In this article,by employing the Hirota bilinear approach and the long wave limit method,we not only derive soliton solutions,lump solutions,and hybrid solutions for the(2+1)-dimensional Yu-Toda-Sasa-Fukuyama(YTSF)equ...In this article,by employing the Hirota bilinear approach and the long wave limit method,we not only derive soliton solutions,lump solutions,and hybrid solutions for the(2+1)-dimensional Yu-Toda-Sasa-Fukuyama(YTSF)equation,but also analyze the dynamical behaviors of nonlinear local wave propagation in shallow water.Firstly,based on the Hirota bilinear approach,one to four-order soliton solutions of the YTSF equation are obtained,and the effects of different parameters on the amplitude,propagation trajectory,and displacement of solitons are investigated.Secondly,using the long wave limit approach,one to three-order lump solutions and various physical quantities of the YTSF equation are derived.It is found that the real and imaginary parts of the parameter pi dominate the propagation trajectory and the shape of lump waves,respectively.Furthermore,we construct the hybrid solution for the YTSF equation,leading to the conclusion that the interaction between lumps and solitons constitutes an elastic collision.To intuitively understand the dynamic behaviors of these solutions,we conduct numerical simulations to present vivid three-dimensional visualizations.展开更多
Railway noise barriers are an essential piece of infrastructure for reducing noise propagation.However,these barriers experience aerodynamic loads generated by high-speed trains,leading to dynamic effects that may com...Railway noise barriers are an essential piece of infrastructure for reducing noise propagation.However,these barriers experience aerodynamic loads generated by high-speed trains,leading to dynamic effects that may compromise their fatigue capacity.The most common structural design for railway noise barriers consists of vertical configurations of posts and panels.However,there have been few dynamic analyses of steel post/wood panel noise barriers under train-induced aerodynamic loads.This study used dynamic finite element analysis to assess the dynamic behavior of such noise barriers.Analysis of a 40-m-long noise barrier model and a triangular simplified load model,the latter of which effectively represented the detailed aerodynamic load,were first used to establish the model and input of the moving load during dynamic simulation.Then,the effects of different parameters on the dynamic response of the noise barrier were evaluated,including the damping ratio,the profile of the steel post,the span length of the panel,the barrier height,and the train speed.Gray relational analysis indicated that barrier height exhibited the highest correlations with the dynamic responses,followed by train speed,post profile,span length,and damping ratio.A reduction in the natural frequency and an increase in the train speed result in a higher peak response and more pronounced fluctuations between the nose and tail waves.The dynamic amplification factor(DAF)was found to be related to both the natural frequency and train speed.A model was proposed showing that the DAF significantly increases as the square of the natural frequency decreases and the cube of the train speed rises.展开更多
Federated Learning(FL)provides an effective framework for efficient processing in vehicular edge computing.However,the dynamic and uncertain communication environment,along with the performance variations of vehicular...Federated Learning(FL)provides an effective framework for efficient processing in vehicular edge computing.However,the dynamic and uncertain communication environment,along with the performance variations of vehicular devices,affect the distribution and uploading processes of model parameters.In FL-assisted Internet of Vehicles(IoV)scenarios,challenges such as data heterogeneity,limited device resources,and unstable communication environments become increasingly prominent.These issues necessitate intelligent vehicle selection schemes to enhance training efficiency.Given this context,we propose a new scenario involving FL-assisted IoV systems under dynamic and uncertain communication conditions,and develop a dynamic interval multi-objective optimization algorithm to jointly optimize various factors including training experiments,system energy consumption,and bandwidth utilization to meet multi-criteria resource optimization requirements.For the problem at hand,we design a dynamic interval multi-objective optimization algorithm based on interval overlap detection.Simulation results demonstrate that our method outperforms other solutions in terms of accuracy,training cost,and server utilization.It effectively enhances training efficiency under wireless channel environments while rationally utilizing bandwidth resources,thus possessing significant scientific value and application potential in the field of IoV.展开更多
In multi-modal emotion recognition,excessive reliance on historical context often impedes the detection of emotional shifts,while modality heterogeneity and unimodal noise limit recognition performance.Existing method...In multi-modal emotion recognition,excessive reliance on historical context often impedes the detection of emotional shifts,while modality heterogeneity and unimodal noise limit recognition performance.Existing methods struggle to dynamically adjust cross-modal complementary strength to optimize fusion quality and lack effective mechanisms to model the dynamic evolution of emotions.To address these issues,we propose a multi-level dynamic gating and emotion transfer framework for multi-modal emotion recognition.A dynamic gating mechanism is applied across unimodal encoding,cross-modal alignment,and emotion transfer modeling,substantially improving noise robustness and feature alignment.First,we construct a unimodal encoder based on gated recurrent units and feature-selection gating to suppress intra-modal noise and enhance contextual representation.Second,we design a gated-attention crossmodal encoder that dynamically calibrates the complementary contributions of visual and audio modalities to the dominant textual features and eliminates redundant information.Finally,we introduce a gated enhanced emotion transfer module that explicitly models the temporal dependence of emotional evolution in dialogues via transfer gating and optimizes continuity modeling with a comparative learning loss.Experimental results demonstrate that the proposed method outperforms state-of-the-art models on the public MELD and IEMOCAP datasets.展开更多
With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper pro...With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper proposes an intelligent path planning framework based on grid map modeling.First,an improved Safe and Smooth A*(SSA*)algorithm is employed for global path planning.By incorporating obstacle expansion and cornerpoint optimization,the proposed SSA*enhances the safety and smoothness of the planned path.Then,a Partitioned Dynamic Window Approach(PDWA)is integrated for local planning,which is triggered when dynamic or sudden static obstacles appear,enabling real-time obstacle avoidance and path adjustment.A unified objective function is constructed,considering path length,safety,and smoothness comprehensively.Multiple simulation experiments are conducted on typical port grid maps.The results demonstrate that the improved SSA*significantly reduces the number of expanded nodes and computation time in static environmentswhile generating smoother and safer paths.Meanwhile,the PDWA exhibits strong real-time performance and robustness in dynamic scenarios,achieving shorter paths and lower planning times compared to other graph search algorithms.The proposedmethodmaintains stable performance across maps of different scales and various port scenarios,verifying its practicality and potential for wider application.展开更多
To address the key scientific challenge of monitoring the dynamic fracturing of surrounding rock in deep roadways,this study systematically investigates the quantitative relationship between stress and charge signals ...To address the key scientific challenge of monitoring the dynamic fracturing of surrounding rock in deep roadways,this study systematically investigates the quantitative relationship between stress and charge signals during coal mass loading.By integrating innovative analytical approaches,introducing quantitative evaluation indices,and developing a charge–stress inversion model,and incorporating underground monitoring practices,significant progress has been achieved in elucidating the correlation between stress variations and charge signals throughout the entire coal mass fracturing process.First,in the field of stress–charge correlation analysis,empirical mode decomposition(EMD)was combined with wavelet coherence analysis for the first time,enabling the removal of slow-varying stress trends while retaining high-frequency fluctuations.This approach allowed for the quantitative characterization of the evolution of coherence between stress variations and charge fluctuations across multiple time scales.Second,coherence skewness and the proportion of high-coherence intervals were innovatively introduced to examine the influence of time scale selection on correlation results.On this basis,a criterion for determining the near-optimal observation scale of charge signals was proposed,providing a quantitative reference for time scale selection in similar signal analyses.Finally,by correlating charge signals with coal damage factors and stress states,a charge-based damage evolution equation was established to achieve effective stress inversion.Combined with in situ monitoring of stress and charge in roadway surrounding rock,this approach revealed the correlation characteristics of stress and charge intensity responses during the dynamic fracturing process.The results indicate,first,that charge signals are not significantly correlated with the absolute stress level of coal but are directly associated with stress variations following coal damage and failure,with the amplitude of charge fluctuations increasing alongside stress fluctuations.Second,coherence between stress and charge signals varies markedly across time scales,with excessively small or large scales leading to distortion,and the scale corresponding to the peak proportion of intervals with coherence>0.8 was identified as the near-optimal observation scale.Third,charge signals can effectively characterize coal damage factors,and the established damage evolution equation can effectively invert stress variation trends.Fourth,in underground roadways,zones of dynamic fracturing in surrounding rock are commonly located in areas where stress concentration overlaps with regions of high charge intensity,further confirming the strong consistency between charge and stress variations.These findings improve the theoretical framework of charge signal responses in loaded coal and provide a scientific basis for precise“stress-charge”monitoring of dynamic disasters,offering practical potential for engineering applications.展开更多
Reinforced concrete(RC)columns are often subjected to off-central explosion due to the uncertainty of blast locations.However,few studies have focused on the dynamic response of RC columns under offcentral explosions....Reinforced concrete(RC)columns are often subjected to off-central explosion due to the uncertainty of blast locations.However,few studies have focused on the dynamic response of RC columns under offcentral explosions.A field blast experiment was conducted under close-in explosion with varying detonation offset distances(0 m,0.5 m,and 1 m),the overpressure load and dynamic responses of the full-scale RC columns were measured.Compared with the centrally detonated condition,a relative offset distance of 1.67 decreases the maximum and residual deflections of the RC column by 16.8%and 21.4%,respectively,while increasing the maximum and residual support rotations by 24.7%and 17.8%.Based on the experimental results,a theoretical model was proposed that considers the detonation location and charge mass,boundary conditions,axial compression ratio and material properties.The theoretical model exhibited good agreement with the experimental results,with prediction errors below 10%for both maximum and residual deflection.The effects of parameters were analyzed,and it indicated that an increase in offset distance results in decreased maximum and residual deflections but an increased support angle,thereby exacerbating damage.Higher axial load ratio,span-depth ratio,and longitudinal reinforcement ratio reduce both deflections and support angle.Additionally,a rapid method to predict the maximum and residual deflection of RC columns under off-central blast loading was also proposed based on the Generalized Regression Neural Network(GRNN).Eleven features which related to the RC column properties and the blast characteristics were used in the training process of GRNN,and accurate predictions were achieved with prediction errors within 20%.This study fills the gap in predicting the dynamic response of RC columns under off-central explosion,providing valuable references for blast-resistant design.展开更多
Blockchain offers a promising solution to the security challenges faced by the Internet of Vehicles(IoV).However,due to the dynamic connectivity of IoV,blockchain based on a single-chain structure or Directed Acyclic ...Blockchain offers a promising solution to the security challenges faced by the Internet of Vehicles(IoV).However,due to the dynamic connectivity of IoV,blockchain based on a single-chain structure or Directed Acyclic Graph(DAG)structure often suffer from performance limitations.The DAG lattice structure is a novel blockchain model in which each node maintains its own account chain,and only the node itself is allowed to update it.This feature makes the DAG lattice structure particularly suitable for addressing the challenges in dynamically connected IoV environment.In this paper,we propose a blockchain architecture based on the DAG lattice structure,specifically designed for dynamically connected IoV.In the proposed system,nodes must obtain authorization from a trusted authority before joining,forming a permissioned blockchain.Each node is assigned an individual account chain,allowing vehicles with limited storage capacity to participate in the blockchain by storing transactions only from nearby vehicles’account chains.Every transmitted message is treated as a transaction and added to the blockchain,enablingmore efficient data transmission in a dynamic network environment.Areputation-based incentivemechanism is introduced to encourage nodes to behave normally.Experimental results demonstrate that the proposed architecture achieves better performance compared with traditional single-chain and DAG-based approaches in terms of average transmission delay and storage cost.展开更多
Defining science and demarcating it from pseudoscience are longstanding core issues in the philosophy of science.Hilbert’s traditional axiomatic standards(consistency,completeness,independence)struggle with modern co...Defining science and demarcating it from pseudoscience are longstanding core issues in the philosophy of science.Hilbert’s traditional axiomatic standards(consistency,completeness,independence)struggle with modern complex systems,while existing demarcation criteria like replicability and Popper’s falsificationism have practical limitations.Analyzing incompatibilities in complex systems,this paper proposes a revised framework:modified Hilbert axiomatic standards(clearly defined concepts,logical consistency,unrefuted axioms)and dynamic demarcation criteria.Abandoning unattainable traditional requirements of completeness and independence,it emphasizes conceptual clarity,openness,and progressiveness,offering an operational,self-consistent basis for judging scientificity.展开更多
Recycling of waste rubber(WR)is crucial for the sustainable development of the rubber industry.The enhancement of interfacial interactions is the main strategy for waste polymer recycling.However,there is a lack of me...Recycling of waste rubber(WR)is crucial for the sustainable development of the rubber industry.The enhancement of interfacial interactions is the main strategy for waste polymer recycling.However,there is a lack of methods for enhancing the interfacial interactions for WR recycling because WR contains abundant inert C―H bonds.Herein,we designed thioctic acid inverse vulcanization copolymers to endow recycled WR with dynamic disulfide interfacial interactions,significantly improving the mechanical properties of recycled WR.These disulfide interfacial interactions among the recycled WR tend to exchange,which dramatically increases the fractocohesive length and prevents stress concentration near the crack tips.When recycled WR is subjected to external stress,the loads are redistributed across a broad region of adjacent regions instead of being concentrated on a limited length scale,which resists crack propagation.This work effectively recycled WR,providing a strategy for solvent-free reaction-derived inverse vulcanization copolymers to improve the toughness of WR recycling.展开更多
Keratitis is a common ophthalmic disease associated with a high risk of blindness.Although deep learning(DL) based on slit-lamp images has shown great promise for automatic keratitis diagnosis,data heterogeneity and p...Keratitis is a common ophthalmic disease associated with a high risk of blindness.Although deep learning(DL) based on slit-lamp images has shown great promise for automatic keratitis diagnosis,data heterogeneity and privacy constraints hinder data sharing,limiting model generalization across multiple medical centers.To address these challenges,we propose a similarity-guided dynamic adjustment federated learning algorithm for automated keratitis diagnosis(SDAFL_AKD).SDAFL_AKD introduces a similarity-based regularization term during local model updates to alleviate catastrophic forgetting and employs a performance-driven dynamic aggregation mechanism on the server-side to adaptively weight client contributions,thereby enhancing global model robustness under non-independent and identically distributed(Non-IID) conditions.The framework is evaluated on slit-lamp images collected from four independent data sources encompassing keratitis,normal cornea,and other cornea abnormalities,and compared with Fed Avg,model-contrastive federated learning(MOON),stochastic controlled averaging for federated learning(SCAFFOLD) and single-center baseline models.Experimental results demonstrate that SDAFL_AKD consistently outperforms conventional methods,achieving average accuracies of 97.95% on a balanced dataset and 86.05% on an imbalanced smart phone-acquired dataset.Ablation studies further confirm the synergistic benefits of the similarity(SIM) and dynamic aggregation(DA) modules in improving multi-category recognition and generalization.These findings indicate the effectiveness of SDAFL_AKD for keratitis diagnosis under data heterogeneous and privacy-constrained conditions,providing a scalable solution for collaborative ophthalmic image analysis across institutions.展开更多
In this study,the dynamic characteristics and microstructures of lacustrine soft clays were studied.Dynamic character tests were conducted on undisturbed,remolded,and saturated lacustrine soft clays,using a dynamic tr...In this study,the dynamic characteristics and microstructures of lacustrine soft clays were studied.Dynamic character tests were conducted on undisturbed,remolded,and saturated lacustrine soft clays,using a dynamic triaxial tester.A scanning electron microscope(SEM)was employed to assess the soil samples after dynamic testing.The results indicate that the dynamic characteristics of lacustrine soft clay were significantly affected by confining pressure and water content.A quantitative relationship was established among confining pressures,water content,and the dynamic shear modulus ratio.The dynamic characteristic parameters of undisturbed,remolded and saturated soil are obviously different,and the original structure can enhance the shear strength of soil.By comparing the results with those from other studies,we found that the dynamic characters of soft clays were considerably varied in different regions,and lacustrine soft clays had a larger dynamic shear modulus ratio and a smaller damping ratio when the dynamic shear strain was large.Using IPP software to process the microstructural images,we found that the soil was dominated by small pores and medium particles,and the roundness of pores and particles had an apparently positive correlation with the maximum diameter.Moreover,the pores and particles of the soil showed fractal characteristics and directionality,and the fractal dimensions and probability entropy were strongly correlated with the macrostructural parameters.Finally,we developed a prediction model for macrostructural and microstructural parameters.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
The water hammer problem is an important issue in the dynamics of liquid propulsion system.This paper aims to use the Lattice Boltzmann Method(LBM)with entropy limiter to study the water hammer problems in propellant ...The water hammer problem is an important issue in the dynamics of liquid propulsion system.This paper aims to use the Lattice Boltzmann Method(LBM)with entropy limiter to study the water hammer problems in propellant feedlines.The dynamic characteristics of valve-closing water hammer and filling water hammer are investigated by this method,and the sensitivity of filling water hammer is analyzed with a single factor sensitivity analysis with 8 factors and 9 levels and a multi-factor sensitivity analysis with L_(27)(3^(13))orthogonal experiment based on range method.It is found that the solving result of LBM with entropy limiter is basically in good agreement with finite volume method,and using the entropy limiter can eliminate numerical oscillations when solving valve-closing water hammer problems and solve the numerical"blow up"when solving filling water hammer problems.It can be seen that the dynamic characteristics of valve-closing water hammer are relatively simple,while there are many factors that affect the filling water hammer and the degree of these effects varies.The effects on the maximum water hammer pressure are relatively uniform,but those on the water hammer response time vary greatly through the skewness analysis.展开更多
With the recent increase in data volume and diversity,traditional text representation techniques are struggling to capture context,particularly in environments with sparse data.To address these challenges,this study p...With the recent increase in data volume and diversity,traditional text representation techniques are struggling to capture context,particularly in environments with sparse data.To address these challenges,this study proposes a new model,the Masked Joint Representation Model(MJRM).MJRM approximates the original hypothesis by leveraging multiple elements in a limited context.It dynamically adapts to changes in characteristics based on data distribution through three main components.First,masking-based representation learning,termed selective dynamic masking,integrates topic modeling and sentiment clustering to generate and train multiple instances across different data subsets,whose predictions are then aggregated with optimized weights.This design alleviates sparsity,suppresses noise,and preserves contextual structures.Second,regularization-based improvements are applied.Third,techniques for addressing sparse data are used to perform final inference.As a result,MJRM improves performance by up to 4%compared to existing AI techniques.In our experiments,we analyzed the contribution of each factor,demonstrating that masking,dynamic learning,and aggregating multiple instances complement each other to improve performance.This demonstrates that a masking-based multi-learning strategy is effective for context-aware sparse text classification,and can be useful even in challenging situations such as data shortage or data distribution variations.We expect that the approach can be extended to diverse fields such as sentiment analysis,spam filtering,and domain-specific document classification.展开更多
In the future power-electronics-dominated power systems,grid-forming(GFM)converters have been regarded as important devices to actively establish frequency and voltage,so as to provide essential grid support.However,d...In the future power-electronics-dominated power systems,grid-forming(GFM)converters have been regarded as important devices to actively establish frequency and voltage,so as to provide essential grid support.However,due to their voltage source behavior and emulated swing dynamics,GFM converters may encounter low-frequency oscillations(LFOs)when connected to strong grids,which belongs to the self-stability problem of GFM converters.Moreover,GFM converters will also interact with grid-following(GFL)converters and thus impact the mid-frequency oscillations(MFOs)induced by phase-locked loops(PLLs).It has been preliminarily shown in the literature that GFM converters can help stabilize the PLL-induced MFOs,but currently,there is a lack of systematic design methods to coordinate the self-stability and stabilizing ability of GFM converters.This paper addresses this gap by revisiting the impedance model of a typical GFM converter and briefly analyze the oscillations caused by converters.Based on our analysis,we propose a frequency-partitioned synthesis design framework to enable dynamic virtual impedance(DVI)in GFM converters,aiming to enhance their self-stability and stabilizing ability simultaneously.Particularly,a self-stabilizing module is designed to ensure robust device-level damping,with control parameters auto-tuned using H∞methods.In parallel,a stabilizing module is introduced to stabilize GFL converters and enhance the system-level stability,which utilizes a perceive-and-optimize tuning strategy.Simulation results validate the effectiveness of the proposed synthesis DVI framework.展开更多
Due to the centralization of charging stations(CSs),CSs are organized as charging station alliances(CSAs)in the commercial competition.Under this situation,this paper studies the profit-oriented dynamic pricing strate...Due to the centralization of charging stations(CSs),CSs are organized as charging station alliances(CSAs)in the commercial competition.Under this situation,this paper studies the profit-oriented dynamic pricing strategy of CSAs.As the practicability basis,a privacy-protected bidirectional real-time information interaction framework is designed,under which the status of EVs is utilized as the reference for pricing,and the prices of CSs are the reference for charging decisions.Based on this framework,the decision-making models of EVs and CSs are established,in which the uncertainty caused by the information asymmetry between EVs and CSs and the bounded rationality of EV users are integrated.To solve the pricing decision model,the evolutionary game theory is adopted to describe the dynamic pricing game among CSAs,the equilibrium of which gives the optimal pricing strategy.Finally,the case study conducted in an urban area of Shanghai,China,validates the practicability of the framework and the effectiveness of the dynamic pricing strategy.展开更多
As vital hydraulic infrastructures,concrete dams demand uncompromising safety assurance.Seismic effect commonly serves as a potential factor contributing to the damage of concrete dams,making seismic performance analy...As vital hydraulic infrastructures,concrete dams demand uncompromising safety assurance.Seismic effect commonly serves as a potential factor contributing to the damage of concrete dams,making seismic performance analysis crucial for structural integrity.Numerical simulation based on damage mechanics is usually considered as the approach for investigating the seismic damage behavior of concrete dams.To address the limitations of existing studies and extract the key dynamic characteristics of concrete arch dams,a concrete elastoplastic damage mechanics model is adopted,a seismic load input technique involving the viscoelastic boundary along with equivalent nodal forces is generated,and a spring-contact pair simulation technique formodeling the transverse joints of arch dams is developed.The damage process of an arch dam under the classic Koyna seismic load is simulated,with the damage evolution process under seismic action being characterized.The middle sections of the arch dam near the upper portion are considered regions prone to damage under seismic action.Furthermore,the nonlinear dynamic characteristics caused by the opening and closing collision between transverse joints of the arch damunder strong seismic action are extracted.The extracted dynamic characteristic provides a manifestation for the dynamic damage diagnosis of arch dams based on seismic responses.展开更多
Probiotics can regulate gut microbes to maintain human health.However,the sensitivity of probiotics to environmental conditions reduces their bioavailability.In contrast,the formation of probiotic biofilm provides a n...Probiotics can regulate gut microbes to maintain human health.However,the sensitivity of probiotics to environmental conditions reduces their bioavailability.In contrast,the formation of probiotic biofilm provides a natural physical barrier against external interference.Our previous study established a dynamic culture system of the biofilm-state Bifidobacterium adolescentis Gr19(B-DC-B.adolescentis Gr19),forming higher density and more structurally stable biofilms,which enhanced its potential probiotic properties in vivo.Thus,the protective effect and mechanism of B-DC-B.adolescentis Gr19 on lipopolysaccharide(LPS)-induced intestinal barrier dysfunction were investigated in this study.The results showed that B-DC-B.adolescentis Gr19 not only had high resistance and adhesion activity,but also improved the intestinal barrier by increasing goblet cells and promoting the expression of tight junction(TJ)-related proteins.Moreover,B-DC-B.adolescentis Gr19 effectively attenuated intestinal barrier injury in Caco-2 cells by improving intestinal permeability and integrity.Remarkably,B-DC-B.adolescentis Gr19 enhanced expression of TJ proteins,restored localization of cytoskeleton and reduced intestinal inflammation by suppressing the Ras homolog family member A/Rho-associated coiled-coil-forming kinases/nuclear factor kappa B/myosin light chain kinase/myosin light chain(RhoA/ROCK/NF-κB/MLCK/MLC)pathway.Therefore,B-DC-B.adolescentis Gr19 plays a key role in mitigating LPS-induced intestinal barrier dysfunction.Overall,the present study provides a theoretical basis for ameliorating intestinal barrier dysfunction and developing novel functional foods by using biofilm-state probiotics under dynamic culture.展开更多
During the hoisting process of the offshore substation,changes in the hoisting speed can affect the hoisting system.Therefore,this study set four different speed conditions for the lifting and lowering stages of the i...During the hoisting process of the offshore substation,changes in the hoisting speed can affect the hoisting system.Therefore,this study set four different speed conditions for the lifting and lowering stages of the installation process,and studied the impact of different lifting and lowering speeds on the hoisting system under the same environmental conditions through numerical simulation.The results show that during the lifting operation,as the lifting speed increases,the swing motion of the substation and the installation vessel tends to decrease,and the faster the hoisting speed,the more obvious the swing suppression of the substation and the installation vessel,and the smaller the fluctuation in the tension amplitude of the slings and mooring lines.In contrast,during the lowering operation,as the lowering speed increases,the swing motion of the substation and the installation vessel tends to increase,and the faster the lowering speed,the more obvious the swing amplification effect of the substation and the installation vessel.Therefore,during hoisting operations,increasing the lifting speed and reducing the lowering speed can mitigate the motion performance of the hoisting coupling system,reduce the tension amplitude variation of the sling and mooring,and ensure the smooth progress of the hoisting operation.展开更多
基金Supported by the National Natural Science Foundation of China(12001424,12271324)the Natural Science Basic research program of Shaanxi Province(2021JZ-21)+1 种基金the China Postdoctoral Science Foundation(2020M673332)Xi’an University,Xi’an Science and Technology Plan Wutongshu Technology Transfer Action Innovation Team(25WTZD07)。
文摘In this article,by employing the Hirota bilinear approach and the long wave limit method,we not only derive soliton solutions,lump solutions,and hybrid solutions for the(2+1)-dimensional Yu-Toda-Sasa-Fukuyama(YTSF)equation,but also analyze the dynamical behaviors of nonlinear local wave propagation in shallow water.Firstly,based on the Hirota bilinear approach,one to four-order soliton solutions of the YTSF equation are obtained,and the effects of different parameters on the amplitude,propagation trajectory,and displacement of solitons are investigated.Secondly,using the long wave limit approach,one to three-order lump solutions and various physical quantities of the YTSF equation are derived.It is found that the real and imaginary parts of the parameter pi dominate the propagation trajectory and the shape of lump waves,respectively.Furthermore,we construct the hybrid solution for the YTSF equation,leading to the conclusion that the interaction between lumps and solitons constitutes an elastic collision.To intuitively understand the dynamic behaviors of these solutions,we conduct numerical simulations to present vivid three-dimensional visualizations.
基金financially supported by the Swedish Transport Administration(Trafikverket)through the“Excellence Area 4”and FOI-BBT program(Grant Nos.BBT-2019-022 and BBT-TRV 2024/132497).
文摘Railway noise barriers are an essential piece of infrastructure for reducing noise propagation.However,these barriers experience aerodynamic loads generated by high-speed trains,leading to dynamic effects that may compromise their fatigue capacity.The most common structural design for railway noise barriers consists of vertical configurations of posts and panels.However,there have been few dynamic analyses of steel post/wood panel noise barriers under train-induced aerodynamic loads.This study used dynamic finite element analysis to assess the dynamic behavior of such noise barriers.Analysis of a 40-m-long noise barrier model and a triangular simplified load model,the latter of which effectively represented the detailed aerodynamic load,were first used to establish the model and input of the moving load during dynamic simulation.Then,the effects of different parameters on the dynamic response of the noise barrier were evaluated,including the damping ratio,the profile of the steel post,the span length of the panel,the barrier height,and the train speed.Gray relational analysis indicated that barrier height exhibited the highest correlations with the dynamic responses,followed by train speed,post profile,span length,and damping ratio.A reduction in the natural frequency and an increase in the train speed result in a higher peak response and more pronounced fluctuations between the nose and tail waves.The dynamic amplification factor(DAF)was found to be related to both the natural frequency and train speed.A model was proposed showing that the DAF significantly increases as the square of the natural frequency decreases and the cube of the train speed rises.
基金supported in part by the Central Guidance for Local Science and Technology Development Funds under Grant No.YDZJSX2025D049Shanxi Provincial Graduate Innovation Research Program under Grant No.2024KY652.
文摘Federated Learning(FL)provides an effective framework for efficient processing in vehicular edge computing.However,the dynamic and uncertain communication environment,along with the performance variations of vehicular devices,affect the distribution and uploading processes of model parameters.In FL-assisted Internet of Vehicles(IoV)scenarios,challenges such as data heterogeneity,limited device resources,and unstable communication environments become increasingly prominent.These issues necessitate intelligent vehicle selection schemes to enhance training efficiency.Given this context,we propose a new scenario involving FL-assisted IoV systems under dynamic and uncertain communication conditions,and develop a dynamic interval multi-objective optimization algorithm to jointly optimize various factors including training experiments,system energy consumption,and bandwidth utilization to meet multi-criteria resource optimization requirements.For the problem at hand,we design a dynamic interval multi-objective optimization algorithm based on interval overlap detection.Simulation results demonstrate that our method outperforms other solutions in terms of accuracy,training cost,and server utilization.It effectively enhances training efficiency under wireless channel environments while rationally utilizing bandwidth resources,thus possessing significant scientific value and application potential in the field of IoV.
基金funded by“the Fanying Special Program of the National Natural Science Foundation of China,grant number 62341307”“the Scientific research project of Jiangxi Provincial Department of Education,grant number GJJ200839”“theDoctoral startup fund of JiangxiUniversity of Technology,grant number 205200100402”.
文摘In multi-modal emotion recognition,excessive reliance on historical context often impedes the detection of emotional shifts,while modality heterogeneity and unimodal noise limit recognition performance.Existing methods struggle to dynamically adjust cross-modal complementary strength to optimize fusion quality and lack effective mechanisms to model the dynamic evolution of emotions.To address these issues,we propose a multi-level dynamic gating and emotion transfer framework for multi-modal emotion recognition.A dynamic gating mechanism is applied across unimodal encoding,cross-modal alignment,and emotion transfer modeling,substantially improving noise robustness and feature alignment.First,we construct a unimodal encoder based on gated recurrent units and feature-selection gating to suppress intra-modal noise and enhance contextual representation.Second,we design a gated-attention crossmodal encoder that dynamically calibrates the complementary contributions of visual and audio modalities to the dominant textual features and eliminates redundant information.Finally,we introduce a gated enhanced emotion transfer module that explicitly models the temporal dependence of emotional evolution in dialogues via transfer gating and optimizes continuity modeling with a comparative learning loss.Experimental results demonstrate that the proposed method outperforms state-of-the-art models on the public MELD and IEMOCAP datasets.
文摘With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper proposes an intelligent path planning framework based on grid map modeling.First,an improved Safe and Smooth A*(SSA*)algorithm is employed for global path planning.By incorporating obstacle expansion and cornerpoint optimization,the proposed SSA*enhances the safety and smoothness of the planned path.Then,a Partitioned Dynamic Window Approach(PDWA)is integrated for local planning,which is triggered when dynamic or sudden static obstacles appear,enabling real-time obstacle avoidance and path adjustment.A unified objective function is constructed,considering path length,safety,and smoothness comprehensively.Multiple simulation experiments are conducted on typical port grid maps.The results demonstrate that the improved SSA*significantly reduces the number of expanded nodes and computation time in static environmentswhile generating smoother and safer paths.Meanwhile,the PDWA exhibits strong real-time performance and robustness in dynamic scenarios,achieving shorter paths and lower planning times compared to other graph search algorithms.The proposedmethodmaintains stable performance across maps of different scales and various port scenarios,verifying its practicality and potential for wider application.
基金supported by the Research Fund of the National Natural Science Foundation of China(No.52374205)the Fundamental Research Project of the Educational Department of Liaoning Province(No.JYTMS20230793)the Research Fund of the State Key Laboratory of Coal Resources and Safe Mining,CUMT(No.YJY-XD-2024-A-016).
文摘To address the key scientific challenge of monitoring the dynamic fracturing of surrounding rock in deep roadways,this study systematically investigates the quantitative relationship between stress and charge signals during coal mass loading.By integrating innovative analytical approaches,introducing quantitative evaluation indices,and developing a charge–stress inversion model,and incorporating underground monitoring practices,significant progress has been achieved in elucidating the correlation between stress variations and charge signals throughout the entire coal mass fracturing process.First,in the field of stress–charge correlation analysis,empirical mode decomposition(EMD)was combined with wavelet coherence analysis for the first time,enabling the removal of slow-varying stress trends while retaining high-frequency fluctuations.This approach allowed for the quantitative characterization of the evolution of coherence between stress variations and charge fluctuations across multiple time scales.Second,coherence skewness and the proportion of high-coherence intervals were innovatively introduced to examine the influence of time scale selection on correlation results.On this basis,a criterion for determining the near-optimal observation scale of charge signals was proposed,providing a quantitative reference for time scale selection in similar signal analyses.Finally,by correlating charge signals with coal damage factors and stress states,a charge-based damage evolution equation was established to achieve effective stress inversion.Combined with in situ monitoring of stress and charge in roadway surrounding rock,this approach revealed the correlation characteristics of stress and charge intensity responses during the dynamic fracturing process.The results indicate,first,that charge signals are not significantly correlated with the absolute stress level of coal but are directly associated with stress variations following coal damage and failure,with the amplitude of charge fluctuations increasing alongside stress fluctuations.Second,coherence between stress and charge signals varies markedly across time scales,with excessively small or large scales leading to distortion,and the scale corresponding to the peak proportion of intervals with coherence>0.8 was identified as the near-optimal observation scale.Third,charge signals can effectively characterize coal damage factors,and the established damage evolution equation can effectively invert stress variation trends.Fourth,in underground roadways,zones of dynamic fracturing in surrounding rock are commonly located in areas where stress concentration overlaps with regions of high charge intensity,further confirming the strong consistency between charge and stress variations.These findings improve the theoretical framework of charge signal responses in loaded coal and provide a scientific basis for precise“stress-charge”monitoring of dynamic disasters,offering practical potential for engineering applications.
基金financially supported by the National Natural Science Foundation of China(Grants No.12472399)。
文摘Reinforced concrete(RC)columns are often subjected to off-central explosion due to the uncertainty of blast locations.However,few studies have focused on the dynamic response of RC columns under offcentral explosions.A field blast experiment was conducted under close-in explosion with varying detonation offset distances(0 m,0.5 m,and 1 m),the overpressure load and dynamic responses of the full-scale RC columns were measured.Compared with the centrally detonated condition,a relative offset distance of 1.67 decreases the maximum and residual deflections of the RC column by 16.8%and 21.4%,respectively,while increasing the maximum and residual support rotations by 24.7%and 17.8%.Based on the experimental results,a theoretical model was proposed that considers the detonation location and charge mass,boundary conditions,axial compression ratio and material properties.The theoretical model exhibited good agreement with the experimental results,with prediction errors below 10%for both maximum and residual deflection.The effects of parameters were analyzed,and it indicated that an increase in offset distance results in decreased maximum and residual deflections but an increased support angle,thereby exacerbating damage.Higher axial load ratio,span-depth ratio,and longitudinal reinforcement ratio reduce both deflections and support angle.Additionally,a rapid method to predict the maximum and residual deflection of RC columns under off-central blast loading was also proposed based on the Generalized Regression Neural Network(GRNN).Eleven features which related to the RC column properties and the blast characteristics were used in the training process of GRNN,and accurate predictions were achieved with prediction errors within 20%.This study fills the gap in predicting the dynamic response of RC columns under off-central explosion,providing valuable references for blast-resistant design.
基金funded in part by the Supported by Natural Science Foundation of Inner Mongolia Autonomous Region of China under Grants 2024QN06022 and 2023QN06008in part by the First-Class Discipline Research Special Project under Grant YLXKZX-NGD-015in part by the Inner Mongolia University of Technology Scientific Research Start-Up Project under Grant BS2024067.
文摘Blockchain offers a promising solution to the security challenges faced by the Internet of Vehicles(IoV).However,due to the dynamic connectivity of IoV,blockchain based on a single-chain structure or Directed Acyclic Graph(DAG)structure often suffer from performance limitations.The DAG lattice structure is a novel blockchain model in which each node maintains its own account chain,and only the node itself is allowed to update it.This feature makes the DAG lattice structure particularly suitable for addressing the challenges in dynamically connected IoV environment.In this paper,we propose a blockchain architecture based on the DAG lattice structure,specifically designed for dynamically connected IoV.In the proposed system,nodes must obtain authorization from a trusted authority before joining,forming a permissioned blockchain.Each node is assigned an individual account chain,allowing vehicles with limited storage capacity to participate in the blockchain by storing transactions only from nearby vehicles’account chains.Every transmitted message is treated as a transaction and added to the blockchain,enablingmore efficient data transmission in a dynamic network environment.Areputation-based incentivemechanism is introduced to encourage nodes to behave normally.Experimental results demonstrate that the proposed architecture achieves better performance compared with traditional single-chain and DAG-based approaches in terms of average transmission delay and storage cost.
基金supported by the start-up funding from Westlake University under Grant Number 041030150118 and the scientific research project of Westlake University“Theoretical Research and Demonstration Application of Complex Systems and Deep-Sea Technology(Phase I)”under Grant Number WU2025A006.
文摘Defining science and demarcating it from pseudoscience are longstanding core issues in the philosophy of science.Hilbert’s traditional axiomatic standards(consistency,completeness,independence)struggle with modern complex systems,while existing demarcation criteria like replicability and Popper’s falsificationism have practical limitations.Analyzing incompatibilities in complex systems,this paper proposes a revised framework:modified Hilbert axiomatic standards(clearly defined concepts,logical consistency,unrefuted axioms)and dynamic demarcation criteria.Abandoning unattainable traditional requirements of completeness and independence,it emphasizes conceptual clarity,openness,and progressiveness,offering an operational,self-consistent basis for judging scientificity.
基金financially supported by the National Natural Science Foundation of China(No.52363007)。
文摘Recycling of waste rubber(WR)is crucial for the sustainable development of the rubber industry.The enhancement of interfacial interactions is the main strategy for waste polymer recycling.However,there is a lack of methods for enhancing the interfacial interactions for WR recycling because WR contains abundant inert C―H bonds.Herein,we designed thioctic acid inverse vulcanization copolymers to endow recycled WR with dynamic disulfide interfacial interactions,significantly improving the mechanical properties of recycled WR.These disulfide interfacial interactions among the recycled WR tend to exchange,which dramatically increases the fractocohesive length and prevents stress concentration near the crack tips.When recycled WR is subjected to external stress,the loads are redistributed across a broad region of adjacent regions instead of being concentrated on a limited length scale,which resists crack propagation.This work effectively recycled WR,providing a strategy for solvent-free reaction-derived inverse vulcanization copolymers to improve the toughness of WR recycling.
基金Supported by the National Natural Science Foundation of China (No.62276210,82201148,62376215)the Key Research and Development Project of Shaanxi Province (No.2025CY-YBXM-044,2024GX-YBXM-137)+5 种基金the Ningbo Top Medical and Health Research Program (No.2023030716)the Natural Science Foundation of Ningbo (No.2023J390)Interdisciplinary Research Program of the School of Electronic Engineering,Xi’an University of Posts and Telecommunications (No.XKJC2501)the Open Fund of National Engineering Laboratory for Big Data System Computing Technology (No.SZU-BDSC-OF2024-16)the Key Research and Development Project of Xianyang (No.L2024-ZDYF-ZDYF-SF-0067)General Special Scientific Research Program of Shaanxi Provincial Department of Education (No.24JK0651)。
文摘Keratitis is a common ophthalmic disease associated with a high risk of blindness.Although deep learning(DL) based on slit-lamp images has shown great promise for automatic keratitis diagnosis,data heterogeneity and privacy constraints hinder data sharing,limiting model generalization across multiple medical centers.To address these challenges,we propose a similarity-guided dynamic adjustment federated learning algorithm for automated keratitis diagnosis(SDAFL_AKD).SDAFL_AKD introduces a similarity-based regularization term during local model updates to alleviate catastrophic forgetting and employs a performance-driven dynamic aggregation mechanism on the server-side to adaptively weight client contributions,thereby enhancing global model robustness under non-independent and identically distributed(Non-IID) conditions.The framework is evaluated on slit-lamp images collected from four independent data sources encompassing keratitis,normal cornea,and other cornea abnormalities,and compared with Fed Avg,model-contrastive federated learning(MOON),stochastic controlled averaging for federated learning(SCAFFOLD) and single-center baseline models.Experimental results demonstrate that SDAFL_AKD consistently outperforms conventional methods,achieving average accuracies of 97.95% on a balanced dataset and 86.05% on an imbalanced smart phone-acquired dataset.Ablation studies further confirm the synergistic benefits of the similarity(SIM) and dynamic aggregation(DA) modules in improving multi-category recognition and generalization.These findings indicate the effectiveness of SDAFL_AKD for keratitis diagnosis under data heterogeneous and privacy-constrained conditions,providing a scalable solution for collaborative ophthalmic image analysis across institutions.
基金National Natural Science Foundation of China under Grant No.52278340Natural Science Foundation of Hebei Province under Grant No.E2023202028。
文摘In this study,the dynamic characteristics and microstructures of lacustrine soft clays were studied.Dynamic character tests were conducted on undisturbed,remolded,and saturated lacustrine soft clays,using a dynamic triaxial tester.A scanning electron microscope(SEM)was employed to assess the soil samples after dynamic testing.The results indicate that the dynamic characteristics of lacustrine soft clay were significantly affected by confining pressure and water content.A quantitative relationship was established among confining pressures,water content,and the dynamic shear modulus ratio.The dynamic characteristic parameters of undisturbed,remolded and saturated soil are obviously different,and the original structure can enhance the shear strength of soil.By comparing the results with those from other studies,we found that the dynamic characters of soft clays were considerably varied in different regions,and lacustrine soft clays had a larger dynamic shear modulus ratio and a smaller damping ratio when the dynamic shear strain was large.Using IPP software to process the microstructural images,we found that the soil was dominated by small pores and medium particles,and the roundness of pores and particles had an apparently positive correlation with the maximum diameter.Moreover,the pores and particles of the soil showed fractal characteristics and directionality,and the fractal dimensions and probability entropy were strongly correlated with the macrostructural parameters.Finally,we developed a prediction model for macrostructural and microstructural parameters.
基金support from the Joint Funds of the National Natural Science Foundation of China(Grant No.U23A2060)the National Natural Science Foundation of China(Grant Nos.42177143 and 52474150).
文摘Drilling and blasting tunneling is a cyclic process in which tunnel rock undergoes repeated blast loading,affecting its dynamic characteristics,energy evolution,and damage progression.To explore the dynamic mechanical properties and damage mechanisms of carbonaceous slate under cyclic impact loads of varying intensities,cyclic dynamic tests are conducted using a triaxial split Hopkinson pressure bar.This study analyzes the stress-strain relationship,energy damage evolution,and macro-to-micro failure characteristics.The results show that peak stress and strain are significantly influenced by impact intensity and the number of impacts.The initial dynamic stress is positively correlated with the impact intensity,but with more impact,the dynamic stress decreases while the peak strain increases.Energy evolution follows a pattern of"slow growthfluctuating growthrapid growth,"with the crack initiation stress and its proportion decreasing.CT and SEM analyses reveal that as the impact intensity increases,failure becomes more chaotic,the fracture volume increases,and the fracture mode shifts from interlayer and intergranular to through-layer and trans-granular fractures.These findings provide an experimental basis for soft rock tunnel stability analysis.
基金supported by the Natural Science BasicResearch Program of Shaanxi,China(No.2021JC-14)。
文摘The water hammer problem is an important issue in the dynamics of liquid propulsion system.This paper aims to use the Lattice Boltzmann Method(LBM)with entropy limiter to study the water hammer problems in propellant feedlines.The dynamic characteristics of valve-closing water hammer and filling water hammer are investigated by this method,and the sensitivity of filling water hammer is analyzed with a single factor sensitivity analysis with 8 factors and 9 levels and a multi-factor sensitivity analysis with L_(27)(3^(13))orthogonal experiment based on range method.It is found that the solving result of LBM with entropy limiter is basically in good agreement with finite volume method,and using the entropy limiter can eliminate numerical oscillations when solving valve-closing water hammer problems and solve the numerical"blow up"when solving filling water hammer problems.It can be seen that the dynamic characteristics of valve-closing water hammer are relatively simple,while there are many factors that affect the filling water hammer and the degree of these effects varies.The effects on the maximum water hammer pressure are relatively uniform,but those on the water hammer response time vary greatly through the skewness analysis.
基金supported by the SungKyunKwan University and the BK21 FOUR(Graduate School Innovation)funded by the Ministry of Education(MOE,Korea)and National Research Foundation of Korea(NRF).
文摘With the recent increase in data volume and diversity,traditional text representation techniques are struggling to capture context,particularly in environments with sparse data.To address these challenges,this study proposes a new model,the Masked Joint Representation Model(MJRM).MJRM approximates the original hypothesis by leveraging multiple elements in a limited context.It dynamically adapts to changes in characteristics based on data distribution through three main components.First,masking-based representation learning,termed selective dynamic masking,integrates topic modeling and sentiment clustering to generate and train multiple instances across different data subsets,whose predictions are then aggregated with optimized weights.This design alleviates sparsity,suppresses noise,and preserves contextual structures.Second,regularization-based improvements are applied.Third,techniques for addressing sparse data are used to perform final inference.As a result,MJRM improves performance by up to 4%compared to existing AI techniques.In our experiments,we analyzed the contribution of each factor,demonstrating that masking,dynamic learning,and aggregating multiple instances complement each other to improve performance.This demonstrates that a masking-based multi-learning strategy is effective for context-aware sparse text classification,and can be useful even in challenging situations such as data shortage or data distribution variations.We expect that the approach can be extended to diverse fields such as sentiment analysis,spam filtering,and domain-specific document classification.
基金supported by National Natural Science Foundation of China(U24B6008,U22B6008)State Grid Zhejiang Electric Power Co.,Ltd.Science,and Technology Project(B311DS240015).
文摘In the future power-electronics-dominated power systems,grid-forming(GFM)converters have been regarded as important devices to actively establish frequency and voltage,so as to provide essential grid support.However,due to their voltage source behavior and emulated swing dynamics,GFM converters may encounter low-frequency oscillations(LFOs)when connected to strong grids,which belongs to the self-stability problem of GFM converters.Moreover,GFM converters will also interact with grid-following(GFL)converters and thus impact the mid-frequency oscillations(MFOs)induced by phase-locked loops(PLLs).It has been preliminarily shown in the literature that GFM converters can help stabilize the PLL-induced MFOs,but currently,there is a lack of systematic design methods to coordinate the self-stability and stabilizing ability of GFM converters.This paper addresses this gap by revisiting the impedance model of a typical GFM converter and briefly analyze the oscillations caused by converters.Based on our analysis,we propose a frequency-partitioned synthesis design framework to enable dynamic virtual impedance(DVI)in GFM converters,aiming to enhance their self-stability and stabilizing ability simultaneously.Particularly,a self-stabilizing module is designed to ensure robust device-level damping,with control parameters auto-tuned using H∞methods.In parallel,a stabilizing module is introduced to stabilize GFL converters and enhance the system-level stability,which utilizes a perceive-and-optimize tuning strategy.Simulation results validate the effectiveness of the proposed synthesis DVI framework.
基金sponsored in part by the National Natural Science Foundation of China(52167014)in part by the Science and Technology Commission of Shanghai Municipality(23XD1422000,23QB1400500).
文摘Due to the centralization of charging stations(CSs),CSs are organized as charging station alliances(CSAs)in the commercial competition.Under this situation,this paper studies the profit-oriented dynamic pricing strategy of CSAs.As the practicability basis,a privacy-protected bidirectional real-time information interaction framework is designed,under which the status of EVs is utilized as the reference for pricing,and the prices of CSs are the reference for charging decisions.Based on this framework,the decision-making models of EVs and CSs are established,in which the uncertainty caused by the information asymmetry between EVs and CSs and the bounded rationality of EV users are integrated.To solve the pricing decision model,the evolutionary game theory is adopted to describe the dynamic pricing game among CSAs,the equilibrium of which gives the optimal pricing strategy.Finally,the case study conducted in an urban area of Shanghai,China,validates the practicability of the framework and the effectiveness of the dynamic pricing strategy.
基金supported by the Fundamental Research Funds for the Central Universities(No.B250201286)the Jiangsu-Czech Bilateral Co-Funding R&D Project(No.BZ2023011)+2 种基金the Jiangsu School-Enterprise Cooperation R&D Project(No.24880047-D01-001)the Anhui International Joint Research Center of Data Diagnosis and Smart Maintenance on Bridge Structures(No.2021AHGHZD03)the Key Research Project of Natural Science in Colleges and Universities of Anhui Province(No.2024AH051404).
文摘As vital hydraulic infrastructures,concrete dams demand uncompromising safety assurance.Seismic effect commonly serves as a potential factor contributing to the damage of concrete dams,making seismic performance analysis crucial for structural integrity.Numerical simulation based on damage mechanics is usually considered as the approach for investigating the seismic damage behavior of concrete dams.To address the limitations of existing studies and extract the key dynamic characteristics of concrete arch dams,a concrete elastoplastic damage mechanics model is adopted,a seismic load input technique involving the viscoelastic boundary along with equivalent nodal forces is generated,and a spring-contact pair simulation technique formodeling the transverse joints of arch dams is developed.The damage process of an arch dam under the classic Koyna seismic load is simulated,with the damage evolution process under seismic action being characterized.The middle sections of the arch dam near the upper portion are considered regions prone to damage under seismic action.Furthermore,the nonlinear dynamic characteristics caused by the opening and closing collision between transverse joints of the arch damunder strong seismic action are extracted.The extracted dynamic characteristic provides a manifestation for the dynamic damage diagnosis of arch dams based on seismic responses.
基金funded by Beijing Natural Science Foundation(6252001)Guangdong Basic and Applied Basic Research Foundation(2022A1515140021)Natural Science Foundation of China(31871772).
文摘Probiotics can regulate gut microbes to maintain human health.However,the sensitivity of probiotics to environmental conditions reduces their bioavailability.In contrast,the formation of probiotic biofilm provides a natural physical barrier against external interference.Our previous study established a dynamic culture system of the biofilm-state Bifidobacterium adolescentis Gr19(B-DC-B.adolescentis Gr19),forming higher density and more structurally stable biofilms,which enhanced its potential probiotic properties in vivo.Thus,the protective effect and mechanism of B-DC-B.adolescentis Gr19 on lipopolysaccharide(LPS)-induced intestinal barrier dysfunction were investigated in this study.The results showed that B-DC-B.adolescentis Gr19 not only had high resistance and adhesion activity,but also improved the intestinal barrier by increasing goblet cells and promoting the expression of tight junction(TJ)-related proteins.Moreover,B-DC-B.adolescentis Gr19 effectively attenuated intestinal barrier injury in Caco-2 cells by improving intestinal permeability and integrity.Remarkably,B-DC-B.adolescentis Gr19 enhanced expression of TJ proteins,restored localization of cytoskeleton and reduced intestinal inflammation by suppressing the Ras homolog family member A/Rho-associated coiled-coil-forming kinases/nuclear factor kappa B/myosin light chain kinase/myosin light chain(RhoA/ROCK/NF-κB/MLCK/MLC)pathway.Therefore,B-DC-B.adolescentis Gr19 plays a key role in mitigating LPS-induced intestinal barrier dysfunction.Overall,the present study provides a theoretical basis for ameliorating intestinal barrier dysfunction and developing novel functional foods by using biofilm-state probiotics under dynamic culture.
基金support from the National Natural Science Foundation of China(No.52271287)funding from the State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation,Tianjin University。
文摘During the hoisting process of the offshore substation,changes in the hoisting speed can affect the hoisting system.Therefore,this study set four different speed conditions for the lifting and lowering stages of the installation process,and studied the impact of different lifting and lowering speeds on the hoisting system under the same environmental conditions through numerical simulation.The results show that during the lifting operation,as the lifting speed increases,the swing motion of the substation and the installation vessel tends to decrease,and the faster the hoisting speed,the more obvious the swing suppression of the substation and the installation vessel,and the smaller the fluctuation in the tension amplitude of the slings and mooring lines.In contrast,during the lowering operation,as the lowering speed increases,the swing motion of the substation and the installation vessel tends to increase,and the faster the lowering speed,the more obvious the swing amplification effect of the substation and the installation vessel.Therefore,during hoisting operations,increasing the lifting speed and reducing the lowering speed can mitigate the motion performance of the hoisting coupling system,reduce the tension amplitude variation of the sling and mooring,and ensure the smooth progress of the hoisting operation.
