making the scheme more robust. Finally, experimental results indicate that, by using the threshold signature technology and the cluster head election algorithm, our scheme effectively improves the execution efficiency of oracles and solves the problem of a single point of failure, leading to higher scalability and robustness.展开更多
The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level m...The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level model and technology called Spatial Grasp for dealing with large distributed systems,which can provide spatial vision,awareness,management,control,and even consciousness.The technology description includes its key Spatial Grasp Language(SGL),self-evolution of recursive SGL scenarios,and implementation of SGL interpreter converting distributed networked systems into powerful spatial engines.Examples of typical spatial scenarios in SGL include finding shortest path tree and shortest path between network nodes,collecting proper information throughout the whole world,elimination of multiple targets by intelligent teams of chasers,and withstanding cyber attacks in distributed networked systems.Also this paper compares Spatial Grasp model with traditional algorithms,confirming universality of the former for any spatial systems,while the latter just tools for concrete applications.展开更多
This paper designs distributed Nash equilibrium seeking strategies for heterogeneous dynamic cyber-physical systems.In particular, we are concerned with parametric uncertainties in the control channel of the players. ...This paper designs distributed Nash equilibrium seeking strategies for heterogeneous dynamic cyber-physical systems.In particular, we are concerned with parametric uncertainties in the control channel of the players. Moreover, the weights on communication links can be compromised by time-varying uncertainties, which can result from possibly malicious attacks,faults and disturbances. To deal with the unavailability of measurement of optimization errors, an output observer is constructed,based on which adaptive laws are designed to compensate for physical uncertainties. With adaptive laws, a new distributed Nash equilibrium seeking strategy is designed by further integrating consensus protocols and gradient search algorithms.Moreover, to further accommodate compromised communication weights resulting from cyber-uncertainties, the coupling strengths of the consensus module are designed to be adaptive. As a byproduct, the coupling strengths are independent of any global information. With theoretical investigations, it is proven that the proposed strategies are resilient to these uncertainties and players' actions are convergent to the Nash equilibrium. Simulation examples are given to numerically validate the effectiveness of the proposed strategies.展开更多
Responding to the stochasticity and uncertainty in the power height of distributed photovoltaic power generation.This paper presents a distributed photovoltaic ultra-short-term power forecasting method based on Variat...Responding to the stochasticity and uncertainty in the power height of distributed photovoltaic power generation.This paper presents a distributed photovoltaic ultra-short-term power forecasting method based on Variational Mode Decomposition(VMD)and Channel Attention Mechanism.First,Pearson’s correlation coefficient was utilized to filter out the meteorological factors that had a high impact on historical power.Second,the distributed PV power data were decomposed into a relatively smooth power series with different fluctuation patterns using variational modal decomposition(VMD).Finally,the reconstructed distributed PV power as well as other features are input into the combined CNN-SENet-BiLSTM model.In this model,the convolutional neural network(CNN)and channel attention mechanism dynamically adjust the weights while capturing the spatial features of the input data to improve the discriminative ability of key features.The extracted data is then fed into the bidirectional long short-term memory network(BiLSTM)to capture the time-series features,and the final output is the prediction result.The verification is conducted using a dataset from a distributed photovoltaic power station in the Northwest region of China.The results show that compared with other prediction methods,the method proposed in this paper has a higher prediction accuracy,which helps to improve the proportion of distributed PV access to the grid,and can guarantee the safe and stable operation of the power grid.展开更多
The distributed permutation flow shop scheduling problem(DPFSP)has received increasing attention in recent years.The iterated greedy algorithm(IGA)serves as a powerful optimizer for addressing such a problem because o...The distributed permutation flow shop scheduling problem(DPFSP)has received increasing attention in recent years.The iterated greedy algorithm(IGA)serves as a powerful optimizer for addressing such a problem because of its straightforward,single-solution evolution framework.However,a potential draw-back of IGA is the lack of utilization of historical information,which could lead to an imbalance between exploration and exploitation,especially in large-scale DPFSPs.As a consequence,this paper develops an IGA with memory and learning mechanisms(MLIGA)to efficiently solve the DPFSP targeted at the mini-malmakespan.InMLIGA,we incorporate a memory mechanism to make a more informed selection of the initial solution at each stage of the search,by extending,reconstructing,and reinforcing the information from previous solutions.In addition,we design a twolayer cooperative reinforcement learning approach to intelligently determine the key parameters of IGA and the operations of the memory mechanism.Meanwhile,to ensure that the experience generated by each perturbation operator is fully learned and to reduce the prior parameters of MLIGA,a probability curve-based acceptance criterion is proposed by combining a cube root function with custom rules.At last,a discrete adaptive learning rate is employed to enhance the stability of the memory and learningmechanisms.Complete ablation experiments are utilized to verify the effectiveness of the memory mechanism,and the results show that this mechanism is capable of improving the performance of IGA to a large extent.Furthermore,through comparative experiments involving MLIGA and five state-of-the-art algorithms on 720 benchmarks,we have discovered that MLI-GA demonstrates significant potential for solving large-scale DPFSPs.This indicates that MLIGA is well-suited for real-world distributed flow shop scheduling.展开更多
After a century of relative stability in the electricity sector,the widespread adoption of distributed energy resources,along with recent advancements in computing and communication technologies,has fundamentally alte...After a century of relative stability in the electricity sector,the widespread adoption of distributed energy resources,along with recent advancements in computing and communication technologies,has fundamentally altered how energy is consumed,traded,and utilized.This change signifies a crucial shift as the power system evolves from its traditional hierarchical organization to a more decentralized approach.At the heart of this transformation are innovative energy distribution models,like peer-to-peer(P2P)sharing,which enable communities to collaboratively manage their energy resources.The effectiveness of P2P sharing not only improves the economic prospects for prosumers,who generate and consume energy,but also enhances energy resilience and sustainability.This allows communities to better leverage local resources while fostering a sense of collective responsibility and collaboration in energy management.However,there is still no extensive implementation of such sharing models in today’s electricitymarkets.Research on distributed energy P2P trading is still in the exploratory stage,and it is particularly important to comprehensively understand and analyze the existing distributed energy P2P trading market.This paper contributes with an overview of the P2P markets that starts with the network framework,market structure,technical approach for trading mechanism,and blockchain technology,moving to the outlook in this field.展开更多
In this paper,we investigate the periodic traveling wave solutions problem for a single population model with advection and distributed delay.By the bifurcation analysis method,we can obtain periodic traveling wave so...In this paper,we investigate the periodic traveling wave solutions problem for a single population model with advection and distributed delay.By the bifurcation analysis method,we can obtain periodic traveling wave solutions for this model under the influence of advection term and distributed delay.The obtained results indicate that weak kernel and strong kernel can both deduce the existence of periodic traveling wave solutions.Finally,we apply the main results in this paper to Logistic model and Nicholson’s blowflies model.展开更多
Fraction repetition(FR)codes are integral in distributed storage systems(DSS)with exact repair-by-transfer,while pliable fraction repetition codes are vital for DSSs in which both the per-node storage and repetition d...Fraction repetition(FR)codes are integral in distributed storage systems(DSS)with exact repair-by-transfer,while pliable fraction repetition codes are vital for DSSs in which both the per-node storage and repetition degree can easily be adjusted simultaneously.This paper introduces a new type of pliable FR codes,called absolute balanced pliable FR(ABPFR)codes,in which the access balancing in DSS is considered.Additionally,the equivalence between pliable FR codes and resolvable transversal packings in combinatorial design theory is presented.Then constructions of pliable FR codes and ABPFR codes based on resolvable transversal packings are presented.展开更多
With the maturation of emerging information technologies(Internet of Things,cloud computing,and big data),distributed manufacturing has emerged as an important model for future manufacturing.3D printing,with its integ...With the maturation of emerging information technologies(Internet of Things,cloud computing,and big data),distributed manufacturing has emerged as an important model for future manufacturing.3D printing,with its integrated molding and design freedom,is a powerful catalyst for distributed manufacturing.This paper investigates the integrated production and transportation scheduling problem in distributed 3D printing.To solve this problem,we decompose the original problem into three sub-problems and design a multilevel optimization algorithm.We employ a genetic algorithm in the outer-level optimization to determine the optimal allocation of parts to machines.In the inner-level optimization,we utilize a simulated annealing algorithm to tackle the vehicle routing problem during the transportation stage followed by a local search algorithm to address the scheduling problem encountered during the production stage.Our algorithm is validated using real data from a 3D printing company,and the results show that our algorithm can obtain solutions that are the same as or better than those of Gurobi in a reasonable time for small-sized instances.Additionally,three types of initial methods are tested on large-sized instances to verify the efficiency of the proposed algorithm,and some interesting insights are also revealed and discussed.展开更多
Reconfiguration,as well as optimal utilization of distributed generation sources and capacitor banks,are highly effective methods for reducing losses and improving the voltage profile,or in other words,the power quali...Reconfiguration,as well as optimal utilization of distributed generation sources and capacitor banks,are highly effective methods for reducing losses and improving the voltage profile,or in other words,the power quality in the power distribution system.Researchers have considered the use of distributed generation resources in recent years.There are numerous advantages to utilizing these resources,the most significant of which are the reduction of network losses and enhancement of voltage stability.Non-dominated Sorting Genetic Algorithm II(NSGA-II),Multi-Objective Particle Swarm Optimization(MOPSO),and Intersect Mutation Differential Evolution(IMDE)algorithms are used in this paper to perform optimal reconfiguration,simultaneous location,and capacity determination of distributed generation resources and capacitor banks.Three scenarios were used to replicate the studies.The reconfiguration of the switches,as well as the location and determination of the capacitor bank’s optimal capacity,were investigated in this scenario.However,in the third scenario,reconfiguration,and determining the location and capacity of the Distributed Generation(DG)resources and capacitor banks have been carried out simultaneously.Finally,the simulation results of these three algorithms are compared.The results indicate that the proposed NSGAII algorithm outperformed the other two multi-objective algorithms and was capable of maintaining smaller objective functions in all scenarios.Specifically,the energy losses were reduced from 211 to 51.35 kW(a 75.66%reduction),119.13 kW(a 43.54%reduction),and 23.13 kW(an 89.04%reduction),while the voltage stability index(VSI)decreased from 6.96 to 2.105,1.239,and 1.257,respectively,demonstrating significant improvement in the voltage profile.展开更多
In today’s complex and rapidly changing business environment,the traditional single-organization service model can no longer meet the needs of multi-organization collaborative processing.Based on existing business pr...In today’s complex and rapidly changing business environment,the traditional single-organization service model can no longer meet the needs of multi-organization collaborative processing.Based on existing business process engine technologies,this paper proposes a distributed heterogeneous process engine collaboration method for crossorganizational scenarios.The core of this method lies in achieving unified access and management of heterogeneous engines through a business process model adapter and a common operation interface.The key technologies include:Meta-Process Control Architecture,where the central engine(meta-process scheduler)decomposes the original process into fine-grained sub-processes and schedules their execution in a unified order,ensuring consistency with the original process logic;Process Model Adapter,which addresses the BPMN2.0 model differences among heterogeneous engines such as Flowable and Activiti through a matching-and-replacement mechanism,providing a unified process model standard for different engines;Common Operation Interface,which encapsulates the REST APIs of heterogeneous engines and offers a single,standardized interface for process deployment,instance management,and status synchronization.This method integrates multiple techniques to address API differences,process model incompatibilities,and execution order consistency issues among heterogeneous engines,delivering a unified,flexible,and scalable solution for cross-organizational process collaboration.展开更多
Photovoltaic(PV)power generation is undergoing significant growth and serves as a key driver of the global energy transition.However,its intermittent nature,which fluctuates with weather conditions,has raised concerns...Photovoltaic(PV)power generation is undergoing significant growth and serves as a key driver of the global energy transition.However,its intermittent nature,which fluctuates with weather conditions,has raised concerns about grid stability.Accurate PV power prediction has been demonstrated as crucial for power system operation and scheduling,enabling power slope control,fluctuation mitigation,grid stability enhancement,and reliable data support for secure grid operation.However,existing prediction models primarily target centralized PV plants,largely neglecting the spatiotemporal coupling dynamics and output uncertainties inherent to distributed PV systems.This study proposes a novel Spatio-Temporal Graph Neural Network(STGNN)architecture for distributed PV power generation prediction,designed to enhance distributed photovoltaic(PV)power generation forecasting accuracy and support regional grid scheduling.This approach models each PV power plant as a node in an undirected graph,with edges representing correlations between plants to capture spatial dependencies.The model comprises multiple Sparse Attention-based Adaptive Spatio-Temporal(SAAST)blocks.The SAAST blocks include sparse temporal attention,sparse spatial attention,an adaptive Graph Convolutional Network(GCN),and a temporal convolution network(TCN).These components eliminate weak temporal and spatial correlations,better represent dynamic spatial dependencies,and further enhance prediction accuracy.Finally,multi-dimensional comparative experiments between the STGNN and other models on the DKASC PV dataset demonstrate its superior performance in terms of accuracy and goodness-of-fit for distributed PV power generation prediction.展开更多
Coal mining induces changes in the nature of rock and soil bodies,as well as hydrogeological conditions,which can easily trigger the occurrence of geological disasters such as water inrush,movement of the coal seam ro...Coal mining induces changes in the nature of rock and soil bodies,as well as hydrogeological conditions,which can easily trigger the occurrence of geological disasters such as water inrush,movement of the coal seam roof and floor,and rock burst.Transparency in coal mine geological conditions provides technical support for intelligent coal mining and geological disaster prevention.In this sense,it is of great significance to address the requirements for informatizing coal mine geological conditions,dynamically adjust sensing parameters,and accurately identify disaster characteristics so as to prevent and control coal mine geological disasters.This paper examines the various action fields associated with geological disasters in mining faces and scrutinizes the types and sensing parameters of geological disasters resulting from coal seam mining.On this basis,it summarizes a distributed fiber-optic sensing technology framework for transparent geology in coal mines.Combined with the multi-field monitoring characteristics of the strain field,the temperature field,and the vibration field of distributed optical fiber sensing technology,parameters such as the strain increment ratio,the aquifer temperature gradient,and the acoustic wave amplitude are extracted as eigenvalues for identifying rock breaking,aquifer water level,and water cut range,and a multi-field sensing method is established for identifying the characteristics of mining-induced rock mass disasters.The development direction of transparent geology based on optical fiber sensing technology is proposed in terms of the aspects of sensing optical fiber structure for large deformation monitoring,identification accuracy of optical fiber acoustic signals,multi-parameter monitoring,and early warning methods.展开更多
As the environmental problems become increasingly serious,distributed electrical propulsion systems with higher aerodynamic efficiency and lower pollution emission have received extensive attention in recent years.The...As the environmental problems become increasingly serious,distributed electrical propulsion systems with higher aerodynamic efficiency and lower pollution emission have received extensive attention in recent years.The distributed electrical propulsion usually employs the new aero-propulsion integrated configuration.A simulation strategy for internal and external flow coupling based on the combination of lifting line theory and body force method is proposed.The lifting line theory and body force method as source term are embedded into the Navier-Stokes formulation.The lift and drag characteristics of the aero-propulsion coupling configuration are simulated.The results indicate that the coupling configuration has the most obvious lift augmentation at 12°angle of attack,which can provide an 11.11%increase in lift for the airfoil.At 0°angle of attack,the pressure difference on the lip parts provides the thrust component,which results in a lower drag coefficient.Additionally,the failure impact of a ducted fan at the middle or edge on aerodynamics is investigated.For the two failure conditions,the lift of the coupling configuration is decreased significantly by 27.85%and 26.14%respectively,and the lip thrust is decreased by 70.74%and 56.48%respectively.展开更多
基金supported by ScientificResearch Fund of National Health Commission of the People’s Republic of China-Major Science and Technology Program for Medicine and Health in Zhejiang Province(WKJ-ZJ-2406).
文摘Objectives This study aimed to explore the lagged and cumulative effects of risk factors on disability in older adults using distributed lag non-linear models(DLNMs).Methods We utilized data from the China Health and Retirement Longitudinal Study(CHARLS).After feature selection via Elastic Net Regularization,we applied DLNMs to evaluate the lagged effects of risk factors.Disability was defined as the presence of any difficulties in basic activities of daily living(BADL).The cumulative relative risk(CRR)was calculated by summing the lag-specific risk estimates,representing the cumulative disability risk over the specified lag period.Effect modifications and sensitivity analyses were also performed.Results This study included a total of 2,318 participants.Early-phase lag factors,such as the difficulty in stooping(CRR=3.58;95%CI:2.31-5.55;P<0.001)and walking(CRR=2.77;95%CI:1.39-5.55;P<0.001),exerted the strongest effects immediately upon occurrence.Mid-phase lag factors,such as arthritis(CRR=1.51;95%CI:1.10-2.06;P=0.001),showed a resurgence in disability risk within 2-3 years.Late-phase lag factors,including depressive symptoms(CRR=2.38;95%CI:1.30-4.35;P<0.001)and elevated systolic blood pressure(CRR=1.64;95%CI:1.06-2.79;P=0.02),exhibited significant long-term cumulative risks.Conversely,grip strength(CRR=0.80;95%CI:0.54-0.95;P=0.02)and social participation(CRR=0.89;95%CI:0.73-0.99;P=0.04)were significant protective factors.Conclusions The findings underscore the importance of tailored interventions that account for various lag characteristics of different factors to effectively mitigate disability risk.Future studies should explore the underlying biological and sociological mechanisms of these lagged effects,identify intervention strategies that target risk factors with different lagged patterns,and evaluate their effectiveness.
基金supported by the National Natural Science Foundation of China(Grant No.52339001).
文摘To investigate the damage evolution caused by stress-driven and sub-critical crack propagation within the Beishan granite under multi-creep triaxial compressive conditions,the distributed optical fiber sensing and X-ray computed tomography were combined to obtain the strain distribution over the sample surface and internal fractures of the samples.The Gini and skewness(G-S)coefficients were used to quantify strain localization during tests,where the Gini coefficient reflects the degree of clustering of elements with high strain values,i.e.,strain localization/delocalization.The strain localization-induced asymmetry of data distribution is quantified by the skewness coefficient.A precursor to granite failure is defined by the rapid and simultaneous increase of the G-S coefficients,which are calculated from strain increment,giving an earlier warning of failure by about 8%peak stress than those from absolute strain values.Moreover,the process of damage accumulation due to stress-driven crack propagation in Beishan granite is different at various confining pressures as the stress exceeds the crack initiation stress.Concretely,strain localization is continuous until brittle failure at higher confining pressure,while both strain localization and delocalization occur at lower confining pressure.Despite the different stress conditions,a similar statistical characteristic of strain localization during the creep stage is observed.The Gini coefficient increases,and the skewness coefficient decreases slightly as the creep stress is below 95%peak stress.When the accelerated strain localization begins,the Gini and skewness coefficients increase rapidly and simultaneously.
基金support of her postdoctoral research at the GFZ Helmholtz Centre for Geosciences.P.Pan acknowledges the financial support of the National Natural Science Foundation of China(Grant No.52339001)H.Hofmann and Y.Ji acknowledge the financial support of the Helmholtz Association's Initiative and Networking Fund for the Helmholtz Young Investigator Group ARES(contract number VH-NG-1516).
文摘A multi-stage stress relaxation test was performed on a granodiorite sample to understand the deformation process prior to the macroscopic failure of brittle rocks,as well as the transient response during stress relaxation.Distributed optical fiber sensing was used to measure strains across the sample surface by helically wrapping the single-mode fiber around the cylindrical sample.Close agreement was observed between the circumferential strains obtained from the optical fibers and the extensometer.The reconstructed full-field strain contours show strain heterogeneity from the crack closure phase,and the strains in the later deformation phase are dominantly localized within the former high-strain zone.The Gini coefficient was used to quantify the degree of strain localization and shows an initial increase during the crack closure phase,a decrease during the linear elastic phase,and a subsequent increase during the post-yielding phase.This behavior corresponds to a process of initial localization from an imperfect boundary condition,homogenization,and eventual relocalization prior to the macroscopic failure of the sample.The transient strain rate decay during the stress relaxation phase was quantified using the p-value in the“Omori-like"power law function.A higher initial stress at the onset of relaxation results in a lower p-value,indicating a slower strain rate decay.As the sample approaches macroscopic failure,the lowest p-value shifts from the most damaged zone to adjacent areas,suggesting stress redistribution or crack propagation in deformed crystalline rocks under stress relaxation conditions.
基金supported by the National Natural Science Foundation of China(62303273,62373226)the National Research Foundation,Singapore through the Medium Sized Center for Advanced Robotics Technology Innovation(WP2.7)
文摘Dear Editor,The letter deals with the distributed state and fault estimation of the whole physical layer for cyber-physical systems(CPSs) when the cyber layer suffers from DoS attacks. With the advancement of embedded computing, communication and related hardware technologies, CPSs have attracted extensive attention and have been widely used in power system, traffic network, refrigeration system and other fields.
基金support provided by Science Foundation Ireland Frontiers for the Future Programme,21/FFP-P/10090.
文摘Curved geostructures,such as tunnels,are commonly encountered in geotechnical engineering and are critical to maintaining structural stability.Ensuring their proper performance through field monitoring during their service life is essential for the overall functionality of geotechnical infrastructure.Distributed Brillouin sensing(DBS)is increasingly applied in geotechnical projects due to its ability to acquire spatially continuous strain and temperature distributions over distances of up to 150 km using a single optical fibre.However,limited by the complex operations of distributed optic fibre sensing(DFOS)sensors in curved structures,previous reports about exploiting DBS in geotechnical structural health monitoring(SHM)have mostly been focused on flat surfaces.The lack of suitable DFOS installation methods matched to the spatial characteristics of continuous monitoring is one of the major factors that hinder the further application of this technique in curved structures.This review paper starts with a brief introduction of the fundamental working principle of DBS and the inherent limitations of DBS being used on monitoring curved surfaces.Subsequently,the state-of-the-art installation methods of optical fibres in curved structures are reviewed and compared to address the most suitable scenario of each method and their advantages and disadvantages.The installation challenges of optical fibres that can highly affect measurement accuracy are also discussed in the paper.
文摘Dear Editor,This letter focuses on the distributed cooperative regulation problem for a class of networked re-entrant manufacturing systems(RMSs).The networked system is structured with a three-tier architecture:the production line,the manufacturing layer and the workshop layer.The dynamics of re-entrant production lines are governed by hyperbolic partial differential equations(PDEs)based on the law of mass conservation.
基金supported by the National Natural Science Foundation of China(Grant No.62102449)the Central Plains Talent Program under Grant No.224200510003.
文摘With the increasing popularity of blockchain applications, the security of data sources on the blockchain is gradually receiving attention. Providing reliable data for the blockchain safely and efficiently has become a research hotspot, and the security of the oracle responsible for providing reliable data has attracted much attention. The most widely used centralized oracles in blockchain, such as Provable and Town Crier, all rely on a single oracle to obtain data, which suffers from a single point of failure and limits the large-scale development of blockchain. To this end, the distributed oracle scheme is put forward, but the existing distributed oracle schemes such as Chainlink and Augur generally have low execution efficiency and high communication overhead, which leads to their poor applicability. To solve the above problems, this paper proposes a trusted distributed oracle scheme based on a share recovery threshold signature. First, a data verification method of distributed oracles is designed based on threshold signature. By aggregating the signatures of oracles, data from different data sources can be mutually verified, leading to a more efficient data verification and aggregation process. Then, a credibility-based cluster head election algorithm is designed, which reduces the communication overhead by clarifying the function distribution and building a hierarchical structure. Considering the good performance of the BLS threshold signature in large-scale applications, this paper combines it with distributed oracle technology and proposes a BLS threshold signature algorithm that supports share recovery in distributed oracles. The share recovery mechanism enables the proposed scheme to solve the key loss issue, and the setting of the threshold value enables the proposed scheme to complete signature aggregation with only a threshold number of oracles, making the scheme more robust. Finally, experimental results indicate that, by using the threshold signature technology and the cluster head election algorithm, our scheme effectively improves the execution efficiency of oracles and solves the problem of a single point of failure, leading to higher scalability and robustness.
文摘The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level model and technology called Spatial Grasp for dealing with large distributed systems,which can provide spatial vision,awareness,management,control,and even consciousness.The technology description includes its key Spatial Grasp Language(SGL),self-evolution of recursive SGL scenarios,and implementation of SGL interpreter converting distributed networked systems into powerful spatial engines.Examples of typical spatial scenarios in SGL include finding shortest path tree and shortest path between network nodes,collecting proper information throughout the whole world,elimination of multiple targets by intelligent teams of chasers,and withstanding cyber attacks in distributed networked systems.Also this paper compares Spatial Grasp model with traditional algorithms,confirming universality of the former for any spatial systems,while the latter just tools for concrete applications.
基金supported by the National Key R&D Program of China(2022ZD0119604)the National Natural Science Foundation of China(NSFC)(62173181,62222308,62221004)the Natural Science Foundation of Jiangsu Province(BK20220139)
文摘This paper designs distributed Nash equilibrium seeking strategies for heterogeneous dynamic cyber-physical systems.In particular, we are concerned with parametric uncertainties in the control channel of the players. Moreover, the weights on communication links can be compromised by time-varying uncertainties, which can result from possibly malicious attacks,faults and disturbances. To deal with the unavailability of measurement of optimization errors, an output observer is constructed,based on which adaptive laws are designed to compensate for physical uncertainties. With adaptive laws, a new distributed Nash equilibrium seeking strategy is designed by further integrating consensus protocols and gradient search algorithms.Moreover, to further accommodate compromised communication weights resulting from cyber-uncertainties, the coupling strengths of the consensus module are designed to be adaptive. As a byproduct, the coupling strengths are independent of any global information. With theoretical investigations, it is proven that the proposed strategies are resilient to these uncertainties and players' actions are convergent to the Nash equilibrium. Simulation examples are given to numerically validate the effectiveness of the proposed strategies.
基金supported by the Inner Mongolia Power Company 2024 Staff Innovation Studio Innovation Project“Research on Cluster Output Prediction and Group Control Technology for County-Wide Distributed Photovoltaic Construction”.
文摘Responding to the stochasticity and uncertainty in the power height of distributed photovoltaic power generation.This paper presents a distributed photovoltaic ultra-short-term power forecasting method based on Variational Mode Decomposition(VMD)and Channel Attention Mechanism.First,Pearson’s correlation coefficient was utilized to filter out the meteorological factors that had a high impact on historical power.Second,the distributed PV power data were decomposed into a relatively smooth power series with different fluctuation patterns using variational modal decomposition(VMD).Finally,the reconstructed distributed PV power as well as other features are input into the combined CNN-SENet-BiLSTM model.In this model,the convolutional neural network(CNN)and channel attention mechanism dynamically adjust the weights while capturing the spatial features of the input data to improve the discriminative ability of key features.The extracted data is then fed into the bidirectional long short-term memory network(BiLSTM)to capture the time-series features,and the final output is the prediction result.The verification is conducted using a dataset from a distributed photovoltaic power station in the Northwest region of China.The results show that compared with other prediction methods,the method proposed in this paper has a higher prediction accuracy,which helps to improve the proportion of distributed PV access to the grid,and can guarantee the safe and stable operation of the power grid.
基金supported in part by the National Key Research and Development Program of China under Grant No.2021YFF0901300in part by the National Natural Science Foundation of China under Grant Nos.62173076 and 72271048.
文摘The distributed permutation flow shop scheduling problem(DPFSP)has received increasing attention in recent years.The iterated greedy algorithm(IGA)serves as a powerful optimizer for addressing such a problem because of its straightforward,single-solution evolution framework.However,a potential draw-back of IGA is the lack of utilization of historical information,which could lead to an imbalance between exploration and exploitation,especially in large-scale DPFSPs.As a consequence,this paper develops an IGA with memory and learning mechanisms(MLIGA)to efficiently solve the DPFSP targeted at the mini-malmakespan.InMLIGA,we incorporate a memory mechanism to make a more informed selection of the initial solution at each stage of the search,by extending,reconstructing,and reinforcing the information from previous solutions.In addition,we design a twolayer cooperative reinforcement learning approach to intelligently determine the key parameters of IGA and the operations of the memory mechanism.Meanwhile,to ensure that the experience generated by each perturbation operator is fully learned and to reduce the prior parameters of MLIGA,a probability curve-based acceptance criterion is proposed by combining a cube root function with custom rules.At last,a discrete adaptive learning rate is employed to enhance the stability of the memory and learningmechanisms.Complete ablation experiments are utilized to verify the effectiveness of the memory mechanism,and the results show that this mechanism is capable of improving the performance of IGA to a large extent.Furthermore,through comparative experiments involving MLIGA and five state-of-the-art algorithms on 720 benchmarks,we have discovered that MLI-GA demonstrates significant potential for solving large-scale DPFSPs.This indicates that MLIGA is well-suited for real-world distributed flow shop scheduling.
基金funded by the National Natural Science Foundation of China(52167013)the Key Program of Natural Science Foundation of Gansu Province(24JRRA225)Natural Science Foundation of Gansu Province(23JRRA891).
文摘After a century of relative stability in the electricity sector,the widespread adoption of distributed energy resources,along with recent advancements in computing and communication technologies,has fundamentally altered how energy is consumed,traded,and utilized.This change signifies a crucial shift as the power system evolves from its traditional hierarchical organization to a more decentralized approach.At the heart of this transformation are innovative energy distribution models,like peer-to-peer(P2P)sharing,which enable communities to collaboratively manage their energy resources.The effectiveness of P2P sharing not only improves the economic prospects for prosumers,who generate and consume energy,but also enhances energy resilience and sustainability.This allows communities to better leverage local resources while fostering a sense of collective responsibility and collaboration in energy management.However,there is still no extensive implementation of such sharing models in today’s electricitymarkets.Research on distributed energy P2P trading is still in the exploratory stage,and it is particularly important to comprehensively understand and analyze the existing distributed energy P2P trading market.This paper contributes with an overview of the P2P markets that starts with the network framework,market structure,technical approach for trading mechanism,and blockchain technology,moving to the outlook in this field.
基金Supported by the National Natural Science Foundation of China(12261050)Science and Technology Project of Department of Education of Jiangxi Province(GJJ2201612 and GJJ211027)Natural Science Foundation of Jiangxi Province of China(20212BAB202021)。
文摘In this paper,we investigate the periodic traveling wave solutions problem for a single population model with advection and distributed delay.By the bifurcation analysis method,we can obtain periodic traveling wave solutions for this model under the influence of advection term and distributed delay.The obtained results indicate that weak kernel and strong kernel can both deduce the existence of periodic traveling wave solutions.Finally,we apply the main results in this paper to Logistic model and Nicholson’s blowflies model.
基金Supported in part by the National Key R&D Program of China(No.2020YFA0712300)NSFC(No.61872353)。
文摘Fraction repetition(FR)codes are integral in distributed storage systems(DSS)with exact repair-by-transfer,while pliable fraction repetition codes are vital for DSSs in which both the per-node storage and repetition degree can easily be adjusted simultaneously.This paper introduces a new type of pliable FR codes,called absolute balanced pliable FR(ABPFR)codes,in which the access balancing in DSS is considered.Additionally,the equivalence between pliable FR codes and resolvable transversal packings in combinatorial design theory is presented.Then constructions of pliable FR codes and ABPFR codes based on resolvable transversal packings are presented.
基金supported by the National Natural Science Foundation of China(72022018,72091210)Youth Innovation Promotion Association,Chinese Academy of Sciences(2021454).
文摘With the maturation of emerging information technologies(Internet of Things,cloud computing,and big data),distributed manufacturing has emerged as an important model for future manufacturing.3D printing,with its integrated molding and design freedom,is a powerful catalyst for distributed manufacturing.This paper investigates the integrated production and transportation scheduling problem in distributed 3D printing.To solve this problem,we decompose the original problem into three sub-problems and design a multilevel optimization algorithm.We employ a genetic algorithm in the outer-level optimization to determine the optimal allocation of parts to machines.In the inner-level optimization,we utilize a simulated annealing algorithm to tackle the vehicle routing problem during the transportation stage followed by a local search algorithm to address the scheduling problem encountered during the production stage.Our algorithm is validated using real data from a 3D printing company,and the results show that our algorithm can obtain solutions that are the same as or better than those of Gurobi in a reasonable time for small-sized instances.Additionally,three types of initial methods are tested on large-sized instances to verify the efficiency of the proposed algorithm,and some interesting insights are also revealed and discussed.
文摘Reconfiguration,as well as optimal utilization of distributed generation sources and capacitor banks,are highly effective methods for reducing losses and improving the voltage profile,or in other words,the power quality in the power distribution system.Researchers have considered the use of distributed generation resources in recent years.There are numerous advantages to utilizing these resources,the most significant of which are the reduction of network losses and enhancement of voltage stability.Non-dominated Sorting Genetic Algorithm II(NSGA-II),Multi-Objective Particle Swarm Optimization(MOPSO),and Intersect Mutation Differential Evolution(IMDE)algorithms are used in this paper to perform optimal reconfiguration,simultaneous location,and capacity determination of distributed generation resources and capacitor banks.Three scenarios were used to replicate the studies.The reconfiguration of the switches,as well as the location and determination of the capacitor bank’s optimal capacity,were investigated in this scenario.However,in the third scenario,reconfiguration,and determining the location and capacity of the Distributed Generation(DG)resources and capacitor banks have been carried out simultaneously.Finally,the simulation results of these three algorithms are compared.The results indicate that the proposed NSGAII algorithm outperformed the other two multi-objective algorithms and was capable of maintaining smaller objective functions in all scenarios.Specifically,the energy losses were reduced from 211 to 51.35 kW(a 75.66%reduction),119.13 kW(a 43.54%reduction),and 23.13 kW(an 89.04%reduction),while the voltage stability index(VSI)decreased from 6.96 to 2.105,1.239,and 1.257,respectively,demonstrating significant improvement in the voltage profile.
文摘In today’s complex and rapidly changing business environment,the traditional single-organization service model can no longer meet the needs of multi-organization collaborative processing.Based on existing business process engine technologies,this paper proposes a distributed heterogeneous process engine collaboration method for crossorganizational scenarios.The core of this method lies in achieving unified access and management of heterogeneous engines through a business process model adapter and a common operation interface.The key technologies include:Meta-Process Control Architecture,where the central engine(meta-process scheduler)decomposes the original process into fine-grained sub-processes and schedules their execution in a unified order,ensuring consistency with the original process logic;Process Model Adapter,which addresses the BPMN2.0 model differences among heterogeneous engines such as Flowable and Activiti through a matching-and-replacement mechanism,providing a unified process model standard for different engines;Common Operation Interface,which encapsulates the REST APIs of heterogeneous engines and offers a single,standardized interface for process deployment,instance management,and status synchronization.This method integrates multiple techniques to address API differences,process model incompatibilities,and execution order consistency issues among heterogeneous engines,delivering a unified,flexible,and scalable solution for cross-organizational process collaboration.
基金supported by the State Grid Corporation of China Headquarters Science and Technology Project“Research on Key Technologies for Power System Source-Load Forecasting and Regulation Capacity Assessment Oriented towards Major Weather Processes”(4000-202355381A-2-3-XG).
文摘Photovoltaic(PV)power generation is undergoing significant growth and serves as a key driver of the global energy transition.However,its intermittent nature,which fluctuates with weather conditions,has raised concerns about grid stability.Accurate PV power prediction has been demonstrated as crucial for power system operation and scheduling,enabling power slope control,fluctuation mitigation,grid stability enhancement,and reliable data support for secure grid operation.However,existing prediction models primarily target centralized PV plants,largely neglecting the spatiotemporal coupling dynamics and output uncertainties inherent to distributed PV systems.This study proposes a novel Spatio-Temporal Graph Neural Network(STGNN)architecture for distributed PV power generation prediction,designed to enhance distributed photovoltaic(PV)power generation forecasting accuracy and support regional grid scheduling.This approach models each PV power plant as a node in an undirected graph,with edges representing correlations between plants to capture spatial dependencies.The model comprises multiple Sparse Attention-based Adaptive Spatio-Temporal(SAAST)blocks.The SAAST blocks include sparse temporal attention,sparse spatial attention,an adaptive Graph Convolutional Network(GCN),and a temporal convolution network(TCN).These components eliminate weak temporal and spatial correlations,better represent dynamic spatial dependencies,and further enhance prediction accuracy.Finally,multi-dimensional comparative experiments between the STGNN and other models on the DKASC PV dataset demonstrate its superior performance in terms of accuracy and goodness-of-fit for distributed PV power generation prediction.
基金National Natural Science Foundation of China,Grant/Award Number:42130706。
文摘Coal mining induces changes in the nature of rock and soil bodies,as well as hydrogeological conditions,which can easily trigger the occurrence of geological disasters such as water inrush,movement of the coal seam roof and floor,and rock burst.Transparency in coal mine geological conditions provides technical support for intelligent coal mining and geological disaster prevention.In this sense,it is of great significance to address the requirements for informatizing coal mine geological conditions,dynamically adjust sensing parameters,and accurately identify disaster characteristics so as to prevent and control coal mine geological disasters.This paper examines the various action fields associated with geological disasters in mining faces and scrutinizes the types and sensing parameters of geological disasters resulting from coal seam mining.On this basis,it summarizes a distributed fiber-optic sensing technology framework for transparent geology in coal mines.Combined with the multi-field monitoring characteristics of the strain field,the temperature field,and the vibration field of distributed optical fiber sensing technology,parameters such as the strain increment ratio,the aquifer temperature gradient,and the acoustic wave amplitude are extracted as eigenvalues for identifying rock breaking,aquifer water level,and water cut range,and a multi-field sensing method is established for identifying the characteristics of mining-induced rock mass disasters.The development direction of transparent geology based on optical fiber sensing technology is proposed in terms of the aspects of sensing optical fiber structure for large deformation monitoring,identification accuracy of optical fiber acoustic signals,multi-parameter monitoring,and early warning methods.
基金the funding support from the Taihang Laboratory,China(No.D2024-1-0201).
文摘As the environmental problems become increasingly serious,distributed electrical propulsion systems with higher aerodynamic efficiency and lower pollution emission have received extensive attention in recent years.The distributed electrical propulsion usually employs the new aero-propulsion integrated configuration.A simulation strategy for internal and external flow coupling based on the combination of lifting line theory and body force method is proposed.The lifting line theory and body force method as source term are embedded into the Navier-Stokes formulation.The lift and drag characteristics of the aero-propulsion coupling configuration are simulated.The results indicate that the coupling configuration has the most obvious lift augmentation at 12°angle of attack,which can provide an 11.11%increase in lift for the airfoil.At 0°angle of attack,the pressure difference on the lip parts provides the thrust component,which results in a lower drag coefficient.Additionally,the failure impact of a ducted fan at the middle or edge on aerodynamics is investigated.For the two failure conditions,the lift of the coupling configuration is decreased significantly by 27.85%and 26.14%respectively,and the lip thrust is decreased by 70.74%and 56.48%respectively.
