This study presents an innovative development of the exponentially weighted moving average(EWMA)control chart,explicitly adapted for the examination of time series data distinguished by seasonal autoregressive moving ...This study presents an innovative development of the exponentially weighted moving average(EWMA)control chart,explicitly adapted for the examination of time series data distinguished by seasonal autoregressive moving average behavior—SARMA(1,1)L under exponential white noise.Unlike previous works that rely on simplified models such as AR(1)or assume independence,this research derives for the first time an exact two-sided Average Run Length(ARL)formula for theModified EWMAchart under SARMA(1,1)L conditions,using a mathematically rigorous Fredholm integral approach.The derived formulas are validated against numerical integral equation(NIE)solutions,showing strong agreement and significantly reduced computational burden.Additionally,a performance comparison index(PCI)is introduced to assess the chart’s detection capability.Results demonstrate that the proposed method exhibits superior sensitivity to mean shifts in autocorrelated environments,outperforming existing approaches.The findings offer a new,efficient framework for real-time quality control in complex seasonal processes,with potential applications in environmental monitoring and intelligent manufacturing systems.展开更多
The distribution of the various organic and inorganic constituents and their influences on the combustion of coal has been comprehensively studied.However,the combustion characteristics of pulverized coal depend not o...The distribution of the various organic and inorganic constituents and their influences on the combustion of coal has been comprehensively studied.However,the combustion characteristics of pulverized coal depend not only on rank but also on the composition,distribution,and combination of the macerals.Unlike the proximate and ultimate analyses,determining the macerals in coal involves the use of sophisticated microscopic instrumentation and expertise.In this study,an attempt was made to predict the amount of macerals(vitrinite,inertinite,and liptinite)and total mineral matter from the Witbank Coalfields samples using the multiple input single output white-box artificial neural network(MISOWB-ANN),gene expression programming(GEP),multiple linear regression(MLR),and multiple nonlinear regression(MNLR).The predictive models obtained from the multiple soft computing models adopted are contrasted with one another using difference,efficiency,and composite statistical indicators to examine the appropriateness of the models.The MISOWB-ANN provides a more reliable predictive model than the other three models with the lowest difference and highest efficiency and composite statistical indicators.展开更多
Cancer is a major stress for public well-being and is the most dreadful disease.The models used in the discovery of cancer treatment are continuously changing and extending toward advanced preclinical studies.Cancer m...Cancer is a major stress for public well-being and is the most dreadful disease.The models used in the discovery of cancer treatment are continuously changing and extending toward advanced preclinical studies.Cancer models are either naturally existing or artificially prepared experimental systems that show similar features with human tumors though the heterogeneous nature of the tumor is very familiar.The choice of the most fitting model to best reflect the given tumor system is one of the real difficulties for cancer examination.Therefore,vast studies have been conducted on the cancer models for developing a better understanding of cancer invasion,progression,and early detection.These models give an insight into cancer etiology,molecular basis,host tumor interaction,the role of microenvironment,and tumor heterogeneity in tumor metastasis.These models are also used to predict novel can-cer markers,targeted therapies,and are extremely helpful in drug development.In this review,the potential of cancer models to be used as a platform for drug screening and therapeutic discoveries are highlighted.Although none of the cancer models is regarded as ideal because each is associated with essential caveats that restraint its application yet by bridging the gap between preliminary cancer research and transla-tional medicine.However,they promise a brighter future for cancer treatment.展开更多
Analytical and numerical computed models are developed for reverse pulse cleaning system of candle ceramic filters. A standard turbulent model is demonstrated suitably to the designing computation of reverse pulse cle...Analytical and numerical computed models are developed for reverse pulse cleaning system of candle ceramic filters. A standard turbulent model is demonstrated suitably to the designing computation of reverse pulse cleaning system from the experimental and one dimensional computational result. The computed results can be used to guide the designing of reverse pulse cleaning system, which is optimum Venturi geometry. From the computed results, the general conclusions and the designing methods are obtained.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
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
Effectively handling imbalanced datasets remains a fundamental challenge in computational modeling and machine learning,particularly when class overlap significantly deteriorates classification performance.Traditional...Effectively handling imbalanced datasets remains a fundamental challenge in computational modeling and machine learning,particularly when class overlap significantly deteriorates classification performance.Traditional oversampling methods often generate synthetic samples without considering density variations,leading to redundant or misleading instances that exacerbate class overlap in high-density regions.To address these limitations,we propose Wasserstein Generative Adversarial Network Variational Density Estimation WGAN-VDE,a computationally efficient density-aware adversarial resampling framework that enhances minority class representation while strategically reducing class overlap.The originality of WGAN-VDE lies in its density-aware sample refinement,ensuring that synthetic samples are positioned in underrepresented regions,thereby improving class distinctiveness.By applying structured feature representation,targeted sample generation,and density-based selection mechanisms strategies,the proposed framework ensures the generation of well-separated and diverse synthetic samples,improving class separability and reducing redundancy.The experimental evaluation on 20 benchmark datasets demonstrates that this approach outperforms 11 state-of-the-art rebalancing techniques,achieving superior results in F1-score,Accuracy,G-Mean,and AUC metrics.These results establish the proposed method as an effective and robust computational approach,suitable for diverse engineering and scientific applications involving imbalanced data classification and computational modeling.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
In quadrupeds,the cervical and lumbar circuits work together to achieve the speed-dependent gait expression.While most studies have focused on how local lumbar circuits regulate limb coordination and gaits,relatively ...In quadrupeds,the cervical and lumbar circuits work together to achieve the speed-dependent gait expression.While most studies have focused on how local lumbar circuits regulate limb coordination and gaits,relatively few studies are known about cervical circuits and even less about locomotor gaits.We use the previously published models by Danner et al.(DANNER,S.M.,SHEVTSOVA,N.A.,FRIGON,A.,and RYBAK,I.A.Computational modeling of spinal circuits controlling limb coordination and gaits in quadrupeds.e Life,6,e31050(2017))as a basis,and modify it by proposing an asymmetric organization of cervical and lumbar circuits.First,the model reproduces the typical speed-dependent gait expression in mice and more biologically appropriate locomotor parameters,including the gallop gait,locomotor frequencies,and limb coordination of the forelimbs.Then,the model replicates the locomotor features regulated by the M-current.The walk frequency increases with the M-current without affecting the interlimb coordination or gaits.Furthermore,the model reveals the interaction mechanism between the brainstem drive and ionic currents in regulating quadrupedal locomotion.Finally,the model demonstrates the dynamical properties of locomotor gaits.Trot and bound are identified as attractor gaits,walk as a semi-attractor gait,and gallop as a transitional gait,with predictable transitions between these gaits.The model suggests that cervical-lumbar circuits are asymmetrically recruited during quadrupedal locomotion,thereby providing new insights into the neural control of speed-dependent gait expression.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
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
The mechanical properties of biological soft tissues play a critical role in the study of biomechanics and the development of protective measures against human injury.Various testing techniques at different scales hav...The mechanical properties of biological soft tissues play a critical role in the study of biomechanics and the development of protective measures against human injury.Various testing techniques at different scales have been employed to characterize the mechanical behavior of soft tissues,which is essential for developing accurate tissue simulants and numerical models.This review comprehensively explores the mechanical properties of soft tissues,examining experimental methods,mechanical models,numerical simulations,and the progress in materials that mimic the mechanical performance of soft tissues.Finally,it reviews the damage and protection of human tissues under kinetic impacts,anticipating the future construction of soft tissue surrogate targets.The aim is to provide a systematic theoretical foundation and the latest advancements in the field,addressing the design,preparation,and quantitative modeling of biomimetic materials,thereby promoting the in-depth development of soft tissue mechanics and its applications.展开更多
Among the existing research on the treatment of disorders of consciousness(DOC),deep brain stimulation(DBS)offers a highly promising therapeutic approach.This comprehensive review documents the historical development ...Among the existing research on the treatment of disorders of consciousness(DOC),deep brain stimulation(DBS)offers a highly promising therapeutic approach.This comprehensive review documents the historical development of DBS and its role in the treatment of DOC,tracing its progression from an experimental therapy to a detailed modulation approach based on the mesocircuit model hypothesis.The mesocircuit model hypothesis suggests that DOC arises from disruptions in a critical network of brain regions,providing a framework for refining DBS targets.We also discuss the multimodal approaches for assessing patients with DOC,encompassing clinical behavioral scales,electrophysiological assessment,and neuroimaging techniques methods.During the evolution of DOC therapy,the segmentation of central nuclei,the recording of single-neurons,and the analysis of local field potentials have emerged as favorable technical factors that enhance the efficacy of DBS treatment.Advances in computational models have also facilitated a deeper exploration of the neural dynamics associated with DOC,linking neuron-level dynamics with macroscopic behavioral changes.Despite showing promising outcomes,challenges remain in patient selection,precise target localization,and the determination of optimal stimulation parameters.Future research should focus on conducting large-scale controlled studies to delve into the pathophysiological mechanisms of DOC.It is imperative to further elucidate the precise modulatory effects of DBS on thalamo-cortical and cortico-cortical functional connectivity networks.Ultimately,by optimizing neuromodulation strategies,we aim to substantially enhance therapeutic outcomes and greatly expedite the process of consciousness recovery in patients.展开更多
In order to help athletes optimize their performances in competitions while prevent overtraining and the risk of overuse injuries,it is important to develop science-based strategies for optimally designing training pr...In order to help athletes optimize their performances in competitions while prevent overtraining and the risk of overuse injuries,it is important to develop science-based strategies for optimally designing training programs.The purpose of the present study is to develop a novel method by the combined use of optimal control theory and a training-performance model for designing optimal training programs,with the hope of helping athletes achieve the best performance exactly on the competition day while properly manage training load during the training course for preventing overtraining.The training-performance model used in the proposed optimal control framework is a conceptual extension of the Banister impulse-response model that describes the dynamics of performance,training load(served as the control variable),fitness(the overall positive effects on performance),and fatigue(the overall negative effects on performance).The objective functional of the proposed optimal control framework is to maximize the fitness and minimize the fatigue on the competition day with the goal of maximizing the performance on the competition day while minimizing the cumulative training load during the training course.The Forward-Backward Sweep Method is used to solve the proposed optimal control framework to obtain the optimal solutions of performance,training load,fitness,and fatigue.The simulation results show that the performance on the competition day is higher while the cumulative training load during the training course is lower with using optimal control theory than those without,successfully showing the feasibility and benefits of using the proposed optimal control framework to design optimal training programs for helping athletes achieve the best performance exactly on the competition day while properly manage training load during the training course for preventing overtraining.The present feasibility study lays the foundation of the combined use of optimal control theory and training-performance models to design personalized optimal training programs in real applications in athletic training and sports science for helping athletes achieve the best performances in competitions while prevent overtraining and the risk of overuse injuries.展开更多
To fundamentally alleviate the excavation chamber clogging during slurry tunnel boring machine(TBM)advancing in hard rock,large-diameter short screw conveyor was adopted to slurry TBM of Qingdao Jiaozhou Bay Second Un...To fundamentally alleviate the excavation chamber clogging during slurry tunnel boring machine(TBM)advancing in hard rock,large-diameter short screw conveyor was adopted to slurry TBM of Qingdao Jiaozhou Bay Second Undersea Tunnel.To evaluate the discharging performance of short screw conveyor in different cases,the full-scale transient slurry-rock two-phase model for a short screw conveyor actively discharging rocks was established using computational fluid dynamics-discrete element method(CFD-DEM)coupling approach.In the fluid domain of coupling model,the sliding mesh technology was utilized to describe the rotations of the atmospheric composite cutterhead and the short screw conveyor.In the particle domain of coupling model,the dynamic particle factories were established to produce rock particles with the rotation of the cutterhead.And the accuracy and reliability of the CFD-DEM simulation results were validated via the field test and model test.Furthermore,a comprehensive parameter analysis was conducted to examine the effects of TBM operating parameters,the geometric design of screw conveyor and the size of rocks on the discharging performance of short screw conveyor.Accordingly,a reasonable rotational speed of screw conveyor was suggested and applied to Jiaozhou Bay Second Undersea Tunnel project.The findings in this paper could provide valuable references for addressing the excavation chamber clogging during ultra-large-diameter slurry TBM tunneling in hard rock for similar future.展开更多
Objective To investigate the spike activities of cerebellar cortical cells in a computational network model con- structed based on the anatomical structure of cerebellar cortex. Methods and Results The multicompartmen...Objective To investigate the spike activities of cerebellar cortical cells in a computational network model con- structed based on the anatomical structure of cerebellar cortex. Methods and Results The multicompartment model of neuron and NEURON software were used to study the external influences on cerebellar cortical cells. Various potential spike patterns in these cells were obtained. By analyzing the impacts of different incoming stimuli on the potential spike of Purkinje cell, temporal focusing caused by the granule cell-golgi cell feedback inhibitory loop to Purkinje cell and spa- tial focusing caused by the parallel fiber-basket/stellate cell local inhibitory loop to Purkinje cell were discussed. Finally, the motor learning process of rabbit eye blink conditioned reflex was demonstrated in this model. The simulation results showed that when the afferent from climbing fiber existed, rabbit adaptation to eye blinking gradually became stable under the Spike Timing-Dependent Plasticity （STDP） learning rule. Conclusion The constructed cerebellar cortex network is a reliable and feasible model. The model simulation results confirmed the output signal stability of cerebellar cortex after STDP learning and the network can execute the function of spatial and temporal focusing.展开更多
Based on architecture analysis of island-style F PGA,area and delay models of LUT FPGA are proposed.The models are used to analyze the effect of LUT size on FPGA area and performance.Results show optimal LUT size obta...Based on architecture analysis of island-style F PGA,area and delay models of LUT FPGA are proposed.The models are used to analyze the effect of LUT size on FPGA area and performance.Results show optimal LUT size obtained by computation models is the same as that from experiments:a LUT size of 4 produces the best area results,and a LUT size of 5 provides the better performance.展开更多
With the rapid development of cloud computing,edge computing,and smart devices,computing power resources indicate a trend of ubiquitous deployment.The traditional network architecture cannot efficiently leverage these...With the rapid development of cloud computing,edge computing,and smart devices,computing power resources indicate a trend of ubiquitous deployment.The traditional network architecture cannot efficiently leverage these distributed computing power resources due to computing power island effect.To overcome these problems and improve network efficiency,a new network computing paradigm is proposed,i.e.,Computing Power Network(CPN).Computing power network can connect ubiquitous and heterogenous computing power resources through networking to realize computing power scheduling flexibly.In this survey,we make an exhaustive review on the state-of-the-art research efforts on computing power network.We first give an overview of computing power network,including definition,architecture,and advantages.Next,a comprehensive elaboration of issues on computing power modeling,information awareness and announcement,resource allocation,network forwarding,computing power transaction platform and resource orchestration platform is presented.The computing power network testbed is built and evaluated.The applications and use cases in computing power network are discussed.Then,the key enabling technologies for computing power network are introduced.Finally,open challenges and future research directions are presented as well.展开更多
A modified and improved primitive equation numerical model with p-sigma incorporated vertical coordinates is used to simulate the effects of different sea surface temperature distributions over the western Pacific on ...A modified and improved primitive equation numerical model with p-sigma incorporated vertical coordinates is used to simulate the effects of different sea surface temperature distributions over the western Pacific on the summer monsoon properties. The different sea surface temperature (SST) distributions are automatically generated in the time integrations by using two different SST models, one of which is called the deep ocean model (DOM) and the other the shallow ocean model (SOM). The SST generated by the DOM has the distribution pattern of the initial SST which is similar to the pattern in the cold water years over the western Pacific, while the SST generated by the SOM has the pattern similar to that in the warm water years. The differences between the experimental results by using DOM and SOM are analyzed in detail. The analyses indicate that the most basic and important characteristics of the summer monsoon climate can be simulated successfully in both experiments, that means the climatic properties in the monsoonal climate regions are mainly determined by the seasonal heating, the contrast between the land and the sea, the topography, and the physical properties of the underlying surfaces. However, the differences between the two experiments tell us that the climatic properties in the summer monsoon regions in the cold water year and the warm water year do differ from each other in details. In the warm water year, the thermal contrast between the land and the sea becomes weaker. Over the warm water area, the upward motions are induced and the dynamical conditions favorable for the convective activities are formed, the Somali low-level cross equatorial current is somewhat weakened, while the cross equatorial currents, east of 90°E, are strongly strengthened, the precipitation amount in the tropical regions largely increases, and the precipitation over the coastal regions increases, too. However the precipitation over the southeast China and its coastal area decreases. The precipitation amount mainly depends on the strength of the convective activity.展开更多
基金financially by the National Research Council of Thailand(NRCT)under Contract No.N42A670894.
文摘This study presents an innovative development of the exponentially weighted moving average(EWMA)control chart,explicitly adapted for the examination of time series data distinguished by seasonal autoregressive moving average behavior—SARMA(1,1)L under exponential white noise.Unlike previous works that rely on simplified models such as AR(1)or assume independence,this research derives for the first time an exact two-sided Average Run Length(ARL)formula for theModified EWMAchart under SARMA(1,1)L conditions,using a mathematically rigorous Fredholm integral approach.The derived formulas are validated against numerical integral equation(NIE)solutions,showing strong agreement and significantly reduced computational burden.Additionally,a performance comparison index(PCI)is introduced to assess the chart’s detection capability.Results demonstrate that the proposed method exhibits superior sensitivity to mean shifts in autocorrelated environments,outperforming existing approaches.The findings offer a new,efficient framework for real-time quality control in complex seasonal processes,with potential applications in environmental monitoring and intelligent manufacturing systems.
文摘The distribution of the various organic and inorganic constituents and their influences on the combustion of coal has been comprehensively studied.However,the combustion characteristics of pulverized coal depend not only on rank but also on the composition,distribution,and combination of the macerals.Unlike the proximate and ultimate analyses,determining the macerals in coal involves the use of sophisticated microscopic instrumentation and expertise.In this study,an attempt was made to predict the amount of macerals(vitrinite,inertinite,and liptinite)and total mineral matter from the Witbank Coalfields samples using the multiple input single output white-box artificial neural network(MISOWB-ANN),gene expression programming(GEP),multiple linear regression(MLR),and multiple nonlinear regression(MNLR).The predictive models obtained from the multiple soft computing models adopted are contrasted with one another using difference,efficiency,and composite statistical indicators to examine the appropriateness of the models.The MISOWB-ANN provides a more reliable predictive model than the other three models with the lowest difference and highest efficiency and composite statistical indicators.
文摘Cancer is a major stress for public well-being and is the most dreadful disease.The models used in the discovery of cancer treatment are continuously changing and extending toward advanced preclinical studies.Cancer models are either naturally existing or artificially prepared experimental systems that show similar features with human tumors though the heterogeneous nature of the tumor is very familiar.The choice of the most fitting model to best reflect the given tumor system is one of the real difficulties for cancer examination.Therefore,vast studies have been conducted on the cancer models for developing a better understanding of cancer invasion,progression,and early detection.These models give an insight into cancer etiology,molecular basis,host tumor interaction,the role of microenvironment,and tumor heterogeneity in tumor metastasis.These models are also used to predict novel can-cer markers,targeted therapies,and are extremely helpful in drug development.In this review,the potential of cancer models to be used as a platform for drug screening and therapeutic discoveries are highlighted.Although none of the cancer models is regarded as ideal because each is associated with essential caveats that restraint its application yet by bridging the gap between preliminary cancer research and transla-tional medicine.However,they promise a brighter future for cancer treatment.
基金TheNationalNaturalScienceFoundationofChina (No .5 9776 0 2 5 )andtheHi TechResearchandDevelopmentProgramofChina (S 86 3No.2 0 0 1AA3330 40 ) )
文摘Analytical and numerical computed models are developed for reverse pulse cleaning system of candle ceramic filters. A standard turbulent model is demonstrated suitably to the designing computation of reverse pulse cleaning system from the experimental and one dimensional computational result. The computed results can be used to guide the designing of reverse pulse cleaning system, which is optimum Venturi geometry. From the computed results, the general conclusions and the designing methods are obtained.
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.
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 Ongoing Research Funding Program(ORF-2025-488)King Saud University,Riyadh,Saudi Arabia.
文摘Effectively handling imbalanced datasets remains a fundamental challenge in computational modeling and machine learning,particularly when class overlap significantly deteriorates classification performance.Traditional oversampling methods often generate synthetic samples without considering density variations,leading to redundant or misleading instances that exacerbate class overlap in high-density regions.To address these limitations,we propose Wasserstein Generative Adversarial Network Variational Density Estimation WGAN-VDE,a computationally efficient density-aware adversarial resampling framework that enhances minority class representation while strategically reducing class overlap.The originality of WGAN-VDE lies in its density-aware sample refinement,ensuring that synthetic samples are positioned in underrepresented regions,thereby improving class distinctiveness.By applying structured feature representation,targeted sample generation,and density-based selection mechanisms strategies,the proposed framework ensures the generation of well-separated and diverse synthetic samples,improving class separability and reducing redundancy.The experimental evaluation on 20 benchmark datasets demonstrates that this approach outperforms 11 state-of-the-art rebalancing techniques,achieving superior results in F1-score,Accuracy,G-Mean,and AUC metrics.These results establish the proposed method as an effective and robust computational approach,suitable for diverse engineering and scientific applications involving imbalanced data classification and computational modeling.
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Project supported by the National Natural Science Foundation of China(Nos.12272092 and 12332004)。
文摘In quadrupeds,the cervical and lumbar circuits work together to achieve the speed-dependent gait expression.While most studies have focused on how local lumbar circuits regulate limb coordination and gaits,relatively few studies are known about cervical circuits and even less about locomotor gaits.We use the previously published models by Danner et al.(DANNER,S.M.,SHEVTSOVA,N.A.,FRIGON,A.,and RYBAK,I.A.Computational modeling of spinal circuits controlling limb coordination and gaits in quadrupeds.e Life,6,e31050(2017))as a basis,and modify it by proposing an asymmetric organization of cervical and lumbar circuits.First,the model reproduces the typical speed-dependent gait expression in mice and more biologically appropriate locomotor parameters,including the gallop gait,locomotor frequencies,and limb coordination of the forelimbs.Then,the model replicates the locomotor features regulated by the M-current.The walk frequency increases with the M-current without affecting the interlimb coordination or gaits.Furthermore,the model reveals the interaction mechanism between the brainstem drive and ionic currents in regulating quadrupedal locomotion.Finally,the model demonstrates the dynamical properties of locomotor gaits.Trot and bound are identified as attractor gaits,walk as a semi-attractor gait,and gallop as a transitional gait,with predictable transitions between these gaits.The model suggests that cervical-lumbar circuits are asymmetrically recruited during quadrupedal locomotion,thereby providing new insights into the neural control of speed-dependent gait expression.
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 No.U2241273)the Beijing Municipal Natural Science Foundation(Grant No.Z240017)+3 种基金the 111 project(Grant No.B13003)the Fundamental Research Funds for the Central Universitiesthe China Scholarship Councilthe Academic Excellence Foundation of BUAA for PhD Students.
文摘The mechanical properties of biological soft tissues play a critical role in the study of biomechanics and the development of protective measures against human injury.Various testing techniques at different scales have been employed to characterize the mechanical behavior of soft tissues,which is essential for developing accurate tissue simulants and numerical models.This review comprehensively explores the mechanical properties of soft tissues,examining experimental methods,mechanical models,numerical simulations,and the progress in materials that mimic the mechanical performance of soft tissues.Finally,it reviews the damage and protection of human tissues under kinetic impacts,anticipating the future construction of soft tissue surrogate targets.The aim is to provide a systematic theoretical foundation and the latest advancements in the field,addressing the design,preparation,and quantitative modeling of biomimetic materials,thereby promoting the in-depth development of soft tissue mechanics and its applications.
基金supported by the Science and Technology Innovation 2030(2022ZD0205300)the International(Hong Kong,Macao,and Taiwan)Science and Technology Cooperation Project(Z221100002722014)+5 种基金the 2022 Open Project of Key Laboratory and Engineering Technology Research of the Ministry of Civil Affairs(2022GKZS0003)the Chinese Institute for Brain Research Youth Scholar Program(2022-NKX-XM-02)the Natural Science Foundation of Beijing municipality(7232049)the General Program of National Natural Science Foundation of China(82371197)the FundRef Organization name of Guarantors of Brain(HMR04170)the Royal Society(IES\R3\213123).
文摘Among the existing research on the treatment of disorders of consciousness(DOC),deep brain stimulation(DBS)offers a highly promising therapeutic approach.This comprehensive review documents the historical development of DBS and its role in the treatment of DOC,tracing its progression from an experimental therapy to a detailed modulation approach based on the mesocircuit model hypothesis.The mesocircuit model hypothesis suggests that DOC arises from disruptions in a critical network of brain regions,providing a framework for refining DBS targets.We also discuss the multimodal approaches for assessing patients with DOC,encompassing clinical behavioral scales,electrophysiological assessment,and neuroimaging techniques methods.During the evolution of DOC therapy,the segmentation of central nuclei,the recording of single-neurons,and the analysis of local field potentials have emerged as favorable technical factors that enhance the efficacy of DBS treatment.Advances in computational models have also facilitated a deeper exploration of the neural dynamics associated with DOC,linking neuron-level dynamics with macroscopic behavioral changes.Despite showing promising outcomes,challenges remain in patient selection,precise target localization,and the determination of optimal stimulation parameters.Future research should focus on conducting large-scale controlled studies to delve into the pathophysiological mechanisms of DOC.It is imperative to further elucidate the precise modulatory effects of DBS on thalamo-cortical and cortico-cortical functional connectivity networks.Ultimately,by optimizing neuromodulation strategies,we aim to substantially enhance therapeutic outcomes and greatly expedite the process of consciousness recovery in patients.
基金funded by the National Science and Technology Council,grant number NSTC 113-2221-E-002-136-.
文摘In order to help athletes optimize their performances in competitions while prevent overtraining and the risk of overuse injuries,it is important to develop science-based strategies for optimally designing training programs.The purpose of the present study is to develop a novel method by the combined use of optimal control theory and a training-performance model for designing optimal training programs,with the hope of helping athletes achieve the best performance exactly on the competition day while properly manage training load during the training course for preventing overtraining.The training-performance model used in the proposed optimal control framework is a conceptual extension of the Banister impulse-response model that describes the dynamics of performance,training load(served as the control variable),fitness(the overall positive effects on performance),and fatigue(the overall negative effects on performance).The objective functional of the proposed optimal control framework is to maximize the fitness and minimize the fatigue on the competition day with the goal of maximizing the performance on the competition day while minimizing the cumulative training load during the training course.The Forward-Backward Sweep Method is used to solve the proposed optimal control framework to obtain the optimal solutions of performance,training load,fitness,and fatigue.The simulation results show that the performance on the competition day is higher while the cumulative training load during the training course is lower with using optimal control theory than those without,successfully showing the feasibility and benefits of using the proposed optimal control framework to design optimal training programs for helping athletes achieve the best performance exactly on the competition day while properly manage training load during the training course for preventing overtraining.The present feasibility study lays the foundation of the combined use of optimal control theory and training-performance models to design personalized optimal training programs in real applications in athletic training and sports science for helping athletes achieve the best performances in competitions while prevent overtraining and the risk of overuse injuries.
基金supported by the Fundamental Research Funds for the Central Universities(Grant No.2023YJS053)the National Natural Science Foundation of China(Grant No.52278386).
文摘To fundamentally alleviate the excavation chamber clogging during slurry tunnel boring machine(TBM)advancing in hard rock,large-diameter short screw conveyor was adopted to slurry TBM of Qingdao Jiaozhou Bay Second Undersea Tunnel.To evaluate the discharging performance of short screw conveyor in different cases,the full-scale transient slurry-rock two-phase model for a short screw conveyor actively discharging rocks was established using computational fluid dynamics-discrete element method(CFD-DEM)coupling approach.In the fluid domain of coupling model,the sliding mesh technology was utilized to describe the rotations of the atmospheric composite cutterhead and the short screw conveyor.In the particle domain of coupling model,the dynamic particle factories were established to produce rock particles with the rotation of the cutterhead.And the accuracy and reliability of the CFD-DEM simulation results were validated via the field test and model test.Furthermore,a comprehensive parameter analysis was conducted to examine the effects of TBM operating parameters,the geometric design of screw conveyor and the size of rocks on the discharging performance of short screw conveyor.Accordingly,a reasonable rotational speed of screw conveyor was suggested and applied to Jiaozhou Bay Second Undersea Tunnel project.The findings in this paper could provide valuable references for addressing the excavation chamber clogging during ultra-large-diameter slurry TBM tunneling in hard rock for similar future.
基金supported by the grants from National Natural Science Foundation of China (No. 10872069)
文摘Objective To investigate the spike activities of cerebellar cortical cells in a computational network model con- structed based on the anatomical structure of cerebellar cortex. Methods and Results The multicompartment model of neuron and NEURON software were used to study the external influences on cerebellar cortical cells. Various potential spike patterns in these cells were obtained. By analyzing the impacts of different incoming stimuli on the potential spike of Purkinje cell, temporal focusing caused by the granule cell-golgi cell feedback inhibitory loop to Purkinje cell and spa- tial focusing caused by the parallel fiber-basket/stellate cell local inhibitory loop to Purkinje cell were discussed. Finally, the motor learning process of rabbit eye blink conditioned reflex was demonstrated in this model. The simulation results showed that when the afferent from climbing fiber existed, rabbit adaptation to eye blinking gradually became stable under the Spike Timing-Dependent Plasticity （STDP） learning rule. Conclusion The constructed cerebellar cortex network is a reliable and feasible model. The model simulation results confirmed the output signal stability of cerebellar cortex after STDP learning and the network can execute the function of spatial and temporal focusing.
文摘Based on architecture analysis of island-style F PGA,area and delay models of LUT FPGA are proposed.The models are used to analyze the effect of LUT size on FPGA area and performance.Results show optimal LUT size obtained by computation models is the same as that from experiments:a LUT size of 4 produces the best area results,and a LUT size of 5 provides the better performance.
基金supported by the National Science Foundation of China under Grant 62271062 and 62071063by the Zhijiang Laboratory Open Project Fund 2020LCOAB01。
文摘With the rapid development of cloud computing,edge computing,and smart devices,computing power resources indicate a trend of ubiquitous deployment.The traditional network architecture cannot efficiently leverage these distributed computing power resources due to computing power island effect.To overcome these problems and improve network efficiency,a new network computing paradigm is proposed,i.e.,Computing Power Network(CPN).Computing power network can connect ubiquitous and heterogenous computing power resources through networking to realize computing power scheduling flexibly.In this survey,we make an exhaustive review on the state-of-the-art research efforts on computing power network.We first give an overview of computing power network,including definition,architecture,and advantages.Next,a comprehensive elaboration of issues on computing power modeling,information awareness and announcement,resource allocation,network forwarding,computing power transaction platform and resource orchestration platform is presented.The computing power network testbed is built and evaluated.The applications and use cases in computing power network are discussed.Then,the key enabling technologies for computing power network are introduced.Finally,open challenges and future research directions are presented as well.
基金Supported by the National Fundamental Key Research:"studies on climate dynamics and climate prediction theory."
文摘A modified and improved primitive equation numerical model with p-sigma incorporated vertical coordinates is used to simulate the effects of different sea surface temperature distributions over the western Pacific on the summer monsoon properties. The different sea surface temperature (SST) distributions are automatically generated in the time integrations by using two different SST models, one of which is called the deep ocean model (DOM) and the other the shallow ocean model (SOM). The SST generated by the DOM has the distribution pattern of the initial SST which is similar to the pattern in the cold water years over the western Pacific, while the SST generated by the SOM has the pattern similar to that in the warm water years. The differences between the experimental results by using DOM and SOM are analyzed in detail. The analyses indicate that the most basic and important characteristics of the summer monsoon climate can be simulated successfully in both experiments, that means the climatic properties in the monsoonal climate regions are mainly determined by the seasonal heating, the contrast between the land and the sea, the topography, and the physical properties of the underlying surfaces. However, the differences between the two experiments tell us that the climatic properties in the summer monsoon regions in the cold water year and the warm water year do differ from each other in details. In the warm water year, the thermal contrast between the land and the sea becomes weaker. Over the warm water area, the upward motions are induced and the dynamical conditions favorable for the convective activities are formed, the Somali low-level cross equatorial current is somewhat weakened, while the cross equatorial currents, east of 90°E, are strongly strengthened, the precipitation amount in the tropical regions largely increases, and the precipitation over the coastal regions increases, too. However the precipitation over the southeast China and its coastal area decreases. The precipitation amount mainly depends on the strength of the convective activity.
