Three-dimensional (3D) visualization of dynamic biological processes in deep tissue remains challenging due to the trade-off between temporal resolution and imaging depth. Here, we present a novel near-infrared-II (NI...Three-dimensional (3D) visualization of dynamic biological processes in deep tissue remains challenging due to the trade-off between temporal resolution and imaging depth. Here, we present a novel near-infrared-II (NIR-II, 900–1880nm) fluorescence volumetric microscopic imaging method that combines an electrically tunable lens (ETL) with deep learning approaches for rapid 3D imaging. The technology achieves volumetric imaging at 4.2 frames per second (fps) across a 200 μm depth range in live mouse brain vasculature. Two specialized neural networks are utilized: a scale-recurrent network (SRN) for image enhancement and a cerebral vessel interpolation (CVI) network that enables 16-fold axial upsampling. The SRN, trained on two-photon fluorescence microscopic data, improves both lateral and axial resolution of NIR-II fluorescence wide-field microscopic images. The CVI network, adapted from video interpolation techniques, generates intermediate frames between acquired axial planes, resulting in smooth and continuous 3D vessel reconstructions. Using this integrated system, we visualize and quantify blood flow dynamics in individual vessels and are capable of measuring blood velocity at different depths. This approach maintains high lateral resolution while achieving rapid volumetric imaging, and is particularly suitable for studying dynamic vascular processes in deep tissue. Our method demonstrates the potential of combining optical engineering with artificial intelligence to advance biological imaging capabilities.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
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
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
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
As an emerging thermal management strategy,dynamic radiative cooling(DRC)technology enables dynamic modulation of spectral radiation properties under varying environmental conditions through the directional design of ...As an emerging thermal management strategy,dynamic radiative cooling(DRC)technology enables dynamic modulation of spectral radiation properties under varying environmental conditions through the directional design of material spectral characteristics.However,a comprehensive review of the basic physical mechanisms of radiative heat transfer in DRC materials and various design principles involved in dynamic radiative thermal regulation is still lacking.This review systematically summarizes recent advances in this field,spanning from fundamental physical principles to intrinsic molecular and electronic mechanisms,and further to representative material systems and multi-band regulation strategies,highlighting the interdisciplinary research achievements and technological innovations.This work outlines the core mechanisms governing the regulation of different spectral bands during radiative heat transfer processes.Then,the main categories of DRC materials are systematically reviewed,including actively responsive structures,passively responsive structures,and multi-stimuli-responsive materials.Furthermore,the challenges faced by current DRC technology and future development trends are summarized and discussed,providing valuable reference and guidance for further research in this field.Although DRC technologies still face significant challenges in material stability,manufacturing processes,and system integration,the continuous advances in related areas and multifunctional materials are expected to broaden the application prospects of DRC in the future.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
Rheumatoid arthritis(RA)patients face significant psychological challenges alongside physical symptoms,necessitating a comprehensive understanding of how psychological vulnerability and adaptation patterns evolve thro...Rheumatoid arthritis(RA)patients face significant psychological challenges alongside physical symptoms,necessitating a comprehensive understanding of how psychological vulnerability and adaptation patterns evolve throughout the disease course.This review examined 95 studies(2000-2025)from PubMed,Web of Science,and CNKI databases including longitudinal cohorts,randomized controlled trials,and mixed-methods research,to characterize the complex interplay between biological,psychological,and social factors affecting RA patients’mental health.Findings revealed three distinct vulnerability trajectories(45%persistently low,30%fluctuating improvement,25%persistently high)and four adaptation stages,with critical intervention periods occurring 3-6 months postdiagnosis and during disease flares.Multiple factors significantly influence psychological outcomes,including gender(females showing 1.8-fold increased risk),age(younger patients experiencing 42%higher vulnerability),pain intensity,inflammatory markers,and neuroendocrine dysregulation(48%showing cortisol rhythm disruption).Early psychological intervention(within 3 months of diagnosis)demonstrated robust benefits,reducing depression incidence by 42%with effects persisting 24-36 months,while different modalities showed complementary advantages:Cognitive behavioral therapy for depression(Cohen’s d=0.68),mindfulness for pain acceptance(38%improvement),and peer support for meaning reconstruction(25.6%increase).These findings underscore the importance of integrating routine psychological assessment into standard RA care,developing stage-appropriate interventions,and advancing research toward personalized biopsychosocial approaches that address the dynamic psychological dimensions of the disease.展开更多
Fault-tolerant systems are crucial for ensuring the reliability and availability of missioncritical applications in modern computing environments.The dynamic heterogeneous redundancy(DHR)architecture is a key componen...Fault-tolerant systems are crucial for ensuring the reliability and availability of missioncritical applications in modern computing environments.The dynamic heterogeneous redundancy(DHR)architecture is a key component in constructing fault-tolerant systems,particularly in areas such as national security,power networks,and banking private networks.DHR is transforming the cyberspace security industry chain by accommodating a broader range of applications and increasingly capturing the market.However,the development of applications for DHR architecture encounters challenges due to the complexities of handling heterogeneity,managing dynamism,and maintaining usability.To address these issues,we introduce MimicStudio,a comprehensive development framework with a standardized workflow.To our knowledge,MimicStudio is the first effective solution for DHR software development.We present a detailed implementation of MimicStudio with a heterogeneous microcontroller unit project,encompassing three CPUs with different instruction set architectures.The paper evaluates MimicStudio’s support for essential features,including zero-copy synchronization,parallelized build,multi-core collaborative debugging,and dynamic adjustment of the software system’s structure.Our results show that MimicStudio provides a flexible and efficient solution for supporting the dynamic,heterogeneous,and redundant features of fault-tolerant systems.展开更多
Pulsed dynamic electrolysis(PDE),driven by renewable energy,has emerged as an innovative electrocatalytic conversion method,demonstrating significant potential in addressing global energy challenges and promoting sust...Pulsed dynamic electrolysis(PDE),driven by renewable energy,has emerged as an innovative electrocatalytic conversion method,demonstrating significant potential in addressing global energy challenges and promoting sustainable development.Despite significant progress in various electrochemical systems,the regulatory mechanisms of PDE in energy and mass transfer and the lifespan extension of electrolysis systems,particularly in water electrolysis(WE)for hydrogen production,remain insufficiently explored.Therefore,there is an urgent need for a deeper understanding of the unique contributions of PDE in mass transfer enhancement,microenvironment regulation,and hydrogen production optimization,aiming to achieve low-energy consumption,high catalytic activity,and long-term stability in the generation of target products.Here,this review critically examines the microenvironmental effects of PDE on energy and mass transfer,the electrode degradation mechanisms in the lifespan extension of electrolysis systems,and the key factors in enhancing WE for hydrogen production,providing a comprehensive summary of current research progress.The review focuses on the complex regulatory mechanisms of frequency,duty cycle,amplitude,and other factors in hydrogen evolution reaction(HER)performance within PDE strategies,revealing the interrelationships among them.Finally,the potential future directions and challenges for transitioning from laboratory studies to industrial applications are proposed.展开更多
While biomaterials are endowed with sophisticated functions by the temporal dynamics and autonomy derived from non-equilibrium assemblies in biological systems,fabricating advanced materials counterparts with these fe...While biomaterials are endowed with sophisticated functions by the temporal dynamics and autonomy derived from non-equilibrium assemblies in biological systems,fabricating advanced materials counterparts with these features through kinetic control remains rare.Herein,we report a non-equilibrium hydrogel that exhibits autonomous time-dependent ultrabright fluorescence(quantum yield 0.90),achieved through the kinetically controlled incorporation of thermodynamic equilibrium host-vip complexes into a poly(2-hydroxyethyl methacrylate)(PHEMA)network.Transient complexes are programmed by coupling rapid assembly kinetics with the slow competitive binding of the polymer matrix.This kinetic mismatch converts a thermodynamic equilibrium supramolecular system into a non-equilibrium state,generating temporally dynamic fluorescence that cyclically shifts from yellow to green and self-reverts.The programmed temporal dynamics endow the hydrogel with high potential for information encryption applications.展开更多
End-to-end Temporal Action Detection(TAD)has achieved remarkable progress in recent years,driven by innovations in model architectures and the emergence of Video Foundation Models(VFMs).However,existing TAD methods th...End-to-end Temporal Action Detection(TAD)has achieved remarkable progress in recent years,driven by innovations in model architectures and the emergence of Video Foundation Models(VFMs).However,existing TAD methods that perform full fine-tuning of pretrained video models often incur substantial computational costs,which become particularly pronounced when processing long video sequences.Moreover,the need for precise temporal boundary annotations makes data labeling extremely expensive.In low-resource settings where annotated samples are scarce,direct fine-tuning tends to cause overfitting.To address these challenges,we introduce Dynamic LowRank Adapter(DyLoRA),a lightweight fine-tuning framework tailored specifically for the TAD task.Built upon the Low-Rank Adaptation(LoRA)architecture,DyLoRA adapts only the key layers of the pretrained model via low-rank decomposition,reducing the number of trainable parameters to less than 5%of full fine-tuning methods.This significantly lowers memory consumption and mitigates overfitting in low-resource settings.Notably,DyLoRA enhances the temporal modeling capability of pretrained models by optimizing temporal dimension weights,thereby alleviating the representation misalignment of temporal features.Experimental results demonstrate that DyLoRA-TAD achieves impressive performance,with 73.9%mAP on THUMOS14,39.52%on ActivityNet-1.3,and 28.2%on Charades,substantially surpassing the best traditional feature-based methods.展开更多
Fissured rocks are prevalent in geotechnical engineering and can significantlyimpact the stability of engineering structures.Microbial-induced carbonate precipitation(MICP)technology provides an ecofriendly solution f...Fissured rocks are prevalent in geotechnical engineering and can significantlyimpact the stability of engineering structures.Microbial-induced carbonate precipitation(MICP)technology provides an ecofriendly solution for repairing fissuredrocks.To optimize repair effectiveness,this study firstinvestigated the effects of environmental factors on bacterial growth,urease activity,and calcium carbonate yield.The optimal MICP scheme was determined to be a pH of 9,a temperature of 25℃,and a cementation solution concentration of 0.5 mol/L.Subsequently,the sandstone specimens with various fissureapertures were repaired using MICP with different bacterial concentrations.Dynamic tests were carried out on the repaired specimens using a split Hopkinson pressure bar system.The experimental results indicate that the dynamic strength of the MICP-repaired specimens positively correlates with strain rate,but decreases with increasing bacterial concentration and fissureaperture.These factors have little effect on the progressive failure behavior.Surface cracks were mainly compression-shear cracks in the repair area and tensile-shear cracks at the end of the specimen.Moreover,the crystal morphology observed by scanning electron microscope indicates that MICP primarily produces vaterite crystals,and lower bacterial concentrations favor the formation of more stable calcite crystals,thereby enhancing the cementitious properties.Furthermore,X-ray computed tomography demonstrates an uneven distribution of calcium carbonate within fissures,with higher fillingrates observed at the injection end and at the bottom of the fissures.Lower bacterial concentrations and smaller fissureapertures are conducive to more uniform distribution and increased fillingrate of calcium carbonate,with fissureaperture exerting a more dominant influence.展开更多
With the increasing complexity of logistics operations,traditional static vehicle routing models are no longer sufficient.In practice,customer demands often arise dynamically,and multi-depot systems are commonly used ...With the increasing complexity of logistics operations,traditional static vehicle routing models are no longer sufficient.In practice,customer demands often arise dynamically,and multi-depot systems are commonly used to improve efficiency.This paper first introduces a vehicle routing problem with the goal of minimizing operating costs in a multi-depot environment with dynamic demand.New customers appear in the delivery process at any time and are periodically optimized according to time slices.Then,we propose a scheduling system TS-DPU based on an improved ant colony algorithm TS-ACO to solve this problem.The classical ant colony algorithm uses spatial distance to select nodes,while TS-ACO considers the impact of both temporal and spatial distance on node selection.Meanwhile,we adopt Cordeau’s Multi-Depot Vehicle Routing Problem with Time Windows(MDVRPTW)dataset to evaluate the performance of our system.According to the experimental results,TS-ACO,which considers spatial and temporal distance,is more effective than the classical ACO,which only considers spatial distance.展开更多
基金supported by the National Key R&D Program of China (No. 2024YFF1206700)the National Natural Science Foundation of China (No. U23A20487)the Hangzhou Chengxi Sci-tech Innovation Corridor Management Committee.
文摘Three-dimensional (3D) visualization of dynamic biological processes in deep tissue remains challenging due to the trade-off between temporal resolution and imaging depth. Here, we present a novel near-infrared-II (NIR-II, 900–1880nm) fluorescence volumetric microscopic imaging method that combines an electrically tunable lens (ETL) with deep learning approaches for rapid 3D imaging. The technology achieves volumetric imaging at 4.2 frames per second (fps) across a 200 μm depth range in live mouse brain vasculature. Two specialized neural networks are utilized: a scale-recurrent network (SRN) for image enhancement and a cerebral vessel interpolation (CVI) network that enables 16-fold axial upsampling. The SRN, trained on two-photon fluorescence microscopic data, improves both lateral and axial resolution of NIR-II fluorescence wide-field microscopic images. The CVI network, adapted from video interpolation techniques, generates intermediate frames between acquired axial planes, resulting in smooth and continuous 3D vessel reconstructions. Using this integrated system, we visualize and quantify blood flow dynamics in individual vessels and are capable of measuring blood velocity at different depths. This approach maintains high lateral resolution while achieving rapid volumetric imaging, and is particularly suitable for studying dynamic vascular processes in deep tissue. Our method demonstrates the potential of combining optical engineering with artificial intelligence to advance biological imaging capabilities.
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 the Taishan Scholars of Shandong Province(tsqn202408151)the National Natural Science Foundation of China(Grant Nos.52476067,52306078,and 52576053).
文摘As an emerging thermal management strategy,dynamic radiative cooling(DRC)technology enables dynamic modulation of spectral radiation properties under varying environmental conditions through the directional design of material spectral characteristics.However,a comprehensive review of the basic physical mechanisms of radiative heat transfer in DRC materials and various design principles involved in dynamic radiative thermal regulation is still lacking.This review systematically summarizes recent advances in this field,spanning from fundamental physical principles to intrinsic molecular and electronic mechanisms,and further to representative material systems and multi-band regulation strategies,highlighting the interdisciplinary research achievements and technological innovations.This work outlines the core mechanisms governing the regulation of different spectral bands during radiative heat transfer processes.Then,the main categories of DRC materials are systematically reviewed,including actively responsive structures,passively responsive structures,and multi-stimuli-responsive materials.Furthermore,the challenges faced by current DRC technology and future development trends are summarized and discussed,providing valuable reference and guidance for further research in this field.Although DRC technologies still face significant challenges in material stability,manufacturing processes,and system integration,the continuous advances in related areas and multifunctional materials are expected to broaden the application prospects of DRC in the future.
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.
基金Supported by Chongqing Health Commission and Chongqing Science and Technology Bureau,No.2023MSXM182。
文摘Rheumatoid arthritis(RA)patients face significant psychological challenges alongside physical symptoms,necessitating a comprehensive understanding of how psychological vulnerability and adaptation patterns evolve throughout the disease course.This review examined 95 studies(2000-2025)from PubMed,Web of Science,and CNKI databases including longitudinal cohorts,randomized controlled trials,and mixed-methods research,to characterize the complex interplay between biological,psychological,and social factors affecting RA patients’mental health.Findings revealed three distinct vulnerability trajectories(45%persistently low,30%fluctuating improvement,25%persistently high)and four adaptation stages,with critical intervention periods occurring 3-6 months postdiagnosis and during disease flares.Multiple factors significantly influence psychological outcomes,including gender(females showing 1.8-fold increased risk),age(younger patients experiencing 42%higher vulnerability),pain intensity,inflammatory markers,and neuroendocrine dysregulation(48%showing cortisol rhythm disruption).Early psychological intervention(within 3 months of diagnosis)demonstrated robust benefits,reducing depression incidence by 42%with effects persisting 24-36 months,while different modalities showed complementary advantages:Cognitive behavioral therapy for depression(Cohen’s d=0.68),mindfulness for pain acceptance(38%improvement),and peer support for meaning reconstruction(25.6%increase).These findings underscore the importance of integrating routine psychological assessment into standard RA care,developing stage-appropriate interventions,and advancing research toward personalized biopsychosocial approaches that address the dynamic psychological dimensions of the disease.
基金supported by National Key Research and Development Program of China(No.2023YFB 4404200).
文摘Fault-tolerant systems are crucial for ensuring the reliability and availability of missioncritical applications in modern computing environments.The dynamic heterogeneous redundancy(DHR)architecture is a key component in constructing fault-tolerant systems,particularly in areas such as national security,power networks,and banking private networks.DHR is transforming the cyberspace security industry chain by accommodating a broader range of applications and increasingly capturing the market.However,the development of applications for DHR architecture encounters challenges due to the complexities of handling heterogeneity,managing dynamism,and maintaining usability.To address these issues,we introduce MimicStudio,a comprehensive development framework with a standardized workflow.To our knowledge,MimicStudio is the first effective solution for DHR software development.We present a detailed implementation of MimicStudio with a heterogeneous microcontroller unit project,encompassing three CPUs with different instruction set architectures.The paper evaluates MimicStudio’s support for essential features,including zero-copy synchronization,parallelized build,multi-core collaborative debugging,and dynamic adjustment of the software system’s structure.Our results show that MimicStudio provides a flexible and efficient solution for supporting the dynamic,heterogeneous,and redundant features of fault-tolerant systems.
基金financially supported by the Key Research and Development Program of Heilongjiang Province(No.2024ZXJ03C06)National Natural Science Foundation of China(No.52476192,No.52106237)+1 种基金Natural Science Foundation of Heilongjiang Province(No.YQ2022E027)Technology Project of China Datang Technology Innovation Co.,Ltd(No.DTKC-2024-20610).
文摘Pulsed dynamic electrolysis(PDE),driven by renewable energy,has emerged as an innovative electrocatalytic conversion method,demonstrating significant potential in addressing global energy challenges and promoting sustainable development.Despite significant progress in various electrochemical systems,the regulatory mechanisms of PDE in energy and mass transfer and the lifespan extension of electrolysis systems,particularly in water electrolysis(WE)for hydrogen production,remain insufficiently explored.Therefore,there is an urgent need for a deeper understanding of the unique contributions of PDE in mass transfer enhancement,microenvironment regulation,and hydrogen production optimization,aiming to achieve low-energy consumption,high catalytic activity,and long-term stability in the generation of target products.Here,this review critically examines the microenvironmental effects of PDE on energy and mass transfer,the electrode degradation mechanisms in the lifespan extension of electrolysis systems,and the key factors in enhancing WE for hydrogen production,providing a comprehensive summary of current research progress.The review focuses on the complex regulatory mechanisms of frequency,duty cycle,amplitude,and other factors in hydrogen evolution reaction(HER)performance within PDE strategies,revealing the interrelationships among them.Finally,the potential future directions and challenges for transitioning from laboratory studies to industrial applications are proposed.
基金supported by the National Natural Science Foundation of China(22025503,22220102004,22401093)the Science and Technology Commission of Shanghai Municipality(24DX1400200)+2 种基金the Innovation Program of Shanghai Municipal Education Commission(2023ZKZD40)the Programme of Introducing Talents of Discipline to Universities(B16017)the China Postdoctoral Science Foundation(2023M741167,GZB20230211,2024T170273)。
文摘While biomaterials are endowed with sophisticated functions by the temporal dynamics and autonomy derived from non-equilibrium assemblies in biological systems,fabricating advanced materials counterparts with these features through kinetic control remains rare.Herein,we report a non-equilibrium hydrogel that exhibits autonomous time-dependent ultrabright fluorescence(quantum yield 0.90),achieved through the kinetically controlled incorporation of thermodynamic equilibrium host-vip complexes into a poly(2-hydroxyethyl methacrylate)(PHEMA)network.Transient complexes are programmed by coupling rapid assembly kinetics with the slow competitive binding of the polymer matrix.This kinetic mismatch converts a thermodynamic equilibrium supramolecular system into a non-equilibrium state,generating temporally dynamic fluorescence that cyclically shifts from yellow to green and self-reverts.The programmed temporal dynamics endow the hydrogel with high potential for information encryption applications.
基金supported by the National Natural Science Foundation of China(Grant No.62266054)the Major Science and Technology Project of Yunnan Province(Grant No.202402AD080002)the Scientific Research Fund of the Yunnan Provincial Department of Education(Grant No.2025Y0302).
文摘End-to-end Temporal Action Detection(TAD)has achieved remarkable progress in recent years,driven by innovations in model architectures and the emergence of Video Foundation Models(VFMs).However,existing TAD methods that perform full fine-tuning of pretrained video models often incur substantial computational costs,which become particularly pronounced when processing long video sequences.Moreover,the need for precise temporal boundary annotations makes data labeling extremely expensive.In low-resource settings where annotated samples are scarce,direct fine-tuning tends to cause overfitting.To address these challenges,we introduce Dynamic LowRank Adapter(DyLoRA),a lightweight fine-tuning framework tailored specifically for the TAD task.Built upon the Low-Rank Adaptation(LoRA)architecture,DyLoRA adapts only the key layers of the pretrained model via low-rank decomposition,reducing the number of trainable parameters to less than 5%of full fine-tuning methods.This significantly lowers memory consumption and mitigates overfitting in low-resource settings.Notably,DyLoRA enhances the temporal modeling capability of pretrained models by optimizing temporal dimension weights,thereby alleviating the representation misalignment of temporal features.Experimental results demonstrate that DyLoRA-TAD achieves impressive performance,with 73.9%mAP on THUMOS14,39.52%on ActivityNet-1.3,and 28.2%on Charades,substantially surpassing the best traditional feature-based methods.
基金support from the National Key R&D Program of China(Grant No.2023YFC3081500)the National Natural Science Foundation of China(Grant Nos.52225904 and 52039007).
文摘Fissured rocks are prevalent in geotechnical engineering and can significantlyimpact the stability of engineering structures.Microbial-induced carbonate precipitation(MICP)technology provides an ecofriendly solution for repairing fissuredrocks.To optimize repair effectiveness,this study firstinvestigated the effects of environmental factors on bacterial growth,urease activity,and calcium carbonate yield.The optimal MICP scheme was determined to be a pH of 9,a temperature of 25℃,and a cementation solution concentration of 0.5 mol/L.Subsequently,the sandstone specimens with various fissureapertures were repaired using MICP with different bacterial concentrations.Dynamic tests were carried out on the repaired specimens using a split Hopkinson pressure bar system.The experimental results indicate that the dynamic strength of the MICP-repaired specimens positively correlates with strain rate,but decreases with increasing bacterial concentration and fissureaperture.These factors have little effect on the progressive failure behavior.Surface cracks were mainly compression-shear cracks in the repair area and tensile-shear cracks at the end of the specimen.Moreover,the crystal morphology observed by scanning electron microscope indicates that MICP primarily produces vaterite crystals,and lower bacterial concentrations favor the formation of more stable calcite crystals,thereby enhancing the cementitious properties.Furthermore,X-ray computed tomography demonstrates an uneven distribution of calcium carbonate within fissures,with higher fillingrates observed at the injection end and at the bottom of the fissures.Lower bacterial concentrations and smaller fissureapertures are conducive to more uniform distribution and increased fillingrate of calcium carbonate,with fissureaperture exerting a more dominant influence.
基金supported by the Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology.
文摘With the increasing complexity of logistics operations,traditional static vehicle routing models are no longer sufficient.In practice,customer demands often arise dynamically,and multi-depot systems are commonly used to improve efficiency.This paper first introduces a vehicle routing problem with the goal of minimizing operating costs in a multi-depot environment with dynamic demand.New customers appear in the delivery process at any time and are periodically optimized according to time slices.Then,we propose a scheduling system TS-DPU based on an improved ant colony algorithm TS-ACO to solve this problem.The classical ant colony algorithm uses spatial distance to select nodes,while TS-ACO considers the impact of both temporal and spatial distance on node selection.Meanwhile,we adopt Cordeau’s Multi-Depot Vehicle Routing Problem with Time Windows(MDVRPTW)dataset to evaluate the performance of our system.According to the experimental results,TS-ACO,which considers spatial and temporal distance,is more effective than the classical ACO,which only considers spatial distance.
