Metaverse technologies are increasingly promoted as game-changers in transport planning,connectedautonomous mobility,and immersive traveler services.However,the field lacks a systematic review of what has been achieve...Metaverse technologies are increasingly promoted as game-changers in transport planning,connectedautonomous mobility,and immersive traveler services.However,the field lacks a systematic review of what has been achieved,where critical technical gaps remain,and where future deployments should be integrated.Using a transparent protocol-driven screening process,we reviewed 1589 records and retained 101 peer-reviewed journal and conference articles(2021–2025)that explicitly frame their contributions within a transport-oriented metaverse.Our reviewreveals a predominantly exploratory evidence base.Among the 101 studies reviewed,17(16.8%)apply fuzzymulticriteria decision-making,36(35.6%)feature digital-twin visualizations or simulation-based testbeds,9(8.9%)present hardware-in-the-loop or field pilots,and only 4(4.0%)report performance metrics such as latency,throughput,or safety under realistic network conditions.Over time,the literature evolves fromearly conceptual sketches(2021–2022)through simulation-centered frameworks(2023)to nascent engineering prototypes(2024–2025).To clarify persistent gaps,we synthesize findings into four foundational layers—geometry and rendering,distributed synchronization,cryptographic integrity,and human factors—enumerating essential algorithms(homogeneous 4×4 transforms,Lamport clocks,Raft consensus,Merkle proofs,sweep-and-prune collision culling,Q-learning,and real-time ergonomic feedback loops).A worked bus-fleet prototype illustrates how blockchain-based ticketing,reinforcement learning-optimized traffic signals,and extended reality dispatch can be integrated into a live digital twin.This prototype is supported by a threephase rollout strategy.Advancing the transport metaverse from blueprint to operation requires open data schemas,reproducible edge–cloud performance benchmarks,cross-disciplinary cyber-physical threat models,and city-scale sandboxes that apply their mathematical foundations in real-world settings.展开更多
Within the prefrontal-cingulate cortex,abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions,contributing to the development of mental disorders such as depression.Despite ...Within the prefrontal-cingulate cortex,abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions,contributing to the development of mental disorders such as depression.Despite this understanding,the neural circuit mechanisms underlying this phenomenon remain elusive.In this study,we present a biophysical computational model encompassing three crucial regions,including the dorsolateral prefrontal cortex,subgenual anterior cingulate cortex,and ventromedial prefrontal cortex.The objective is to investigate the role of coupling relationships within the prefrontal-cingulate cortex networks in balancing emotions and cognitive processes.The numerical results confirm that coupled weights play a crucial role in the balance of emotional cognitive networks.Furthermore,our model predicts the pathogenic mechanism of depression resulting from abnormalities in the subgenual cortex,and network functionality was restored through intervention in the dorsolateral prefrontal cortex.This study utilizes computational modeling techniques to provide an insight explanation for the diagnosis and treatment of depression.展开更多
Electric vehicles,powered by electricity stored in a battery pack,are developing rapidly due to the rapid development of energy storage and the related motor systems being environmentally friendly.However,thermal runa...Electric vehicles,powered by electricity stored in a battery pack,are developing rapidly due to the rapid development of energy storage and the related motor systems being environmentally friendly.However,thermal runaway is the key scientific problem in battery safety research,which can cause fire and even lead to battery explosion under impact loading.In this work,a detailed computational model simulating the mechanical deformation and predicting the short-circuit onset of the 18,650 cylindrical battery is established.The detailed computational model,including the anode,cathode,separator,winding,and battery casing,is then developed under the indentation condition.The failure criteria are subsequently established based on the force–displacement curve and the separator failure.Two methods for improving the anti-short circuit ability are proposed.Results show the three causes of the short circuit and the failure sequence of components and reveal the reason why the fire is more serious under dynamic loading than under quasi-static loading.展开更多
The underlying electrophysiological mechanisms and clinical treatments of cardiovascular diseases,which are the most common cause of morbidity and mortality worldwide,have gotten a lot of attention and been widely exp...The underlying electrophysiological mechanisms and clinical treatments of cardiovascular diseases,which are the most common cause of morbidity and mortality worldwide,have gotten a lot of attention and been widely explored in recent decades.Along the way,techniques such as medical imaging,computing modeling,and artificial intelligence(AI)have always played significant roles in above studies.In this article,we illustrated the applications of AI in cardiac electrophysiological research and disease prediction.We summarized general principles of AI and then focused on the roles of AI in cardiac basic and clinical studies incorporating magnetic resonance imaging and computing modeling techniques.The main challenges and perspectives were also analyzed.展开更多
Acute morphological changes in de novo coronary lesions after drug-coated balloon(DCB)angioplasty can affect endothelial mechanics and consequently clinical outcomes.Angiography-based computational modeling has been v...Acute morphological changes in de novo coronary lesions after drug-coated balloon(DCB)angioplasty can affect endothelial mechanics and consequently clinical outcomes.Angiography-based computational modeling has been validated to assess endothelial dynamic strain(EDS)in coronary arteries in vivo.The EDS was calculated on the basis of pre-and post-DCB angiography.Parameters of quantitative coronary angiography and EDS were quantified at cross-sections in the treated segments.A total of 336 and 348 lesion cross-sections were included in the small/large vessel groups,respectively.The acute lumen gain after DCB was significantly higher in large than small vessels(relative changes:21.3%[17.4%,25.1%]vs.7.4%[4.8%,10.1%],P<0.001).Before treatment,three indices of EDS were significantly higher in small than large vessels(for ED-EDS:29.2%[19.8%,44.8%]vs.20.4%[14.3%,30.2%];for ES-EDS:26.8%[18.9%,37.7%]vs.18.3%[13.9%,25.4%];for TA-EDS:19.1%[13.9%,27.8%]vs.14.3%[10.5%,20.1%],P<0.001).After treatment,the EDS in small vessels significantly decreased(P<0.001).ED-EDS showed the highest correlation with pre-DCB DSP(r=0.43,P<0.001)and post-DCB MLD(r=0.35,P<0.001).The levels of EDS parameters for small or large vessel lesions significantly differed.Further study is required to examine the clinical value of EDS in predicting cardiac events after DCB treatment.展开更多
Reliable computational foot models offer an alternative means to enhance knowledge on the biomechanics of human foot. Model validation is one of the most critical aspects of the entire foot modeling and analysis proce...Reliable computational foot models offer an alternative means to enhance knowledge on the biomechanics of human foot. Model validation is one of the most critical aspects of the entire foot modeling and analysis process.This paper presents an in vivo experiment combining motion capture system and plantar pressure measure platform to validate a three-dimensional finite element model of human foot.The Magnetic Resonance Imaging(MRI)slices for the foot modeling and the experimental data for validation were both collected from the same volunteer subject.The validated components included the comparison of static model predictions of plantar force,plantar pressure and foot surface deformation during six loading conditions,to equivalent measured data.During the whole experiment,foot surface deformation,plantar force and plantar pressure were recorded simultaneously during six different loaded standing conditions.The predictions of the current FE model were in good agreement with these experimental results.展开更多
Biophysical computational models are complementary to experiments and theories,providing powerful tools for the study of neurological diseases.The focus of this review is the dynamic modeling and control strategies of...Biophysical computational models are complementary to experiments and theories,providing powerful tools for the study of neurological diseases.The focus of this review is the dynamic modeling and control strategies of Parkinson’s disease(PD).In previous studies,the development of parkinsonian network dynamics modeling has made great progress.Modeling mainly focuses on the cortex-thalamus-basal ganglia(CTBG)circuit and its sub-circuits,which helps to explore the dynamic behavior of the parkinsonian network,such as synchronization.Deep brain stimulation(DBS)is an effective strategy for the treatment of PD.At present,many studies are based on the side effects of the DBS.However,the translation from modeling results to clinical disease mitigation therapy still faces huge challenges.Here,we introduce the progress of DBS improvement.Its specific purpose is to develop novel DBS treatment methods,optimize the treatment effect of DBS for each patient,and focus on the study in closed-loop DBS.Our goal is to review the inspiration and insights gained by combining the system theory with these computational models to analyze neurodynamics and optimize DBS treatment.展开更多
Ca^2＋ dysregulation is an early event observed in Alzheimer＇s disease（AD） patients preceding the presence of its clinical symptoms.Dysregulation of neuronalCa^2＋ will cause synaptic loss and neuronal death,eventu...Ca^2＋ dysregulation is an early event observed in Alzheimer＇s disease（AD） patients preceding the presence of its clinical symptoms.Dysregulation of neuronalCa^2＋ will cause synaptic loss and neuronal death,eventually leading to memory impairments and cognitive decline.Treatments targetingCa^2＋ signaling pathways are potential therapeutic strategies against AD.The complicated interactions make it challenging and expensive to study the underlying mechanisms as to how Ca^2＋ signaling contributes to the pathogenesis of AD.Computational modeling offers new opportunities to study the signaling pathway and test proposed mechanisms.In this mini-review,we present some computational approaches that have been used to study Ca^2＋ dysregulation of AD by simulating Ca^2＋signaling at various levels.We also pointed out the future directions that computational modeling can be done in studying the Ca^2＋ dysregulation in AD.展开更多
Atrial fibrillation(AF)is one of the most common arrhythmias,associated with high morbidity,mortality,and healthcare costs,and it places a significant burden on both individuals and society.Anti-arrhythmic drugs are t...Atrial fibrillation(AF)is one of the most common arrhythmias,associated with high morbidity,mortality,and healthcare costs,and it places a significant burden on both individuals and society.Anti-arrhythmic drugs are the most commonly used strategy for treating AF.However,drug therapy faces challenges because of its limited efficacy and potential side effects.Catheter ablation is widely used as an alternative treatment for AF.Nevertheless,because the mechanism of AF is not fully understood,the recurrence rate after ablation remains high.In addition,the outcomes of ablation can vary significantly between medical institutions and patients,especially for persistent AF.Therefore,the issue of which ablation strategy is optimal is still far from settled.Computational modeling has the advantages of repeatable operation,low cost,freedom from risk,and complete control,and is a useful tool for not only predicting the results of different ablation strategies on the same model but also finding optimal personalized ablation targets for clinical reference and even guidance.This review summarizes three-dimensional computational modeling simulations of catheter ablation for AF,from the early-stage attempts such as Maze III or circumferential pulmonary vein isolation to the latest advances based on personalized substrate-guided ablation.Finally,we summarize current developments and challenges and provide our perspectives and suggestions for future directions.展开更多
The second part of this paper is devoted to the computational modelling of transient water migration in hardwood. During re-saturation, the moisture content, measured during the process by using X-ray attenuation (see...The second part of this paper is devoted to the computational modelling of transient water migration in hardwood. During re-saturation, the moisture content, measured during the process by using X-ray attenuation (see part 1 of this paper), increases quickly very close to the cavity, but requires a very long time for the remaining part of the sample to absorb the moisture in wetting. For this configuration and this material, the macroscopic approach fails. Consequently, a dual-porosity approach is proposed. The computational domain uses a 2-D axisymmetric configuration for which the axial coordinate represents the macroscopic longitudinal direction of the sample whereas the radial coordinate allows the slow migration from each active vessel towards the fibre zone to be considered. The latter is a microscopic space variable. The moisture content field evolution depicts clearly the dual scale mechanisms:a very fast longitudinal migration in the vessel followed by a slow migration from the vessel towards the fibre zone.The macroscopic moisture content field resulting from this dual scale mechanism is in quite good agreement with the experimental data.展开更多
Extremely low-frequency magnetic field is widely used as a noninvasive stimulation method in clinical practice and basic research. Electrical field induced from magnetic pulse can decrease or increase neuronal electri...Extremely low-frequency magnetic field is widely used as a noninvasive stimulation method in clinical practice and basic research. Electrical field induced from magnetic pulse can decrease or increase neuronal electrical activity. However, the cellular mechanism underlying the effects of magnetic field is not clear from experimental data. Recent studies have demonstrated that "non-neuronal" cells, especially astrocytes, may be the potential effector for transcranial magnetic stimulation(TMS). In the present study, we implemented a neural–astrocyte microcircuit computational model based on hippocampal architecture to investigate the biological effects of different magnetic field frequencies on cells. The purpose of the present study is to elucidate the main influencing factors of MS to allow a better understanding of its mechanisms.Our model reproduced the basic characteristics of the neuron and astrocyte response to different magnetic stimulation. The results predict that interneurons with lower firing thresholds were more active in magnetic fields by contrast to pyramidal neurons. And the synaptic coupling strength between the connected neurons may be one of the critical factor to affect the effect of magnetic field on cells. In addition, the simulations show that astrocytes can decrease or increase slow inward currents(SICs) to finely tune neuronal excitation, which suggests their key role in excitatory–inhibitory balance. The interaction between neurons and astrocytes may represent a novel target for effective therapeutic strategies involving magnetic stimulation.展开更多
Objective image quality assessment(IQA)plays an important role in various visual communication systems,which can automatically and efficiently predict the perceived quality of images.The human eye is the ultimate eval...Objective image quality assessment(IQA)plays an important role in various visual communication systems,which can automatically and efficiently predict the perceived quality of images.The human eye is the ultimate evaluator for visual experience,thus the modeling of human visual system(HVS)is a core issue for objective IQA and visual experience optimization.The traditional model based on black box fitting has low interpretability and it is difficult to guide the experience optimization effectively,while the model based on physiological simulation is hard to integrate into practical visual communication services due to its high computational complexity.For bridging the gap between signal distortion and visual experience,in this paper,we propose a novel perceptual no-reference(NR)IQA algorithm based on structural computational modeling of HVS.According to the mechanism of the human brain,we divide the visual signal processing into a low-level visual layer,a middle-level visual layer and a high-level visual layer,which conduct pixel information processing,primitive information processing and global image information processing,respectively.The natural scene statistics(NSS)based features,deep features and free-energy based features are extracted from these three layers.The support vector regression(SVR)is employed to aggregate features to the final quality prediction.Extensive experimental comparisons on three widely used benchmark IQA databases(LIVE,CSIQ and TID2013)demonstrate that our proposed metric is highly competitive with or outperforms the state-of-the-art NR IQA measures.展开更多
Transcutaneous electrical nerve stimulation(TENS) has been widely used for sensory feedback which is a key consideration of improving the performance of prosthetic hands. Two-electrode discriminability is the key to r...Transcutaneous electrical nerve stimulation(TENS) has been widely used for sensory feedback which is a key consideration of improving the performance of prosthetic hands. Two-electrode discriminability is the key to realize high-spatial-resolution TENS, but the neural firing mechanism is not clear yet. The goal of this research is to investigate the neural firing patterns under two-electrode stimulation and to reveal the potential mechanisms. A three-dimensional(3 D) model is established by incorporating Aβ fiber neuron clusters into a layered forearm structure. The diameters of the stimulating electrodes are selected as 5, 7, 9 and 12 mm, and the two-electrode discrimination distance(TEDD) is quantified. It is found that a distant TEDD is obtained for a relatively large electrode size, and 7 mm is suggested to be the optimal diameter of stimulating electrodes. The present study reveals the neural firing patterns under two-electrode stimulation by the 3 D TENS model. In order to discriminate individual electrodes under simultaneous stimulation, no crosstalk of activated Aβ fibers exists between two electrodes. This research can further guide the optimization of the electrode-array floorplan.展开更多
This paper develops a comprehensive computational modeling and simulation framework based on Complex Adaptive Systems(CAS)theory to unveil the underlying mechanisms of self-organization,nonlinear evolution,and emergen...This paper develops a comprehensive computational modeling and simulation framework based on Complex Adaptive Systems(CAS)theory to unveil the underlying mechanisms of self-organization,nonlinear evolution,and emergence in social systems.By integrating mathematical models,agent-based modeling,network dynamic analysis,and hybrid modeling approaches,the study applies CAS theory to case studies in economic markets,political decision-making,and social interactions.The experimental results demonstrate that local interactions among individual agents can give rise to complex global phenomena,such as market fluctuations,opinion polarization,and sudden outbreaks of social movements.This framework not only provides a more robust explanation for the nonlinear dynamics and abrupt transitions that traditional models often fail to capture,but also offers valuable decision-support tools for public policy formulation,social governance,and risk management.Emphasizing the importance of interdisciplinary approaches,this work outlines future research directions in high-performance computing,artificial intelligence,and real-time data integration to further advance the theoretical and practical applications of CAS in the social sciences.展开更多
Magnesium alloys are highly attractive for the use as temporary implant materials,due to their high biocompatibility and biodegradability.However,the prediction of the degradation rate of the implants is difficult,the...Magnesium alloys are highly attractive for the use as temporary implant materials,due to their high biocompatibility and biodegradability.However,the prediction of the degradation rate of the implants is difficult,therefore,a large number of experiments are required.Computational modelling can aid in enabling the predictability,if sufficiently accurate models can be established.This work presents a generalized model of the degradation of pure magnesium in simulated body fluid over the course of 28 days considering uncertainty aspects.The model includes the computation of the metallic material thinning and is calibrated using the mean degradation depth of several experimental datasets simultaneously.Additionally,the formation and precipitation of relevant degradation products on the sample surface is modelled,based on the ionic composition of simulated body fluid.The computed mean degradation depth is in good agreement with the experimental data(NRMSE=0.07).However,the quality of the depth profile curves of the determined elemental weight percentage of the degradation products differs between elements(such as NRMSE=0.40 for phosphorus vs.NRMSE=1.03 for magnesium).This indicates that the implementation of precipitate formation may need further developments.The sensitivity analysis showed that the model parameters are correlated and which is related to the complexity and the high computational costs of the model.Overall,the model provides a correlating fit to the experimental data of pure Mg samples of different geometries degrading in simulated body fluid with reliable error estimation.展开更多
Orthokeratology(OK)is widely used for effective myopia correction and control.However,the incomplete understanding of its biomechanical mechanisms makes OK lens fitting rely heavily on clinician judgment,complicating ...Orthokeratology(OK)is widely used for effective myopia correction and control.However,the incomplete understanding of its biomechanical mechanisms makes OK lens fitting rely heavily on clinician judgment,complicating accurate predictions of treatment outcomes.In this paper,we performed clinical experiments and numerical analysis to study corneal deformation modes and long-term changes in central corneal thickness.Clinical experiments were conducted on 194 Chinese myopic patients under OK treatment for 3 months.Based on the experimental data,a patient-specific computational biomechanical model for OK was established and validated.Specifically,the anisotropic mechanical properties of the cornea were incorporated into the model to describe the significant difference between its shear modulus(29.5 kPa)and tensile modulus(768.4 kPa).Additionally,a viscohyperelastic material model with a prolonged corneal relaxation time of 5.6 h was developed to capture the long-term deformation response.The results show that corneal thickness reduction in OK is primarily due to out-of-plane shear deformation,influenced by the cornea’s low shear resistance.Modeling the extended corneal relaxation time is crucial for predicting long-term biomechanical responses.The computational model effectively captures long-term changes in central corneal thickness,potentially improving OK lens fitting accuracy.展开更多
Titanium-silicon(Ti-Si)alloy system shows significant potential for aerospace and automotive applications due to its superior specific strength,creep resistance,and oxidation resistance.For Si-containing Ti alloys,the...Titanium-silicon(Ti-Si)alloy system shows significant potential for aerospace and automotive applications due to its superior specific strength,creep resistance,and oxidation resistance.For Si-containing Ti alloys,the sufficient content of Si is critical for achieving these favorable performances,while excessive Si addition will result in mechanical brittleness.Herein,both physical experiments and finite element(FE)simulations are employed to investigate the micro-mechanisms of Si alloying in tailoring the mechanical properties of Ti alloys.Four typical states of Si-containing Ti alloys(solid solution state,hypoeutectoid state,near-eutectoid state,hypereutectoid state)with varying Si content(0.3-1.2 wt.%)were fabricated via in-situ alloying spark plasma sintering.Experimental results indicate that in-situ alloying of 0.6 wt.%Si enhances the alloy’s strength and ductility simultaneously due to the formation of fine and uniformly dispersed Ti_(5)Si_(3)particles,while higher content of Si(0.9 and 1.2 wt.%)results in coarser primary Ti_(5)Si_(3)agglomerations,deteriorating the ductility.FE simulations support these findings,highlighting the finer and more uniformly distributed Ti_(5)Si_(3)particles contribute to less stress concentration and promote uniform deformation across the matrix,while agglomerated Ti_(5)Si_(3)particles result in increased local stress concentrations,leading to higher chances of particle fracture and reduced ductility.This study not only elucidates the micro-mechanisms of in-situ Si alloying for tailoring the mechanical properties of Ti alloys but also aids in optimizing the design of high-performance Si-containing Ti alloys.展开更多
In museum design and operation,daylight is typically discouraged due to high risk of damaging the display objects.However,past studies in high-latitude regions have shown the possibility to apply daylight in museums,s...In museum design and operation,daylight is typically discouraged due to high risk of damaging the display objects.However,past studies in high-latitude regions have shown the possibility to apply daylight in museums,so long as it is carefully planned,and the display objects are not from the category of high responsive materials.In the tropical region,the influence of daylighting on light exposure on museum objects is still unknown.This study therefore aims to assess and mitigate the impact of annual daylight exposure on objects with low responsive materials in a tropical daylit museum building.Annual daylight modelling and simulation are performed to achieve the objective,followed with Morris sensitivity analysis and Mahalanobis distance classifier to optimise the outcome.It is found that either WWR or glazing transmissivity gives the greatest influence on the performance indicators.Based on the proposed optimisation algorithm,it is possible to determine the optimum solutions satisfying the performance indicators target,for a certain opening type.Overall,the contribution of this study is the proposed computational modelling and simulation methods to mitigate the exposure risk while optimising daylight as a renewable energy source.展开更多
The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical r...The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.展开更多
With the rapid advancement of computational technologies and the in-depth exploration of multimodal discourse analysis theory,the intersection of these fields has become a frontier area in both technology and linguist...With the rapid advancement of computational technologies and the in-depth exploration of multimodal discourse analysis theory,the intersection of these fields has become a frontier area in both technology and linguistics research.This article examines the application of computational models in multimodal discourse analysis and analyzes how innovations in multimodal discourse analysis theory drive advancements in computational models.Through empirical studies and theoretical discussions,the paper reveals the interaction mechanisms between computational models and multimodal discourse analysis in practice and highlights their theoretical complementarity,providing new perspectives and methodologies for future research.The findings show that effective computational models enhance the accuracy and depth of multimodal analysis,while theoretical innovations in multimodal discourse analysis propel computational models toward greater efficiency and adaptability.展开更多
基金financial support from the Centro de Matematica da Universidade doMinho(CMAT/UM),through project UID/00013.
文摘Metaverse technologies are increasingly promoted as game-changers in transport planning,connectedautonomous mobility,and immersive traveler services.However,the field lacks a systematic review of what has been achieved,where critical technical gaps remain,and where future deployments should be integrated.Using a transparent protocol-driven screening process,we reviewed 1589 records and retained 101 peer-reviewed journal and conference articles(2021–2025)that explicitly frame their contributions within a transport-oriented metaverse.Our reviewreveals a predominantly exploratory evidence base.Among the 101 studies reviewed,17(16.8%)apply fuzzymulticriteria decision-making,36(35.6%)feature digital-twin visualizations or simulation-based testbeds,9(8.9%)present hardware-in-the-loop or field pilots,and only 4(4.0%)report performance metrics such as latency,throughput,or safety under realistic network conditions.Over time,the literature evolves fromearly conceptual sketches(2021–2022)through simulation-centered frameworks(2023)to nascent engineering prototypes(2024–2025).To clarify persistent gaps,we synthesize findings into four foundational layers—geometry and rendering,distributed synchronization,cryptographic integrity,and human factors—enumerating essential algorithms(homogeneous 4×4 transforms,Lamport clocks,Raft consensus,Merkle proofs,sweep-and-prune collision culling,Q-learning,and real-time ergonomic feedback loops).A worked bus-fleet prototype illustrates how blockchain-based ticketing,reinforcement learning-optimized traffic signals,and extended reality dispatch can be integrated into a live digital twin.This prototype is supported by a threephase rollout strategy.Advancing the transport metaverse from blueprint to operation requires open data schemas,reproducible edge–cloud performance benchmarks,cross-disciplinary cyber-physical threat models,and city-scale sandboxes that apply their mathematical foundations in real-world settings.
基金supported by the Major Research Instrument Development Project of the National Natural Science Foundation of China(82327810)the Foundation of the President of Hebei University(XZJJ202202)the Hebei Province“333 talent project”(A202101058).
文摘Within the prefrontal-cingulate cortex,abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions,contributing to the development of mental disorders such as depression.Despite this understanding,the neural circuit mechanisms underlying this phenomenon remain elusive.In this study,we present a biophysical computational model encompassing three crucial regions,including the dorsolateral prefrontal cortex,subgenual anterior cingulate cortex,and ventromedial prefrontal cortex.The objective is to investigate the role of coupling relationships within the prefrontal-cingulate cortex networks in balancing emotions and cognitive processes.The numerical results confirm that coupled weights play a crucial role in the balance of emotional cognitive networks.Furthermore,our model predicts the pathogenic mechanism of depression resulting from abnormalities in the subgenual cortex,and network functionality was restored through intervention in the dorsolateral prefrontal cortex.This study utilizes computational modeling techniques to provide an insight explanation for the diagnosis and treatment of depression.
基金supported by the National Natural Science Foundation of China(Grant Numbers:12172149 and 12172151).
文摘Electric vehicles,powered by electricity stored in a battery pack,are developing rapidly due to the rapid development of energy storage and the related motor systems being environmentally friendly.However,thermal runaway is the key scientific problem in battery safety research,which can cause fire and even lead to battery explosion under impact loading.In this work,a detailed computational model simulating the mechanical deformation and predicting the short-circuit onset of the 18,650 cylindrical battery is established.The detailed computational model,including the anode,cathode,separator,winding,and battery casing,is then developed under the indentation condition.The failure criteria are subsequently established based on the force–displacement curve and the separator failure.Two methods for improving the anti-short circuit ability are proposed.Results show the three causes of the short circuit and the failure sequence of components and reveal the reason why the fire is more serious under dynamic loading than under quasi-static loading.
基金the Hainan Provincial Natural Science Foundation of China(No.820RC625)the National Natural Science Foundation of China(No.82060332)。
文摘The underlying electrophysiological mechanisms and clinical treatments of cardiovascular diseases,which are the most common cause of morbidity and mortality worldwide,have gotten a lot of attention and been widely explored in recent decades.Along the way,techniques such as medical imaging,computing modeling,and artificial intelligence(AI)have always played significant roles in above studies.In this article,we illustrated the applications of AI in cardiac electrophysiological research and disease prediction.We summarized general principles of AI and then focused on the roles of AI in cardiac basic and clinical studies incorporating magnetic resonance imaging and computing modeling techniques.The main challenges and perspectives were also analyzed.
基金supported by the Zhejiang Provincial Natural Science Foundation of China(LTGY24H180019)Basic Medical and Health Science Technology Projects of Wenzhou City(Y20220132)Medical and Health Science and Technology Project of Zhejiang Province(2023RC210 and 2024KY160).
文摘Acute morphological changes in de novo coronary lesions after drug-coated balloon(DCB)angioplasty can affect endothelial mechanics and consequently clinical outcomes.Angiography-based computational modeling has been validated to assess endothelial dynamic strain(EDS)in coronary arteries in vivo.The EDS was calculated on the basis of pre-and post-DCB angiography.Parameters of quantitative coronary angiography and EDS were quantified at cross-sections in the treated segments.A total of 336 and 348 lesion cross-sections were included in the small/large vessel groups,respectively.The acute lumen gain after DCB was significantly higher in large than small vessels(relative changes:21.3%[17.4%,25.1%]vs.7.4%[4.8%,10.1%],P<0.001).Before treatment,three indices of EDS were significantly higher in small than large vessels(for ED-EDS:29.2%[19.8%,44.8%]vs.20.4%[14.3%,30.2%];for ES-EDS:26.8%[18.9%,37.7%]vs.18.3%[13.9%,25.4%];for TA-EDS:19.1%[13.9%,27.8%]vs.14.3%[10.5%,20.1%],P<0.001).After treatment,the EDS in small vessels significantly decreased(P<0.001).ED-EDS showed the highest correlation with pre-DCB DSP(r=0.43,P<0.001)and post-DCB MLD(r=0.35,P<0.001).The levels of EDS parameters for small or large vessel lesions significantly differed.Further study is required to examine the clinical value of EDS in predicting cardiac events after DCB treatment.
基金supported by the "Mechanical Virtual Human of China"project funded by the National Natural Science Foundation of China(30530230)further support was from the UK Royal Scoiety(Grant:IPJ/2006/R3)
文摘Reliable computational foot models offer an alternative means to enhance knowledge on the biomechanics of human foot. Model validation is one of the most critical aspects of the entire foot modeling and analysis process.This paper presents an in vivo experiment combining motion capture system and plantar pressure measure platform to validate a three-dimensional finite element model of human foot.The Magnetic Resonance Imaging(MRI)slices for the foot modeling and the experimental data for validation were both collected from the same volunteer subject.The validated components included the comparison of static model predictions of plantar force,plantar pressure and foot surface deformation during six loading conditions,to equivalent measured data.During the whole experiment,foot surface deformation,plantar force and plantar pressure were recorded simultaneously during six different loaded standing conditions.The predictions of the current FE model were in good agreement with these experimental results.
基金Project supported by the National Natural Science Foundation of China(Nos.11932003 and 11772019)。
文摘Biophysical computational models are complementary to experiments and theories,providing powerful tools for the study of neurological diseases.The focus of this review is the dynamic modeling and control strategies of Parkinson’s disease(PD).In previous studies,the development of parkinsonian network dynamics modeling has made great progress.Modeling mainly focuses on the cortex-thalamus-basal ganglia(CTBG)circuit and its sub-circuits,which helps to explore the dynamic behavior of the parkinsonian network,such as synchronization.Deep brain stimulation(DBS)is an effective strategy for the treatment of PD.At present,many studies are based on the side effects of the DBS.However,the translation from modeling results to clinical disease mitigation therapy still faces huge challenges.Here,we introduce the progress of DBS improvement.Its specific purpose is to develop novel DBS treatment methods,optimize the treatment effect of DBS for each patient,and focus on the study in closed-loop DBS.Our goal is to review the inspiration and insights gained by combining the system theory with these computational models to analyze neurodynamics and optimize DBS treatment.
文摘Ca^2＋ dysregulation is an early event observed in Alzheimer＇s disease（AD） patients preceding the presence of its clinical symptoms.Dysregulation of neuronalCa^2＋ will cause synaptic loss and neuronal death,eventually leading to memory impairments and cognitive decline.Treatments targetingCa^2＋ signaling pathways are potential therapeutic strategies against AD.The complicated interactions make it challenging and expensive to study the underlying mechanisms as to how Ca^2＋ signaling contributes to the pathogenesis of AD.Computational modeling offers new opportunities to study the signaling pathway and test proposed mechanisms.In this mini-review,we present some computational approaches that have been used to study Ca^2＋ dysregulation of AD by simulating Ca^2＋signaling at various levels.We also pointed out the future directions that computational modeling can be done in studying the Ca^2＋ dysregulation in AD.
基金This work was supported by the National Natural Science Foundation of China(Nos.81901841 and 61527811)the Key Research and Development Program of Zhejiang Province(No.2020C03016)the Dalian University of Technology(No.DUT18RC(3)068),China.
文摘Atrial fibrillation(AF)is one of the most common arrhythmias,associated with high morbidity,mortality,and healthcare costs,and it places a significant burden on both individuals and society.Anti-arrhythmic drugs are the most commonly used strategy for treating AF.However,drug therapy faces challenges because of its limited efficacy and potential side effects.Catheter ablation is widely used as an alternative treatment for AF.Nevertheless,because the mechanism of AF is not fully understood,the recurrence rate after ablation remains high.In addition,the outcomes of ablation can vary significantly between medical institutions and patients,especially for persistent AF.Therefore,the issue of which ablation strategy is optimal is still far from settled.Computational modeling has the advantages of repeatable operation,low cost,freedom from risk,and complete control,and is a useful tool for not only predicting the results of different ablation strategies on the same model but also finding optimal personalized ablation targets for clinical reference and even guidance.This review summarizes three-dimensional computational modeling simulations of catheter ablation for AF,from the early-stage attempts such as Maze III or circumferential pulmonary vein isolation to the latest advances based on personalized substrate-guided ablation.Finally,we summarize current developments and challenges and provide our perspectives and suggestions for future directions.
文摘The second part of this paper is devoted to the computational modelling of transient water migration in hardwood. During re-saturation, the moisture content, measured during the process by using X-ray attenuation (see part 1 of this paper), increases quickly very close to the cavity, but requires a very long time for the remaining part of the sample to absorb the moisture in wetting. For this configuration and this material, the macroscopic approach fails. Consequently, a dual-porosity approach is proposed. The computational domain uses a 2-D axisymmetric configuration for which the axial coordinate represents the macroscopic longitudinal direction of the sample whereas the radial coordinate allows the slow migration from each active vessel towards the fibre zone to be considered. The latter is a microscopic space variable. The moisture content field evolution depicts clearly the dual scale mechanisms:a very fast longitudinal migration in the vessel followed by a slow migration from the vessel towards the fibre zone.The macroscopic moisture content field resulting from this dual scale mechanism is in quite good agreement with the experimental data.
基金supported by the National Natural Science Foundation of China (Grant No. 61673158)the Youth Talent Support Program of Hebei Province,China(Grant No. BJ2019044)。
文摘Extremely low-frequency magnetic field is widely used as a noninvasive stimulation method in clinical practice and basic research. Electrical field induced from magnetic pulse can decrease or increase neuronal electrical activity. However, the cellular mechanism underlying the effects of magnetic field is not clear from experimental data. Recent studies have demonstrated that "non-neuronal" cells, especially astrocytes, may be the potential effector for transcranial magnetic stimulation(TMS). In the present study, we implemented a neural–astrocyte microcircuit computational model based on hippocampal architecture to investigate the biological effects of different magnetic field frequencies on cells. The purpose of the present study is to elucidate the main influencing factors of MS to allow a better understanding of its mechanisms.Our model reproduced the basic characteristics of the neuron and astrocyte response to different magnetic stimulation. The results predict that interneurons with lower firing thresholds were more active in magnetic fields by contrast to pyramidal neurons. And the synaptic coupling strength between the connected neurons may be one of the critical factor to affect the effect of magnetic field on cells. In addition, the simulations show that astrocytes can decrease or increase slow inward currents(SICs) to finely tune neuronal excitation, which suggests their key role in excitatory–inhibitory balance. The interaction between neurons and astrocytes may represent a novel target for effective therapeutic strategies involving magnetic stimulation.
基金This work was supported by National Natural Science Foundation of China(Nos.61831015 and 61901260)Key Research and Development Program of China(No.2019YFB1405902).
文摘Objective image quality assessment(IQA)plays an important role in various visual communication systems,which can automatically and efficiently predict the perceived quality of images.The human eye is the ultimate evaluator for visual experience,thus the modeling of human visual system(HVS)is a core issue for objective IQA and visual experience optimization.The traditional model based on black box fitting has low interpretability and it is difficult to guide the experience optimization effectively,while the model based on physiological simulation is hard to integrate into practical visual communication services due to its high computational complexity.For bridging the gap between signal distortion and visual experience,in this paper,we propose a novel perceptual no-reference(NR)IQA algorithm based on structural computational modeling of HVS.According to the mechanism of the human brain,we divide the visual signal processing into a low-level visual layer,a middle-level visual layer and a high-level visual layer,which conduct pixel information processing,primitive information processing and global image information processing,respectively.The natural scene statistics(NSS)based features,deep features and free-energy based features are extracted from these three layers.The support vector regression(SVR)is employed to aggregate features to the final quality prediction.Extensive experimental comparisons on three widely used benchmark IQA databases(LIVE,CSIQ and TID2013)demonstrate that our proposed metric is highly competitive with or outperforms the state-of-the-art NR IQA measures.
基金the National Natural Science Foundation of China(No.81671801)the Innovation Studio Fund from School of Biomedical Engineering at Shanghai Jiao Tong Universitythe Medical-Engineering Cross Project of Shanghai Jiao Tong University(No.YG2017MS53)
文摘Transcutaneous electrical nerve stimulation(TENS) has been widely used for sensory feedback which is a key consideration of improving the performance of prosthetic hands. Two-electrode discriminability is the key to realize high-spatial-resolution TENS, but the neural firing mechanism is not clear yet. The goal of this research is to investigate the neural firing patterns under two-electrode stimulation and to reveal the potential mechanisms. A three-dimensional(3 D) model is established by incorporating Aβ fiber neuron clusters into a layered forearm structure. The diameters of the stimulating electrodes are selected as 5, 7, 9 and 12 mm, and the two-electrode discrimination distance(TEDD) is quantified. It is found that a distant TEDD is obtained for a relatively large electrode size, and 7 mm is suggested to be the optimal diameter of stimulating electrodes. The present study reveals the neural firing patterns under two-electrode stimulation by the 3 D TENS model. In order to discriminate individual electrodes under simultaneous stimulation, no crosstalk of activated Aβ fibers exists between two electrodes. This research can further guide the optimization of the electrode-array floorplan.
文摘This paper develops a comprehensive computational modeling and simulation framework based on Complex Adaptive Systems(CAS)theory to unveil the underlying mechanisms of self-organization,nonlinear evolution,and emergence in social systems.By integrating mathematical models,agent-based modeling,network dynamic analysis,and hybrid modeling approaches,the study applies CAS theory to case studies in economic markets,political decision-making,and social interactions.The experimental results demonstrate that local interactions among individual agents can give rise to complex global phenomena,such as market fluctuations,opinion polarization,and sudden outbreaks of social movements.This framework not only provides a more robust explanation for the nonlinear dynamics and abrupt transitions that traditional models often fail to capture,but also offers valuable decision-support tools for public policy formulation,social governance,and risk management.Emphasizing the importance of interdisciplinary approaches,this work outlines future research directions in high-performance computing,artificial intelligence,and real-time data integration to further advance the theoretical and practical applications of CAS in the social sciences.
基金funding from the Helmholtz-Incubator project Uncertainty Quantification.
文摘Magnesium alloys are highly attractive for the use as temporary implant materials,due to their high biocompatibility and biodegradability.However,the prediction of the degradation rate of the implants is difficult,therefore,a large number of experiments are required.Computational modelling can aid in enabling the predictability,if sufficiently accurate models can be established.This work presents a generalized model of the degradation of pure magnesium in simulated body fluid over the course of 28 days considering uncertainty aspects.The model includes the computation of the metallic material thinning and is calibrated using the mean degradation depth of several experimental datasets simultaneously.Additionally,the formation and precipitation of relevant degradation products on the sample surface is modelled,based on the ionic composition of simulated body fluid.The computed mean degradation depth is in good agreement with the experimental data(NRMSE=0.07).However,the quality of the depth profile curves of the determined elemental weight percentage of the degradation products differs between elements(such as NRMSE=0.40 for phosphorus vs.NRMSE=1.03 for magnesium).This indicates that the implementation of precipitate formation may need further developments.The sensitivity analysis showed that the model parameters are correlated and which is related to the complexity and the high computational costs of the model.Overall,the model provides a correlating fit to the experimental data of pure Mg samples of different geometries degrading in simulated body fluid with reliable error estimation.
基金supported by the National Natural Science Foundation of China(Grant Nos.82371038,and 11921002)the R&D Program of Beijing Municipal Education Commission(Grant No.KZ20231002503)+1 种基金the Chinese Institutes for Medical Research,Beijing(Grant No.CX24PY17)Beijing Municipal Administration of Hospitals Incubating Program(Grant No.PX2024011)。
文摘Orthokeratology(OK)is widely used for effective myopia correction and control.However,the incomplete understanding of its biomechanical mechanisms makes OK lens fitting rely heavily on clinician judgment,complicating accurate predictions of treatment outcomes.In this paper,we performed clinical experiments and numerical analysis to study corneal deformation modes and long-term changes in central corneal thickness.Clinical experiments were conducted on 194 Chinese myopic patients under OK treatment for 3 months.Based on the experimental data,a patient-specific computational biomechanical model for OK was established and validated.Specifically,the anisotropic mechanical properties of the cornea were incorporated into the model to describe the significant difference between its shear modulus(29.5 kPa)and tensile modulus(768.4 kPa).Additionally,a viscohyperelastic material model with a prolonged corneal relaxation time of 5.6 h was developed to capture the long-term deformation response.The results show that corneal thickness reduction in OK is primarily due to out-of-plane shear deformation,influenced by the cornea’s low shear resistance.Modeling the extended corneal relaxation time is crucial for predicting long-term biomechanical responses.The computational model effectively captures long-term changes in central corneal thickness,potentially improving OK lens fitting accuracy.
基金supported by the Natural Science Foundation of Hunan Province(Grant No.2023JJ40353)the National Key Research and Development Program of China(No.2019YFE03120001).
文摘Titanium-silicon(Ti-Si)alloy system shows significant potential for aerospace and automotive applications due to its superior specific strength,creep resistance,and oxidation resistance.For Si-containing Ti alloys,the sufficient content of Si is critical for achieving these favorable performances,while excessive Si addition will result in mechanical brittleness.Herein,both physical experiments and finite element(FE)simulations are employed to investigate the micro-mechanisms of Si alloying in tailoring the mechanical properties of Ti alloys.Four typical states of Si-containing Ti alloys(solid solution state,hypoeutectoid state,near-eutectoid state,hypereutectoid state)with varying Si content(0.3-1.2 wt.%)were fabricated via in-situ alloying spark plasma sintering.Experimental results indicate that in-situ alloying of 0.6 wt.%Si enhances the alloy’s strength and ductility simultaneously due to the formation of fine and uniformly dispersed Ti_(5)Si_(3)particles,while higher content of Si(0.9 and 1.2 wt.%)results in coarser primary Ti_(5)Si_(3)agglomerations,deteriorating the ductility.FE simulations support these findings,highlighting the finer and more uniformly distributed Ti_(5)Si_(3)particles contribute to less stress concentration and promote uniform deformation across the matrix,while agglomerated Ti_(5)Si_(3)particles result in increased local stress concentrations,leading to higher chances of particle fracture and reduced ductility.This study not only elucidates the micro-mechanisms of in-situ Si alloying for tailoring the mechanical properties of Ti alloys but also aids in optimizing the design of high-performance Si-containing Ti alloys.
基金supported by the Ministry of Education,Culture,Research,and Technology of the Republic of Indonesia,through the PDUPT 2021 Research Program.
文摘In museum design and operation,daylight is typically discouraged due to high risk of damaging the display objects.However,past studies in high-latitude regions have shown the possibility to apply daylight in museums,so long as it is carefully planned,and the display objects are not from the category of high responsive materials.In the tropical region,the influence of daylighting on light exposure on museum objects is still unknown.This study therefore aims to assess and mitigate the impact of annual daylight exposure on objects with low responsive materials in a tropical daylit museum building.Annual daylight modelling and simulation are performed to achieve the objective,followed with Morris sensitivity analysis and Mahalanobis distance classifier to optimise the outcome.It is found that either WWR or glazing transmissivity gives the greatest influence on the performance indicators.Based on the proposed optimisation algorithm,it is possible to determine the optimum solutions satisfying the performance indicators target,for a certain opening type.Overall,the contribution of this study is the proposed computational modelling and simulation methods to mitigate the exposure risk while optimising daylight as a renewable energy source.
文摘The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.
文摘With the rapid advancement of computational technologies and the in-depth exploration of multimodal discourse analysis theory,the intersection of these fields has become a frontier area in both technology and linguistics research.This article examines the application of computational models in multimodal discourse analysis and analyzes how innovations in multimodal discourse analysis theory drive advancements in computational models.Through empirical studies and theoretical discussions,the paper reveals the interaction mechanisms between computational models and multimodal discourse analysis in practice and highlights their theoretical complementarity,providing new perspectives and methodologies for future research.The findings show that effective computational models enhance the accuracy and depth of multimodal analysis,while theoretical innovations in multimodal discourse analysis propel computational models toward greater efficiency and adaptability.
