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
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
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, ...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
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
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
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
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
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
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
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
A new mixed Eulerian-Lagrangian computational model for simulating and visualizing the internal processes and the variations of dynamic parameters of a two-stage pulse tube cooler (PTC) operating at 4 K-temperature re...A new mixed Eulerian-Lagrangian computational model for simulating and visualizing the internal processes and the variations of dynamic parameters of a two-stage pulse tube cooler (PTC) operating at 4 K-temperature region has been developed. We use the Lagrangian method, a set of moving grids, to follow the exact tracks of gas particles as they move with pressure oscillation in the pulse tube to avoid any numerical false diffusion. The Eulerian approach, a set of fixed computational grids, is used to simulate the variations of dynamic parameters in the regenerator. A variety of physical factors, such as real thermal properties of helium, multi-layered magnetic regenerative materials, pressure drop and heat transfer in the regenerator, and heat exchangers, are taken into account in this model. The present modeling is very effective for visualizing the internal physical processes in 4 K-pulse tube coolers.展开更多
The importance of properly treating boundary conditions (BCs) in numerical simulation of hemodynamics in intracranial aneurysm (IA) has been increasingly recognized. In this study, we constructed three types of comput...The importance of properly treating boundary conditions (BCs) in numerical simulation of hemodynamics in intracranial aneurysm (IA) has been increasingly recognized. In this study, we constructed three types of computational model for each IA to investigate how the outcome of numerical simulation is affected by the treatment of BCs. The first type of model (i.e., Type-A model) was obtained by applying 3-D hemodynamic modeling to the entire cerebral arterial network, with its solution being taken as the reference for evaluating the performance of the other two types of model (i.e., Type-B and Type-C models) in which 3-D modeling was confined to the aneurysm region. In addition, patient-specific 1-D models of the cerebral arterial network were developed to provide hemodynamic information for setting the inflow/outflow BCs of the 3-D models. Numerical tests on three IAs revealed that prescribing the outflow BCs of a localized 3-D aneurysm model based on 1-D model-simulated outflow division (i.e., Type-B model) instead of imposing the free outflow BC on all outlets (i.e., Type-C model) helped to improve the fidelity of the simulation of intra-aneurysmal hemodynamics, but could not guarantee a complete reproduction of the reference solution obtained by the Type-A model. Moreover, it was found that the outcome of hemodynamic simulation was more sensitive to the treatment of BCs when an aneurysm was located at arterial bifurcation rather than sidewall. These findings highlight the importance of taking into account systemic cerebroarterial hemodynamics in computational modeling of hemodynamics in IAs, especially those located at bifurcations.展开更多
Hybrid pull-push computational model can provide compelling results over either of single one for processing real-world graphs.Programmability and pipeline parallelism of FPGAs make it potential to process different s...Hybrid pull-push computational model can provide compelling results over either of single one for processing real-world graphs.Programmability and pipeline parallelism of FPGAs make it potential to process different stages of graph iterations.Nevertheless,considering the limited on-chip resources and streamline pipeline computation,the efficiency of hybrid model on FPGAs often suffers due to well-known random access feature of graph processing.In this paper,we present a hybrid graph processing system on FPGAs,which can achieve the best of both worlds.Our approach on FPGAs is unique and novel as follow.First,we propose to use edge block(consisting of edges with the same destination vertex set),which allows to sequentially access edges at block granularity for locality while still preserving the precision.Due to the independence of blocks in the sense that all edges in an inactive block are associated with inactive vertices,this also enables to skip invalid blocks for reducing redundant computation.Second,we consider a large number of vertices and their associated edge-blocks to maintain a predictable execution history.We also present to switch models in advance with few stalls using their state statistics.Our evaluation on a wide variety of graph algorithms for many real-world graphs shows that our approach achieves up to 3.69x speedup over state-of-the-art FPGA-based graph processing systems.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
Valvular heart disease is currently a common problem which causes high morbidity and mortality worldwide.Prosthetic valve replacements are widely needed to correct narrowing or backflow through the valvular orifice.Co...Valvular heart disease is currently a common problem which causes high morbidity and mortality worldwide.Prosthetic valve replacements are widely needed to correct narrowing or backflow through the valvular orifice.Compared to mechanical valves and biological valves,tissue-engineered heart valves can be an ideal substitute because they have a low risk of thromboembolism and calcification,and the potential for remodelling,regeneration,and growth.In order to test the performance of these heart valves,various animal models and other models are needed to optimise the structure and function of tissue-engineered heart valves,which may provide a potential mechanism responsible for substantial enhancement in tissue-engineered heart valves.Choosing the appropriate model for evaluating the performance of the tissue-engineered valve is important,as different models have their own advantages and disadvantages.In this review,we summarise the current state-of-the-art animal models,bioreactors,and computational simulation models with the aim of creating more strategies for better development of tissue-engineered heart valves.This review provides an overview of major factors that influence the selection and design of a model for tissue-engineered heart valve.Continued efforts in improving and testing models for valve regeneration remain crucial in basic science and translational researches.Future research should focus on finding the right animal model and developing better in vitro testing systems for tissue-engineered heart valve.展开更多
The objective of this paper is to investigate the different effects of disuse and estrogen deficiency on bone loss and the underlying mechanisms.A mechanical-biological factors coupled computational model was built to...The objective of this paper is to investigate the different effects of disuse and estrogen deficiency on bone loss and the underlying mechanisms.A mechanical-biological factors coupled computational model was built to simulate different patterns of bone loss induced in female rats by hind limb unloading,ovariectomy,or both in an animal study.A remodeling analysis was performed on a representative cross section of 6 mm2 of cancellous bone in the distal femoral metaphysis of the rats.The BMU activation frequency,the refilling rate,and the principal compressive strain in the state of mechanical unloading and estrogen deficiency were simulated to interpret the underlying mechanisms.Simulated bone loss patterns due to mechanical unloading,estrogen deficiency,or both all corresponded with the experimental observations.The results show that mechanical unloading and estrogen deficiency cause different bone loss patterns;moreover,mechanical unloading induces a greater degree of bone loss than estrogen deficiency,which can lead to improved treatment and prevention strategies for osteoporosis.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
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.
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.
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.
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 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 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 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A new mixed Eulerian-Lagrangian computational model for simulating and visualizing the internal processes and the variations of dynamic parameters of a two-stage pulse tube cooler (PTC) operating at 4 K-temperature region has been developed. We use the Lagrangian method, a set of moving grids, to follow the exact tracks of gas particles as they move with pressure oscillation in the pulse tube to avoid any numerical false diffusion. The Eulerian approach, a set of fixed computational grids, is used to simulate the variations of dynamic parameters in the regenerator. A variety of physical factors, such as real thermal properties of helium, multi-layered magnetic regenerative materials, pressure drop and heat transfer in the regenerator, and heat exchangers, are taken into account in this model. The present modeling is very effective for visualizing the internal physical processes in 4 K-pulse tube coolers.
基金This work was supported by the Clinical Research Plan of SHDC(Grant Nos.16CR3031A,16CR2045B)the SJTU Medical-Engineering Cross-cutting Research Foundation(Jrant Nos.YG2015MS53,YG2017MS45).
文摘The importance of properly treating boundary conditions (BCs) in numerical simulation of hemodynamics in intracranial aneurysm (IA) has been increasingly recognized. In this study, we constructed three types of computational model for each IA to investigate how the outcome of numerical simulation is affected by the treatment of BCs. The first type of model (i.e., Type-A model) was obtained by applying 3-D hemodynamic modeling to the entire cerebral arterial network, with its solution being taken as the reference for evaluating the performance of the other two types of model (i.e., Type-B and Type-C models) in which 3-D modeling was confined to the aneurysm region. In addition, patient-specific 1-D models of the cerebral arterial network were developed to provide hemodynamic information for setting the inflow/outflow BCs of the 3-D models. Numerical tests on three IAs revealed that prescribing the outflow BCs of a localized 3-D aneurysm model based on 1-D model-simulated outflow division (i.e., Type-B model) instead of imposing the free outflow BC on all outlets (i.e., Type-C model) helped to improve the fidelity of the simulation of intra-aneurysmal hemodynamics, but could not guarantee a complete reproduction of the reference solution obtained by the Type-A model. Moreover, it was found that the outcome of hemodynamic simulation was more sensitive to the treatment of BCs when an aneurysm was located at arterial bifurcation rather than sidewall. These findings highlight the importance of taking into account systemic cerebroarterial hemodynamics in computational modeling of hemodynamics in IAs, especially those located at bifurcations.
基金This work was supported by the National Key Research and Development Program of China(2018YFB1003502)the National Natural Science Foundation of China(Grant Nos.61825202,61832006,and 61702201).
文摘Hybrid pull-push computational model can provide compelling results over either of single one for processing real-world graphs.Programmability and pipeline parallelism of FPGAs make it potential to process different stages of graph iterations.Nevertheless,considering the limited on-chip resources and streamline pipeline computation,the efficiency of hybrid model on FPGAs often suffers due to well-known random access feature of graph processing.In this paper,we present a hybrid graph processing system on FPGAs,which can achieve the best of both worlds.Our approach on FPGAs is unique and novel as follow.First,we propose to use edge block(consisting of edges with the same destination vertex set),which allows to sequentially access edges at block granularity for locality while still preserving the precision.Due to the independence of blocks in the sense that all edges in an inactive block are associated with inactive vertices,this also enables to skip invalid blocks for reducing redundant computation.Second,we consider a large number of vertices and their associated edge-blocks to maintain a predictable execution history.We also present to switch models in advance with few stalls using their state statistics.Our evaluation on a wide variety of graph algorithms for many real-world graphs shows that our approach achieves up to 3.69x speedup over state-of-the-art FPGA-based graph processing systems.
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.
基金supported by the National Natural Science Foundation of China(No.81900351)National Key Research and Development Program of China(No.2018YFA0108700)Health Commission of Hubei Province Scientific Research Project of China(No.WJ2019Q034).
文摘Valvular heart disease is currently a common problem which causes high morbidity and mortality worldwide.Prosthetic valve replacements are widely needed to correct narrowing or backflow through the valvular orifice.Compared to mechanical valves and biological valves,tissue-engineered heart valves can be an ideal substitute because they have a low risk of thromboembolism and calcification,and the potential for remodelling,regeneration,and growth.In order to test the performance of these heart valves,various animal models and other models are needed to optimise the structure and function of tissue-engineered heart valves,which may provide a potential mechanism responsible for substantial enhancement in tissue-engineered heart valves.Choosing the appropriate model for evaluating the performance of the tissue-engineered valve is important,as different models have their own advantages and disadvantages.In this review,we summarise the current state-of-the-art animal models,bioreactors,and computational simulation models with the aim of creating more strategies for better development of tissue-engineered heart valves.This review provides an overview of major factors that influence the selection and design of a model for tissue-engineered heart valve.Continued efforts in improving and testing models for valve regeneration remain crucial in basic science and translational researches.Future research should focus on finding the right animal model and developing better in vitro testing systems for tissue-engineered heart valve.
基金Supported by the National Natural Science Foundation of China(Nos 10832012,10872078,and 10972090)
文摘The objective of this paper is to investigate the different effects of disuse and estrogen deficiency on bone loss and the underlying mechanisms.A mechanical-biological factors coupled computational model was built to simulate different patterns of bone loss induced in female rats by hind limb unloading,ovariectomy,or both in an animal study.A remodeling analysis was performed on a representative cross section of 6 mm2 of cancellous bone in the distal femoral metaphysis of the rats.The BMU activation frequency,the refilling rate,and the principal compressive strain in the state of mechanical unloading and estrogen deficiency were simulated to interpret the underlying mechanisms.Simulated bone loss patterns due to mechanical unloading,estrogen deficiency,or both all corresponded with the experimental observations.The results show that mechanical unloading and estrogen deficiency cause different bone loss patterns;moreover,mechanical unloading induces a greater degree of bone loss than estrogen deficiency,which can lead to improved treatment and prevention strategies for osteoporosis.
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.
