Three-dimensional (3D) visualization of dynamic biological processes in deep tissue remains challenging due to the trade-off between temporal resolution and imaging depth. Here, we present a novel near-infrared-II (NI...Three-dimensional (3D) visualization of dynamic biological processes in deep tissue remains challenging due to the trade-off between temporal resolution and imaging depth. Here, we present a novel near-infrared-II (NIR-II, 900–1880nm) fluorescence volumetric microscopic imaging method that combines an electrically tunable lens (ETL) with deep learning approaches for rapid 3D imaging. The technology achieves volumetric imaging at 4.2 frames per second (fps) across a 200 μm depth range in live mouse brain vasculature. Two specialized neural networks are utilized: a scale-recurrent network (SRN) for image enhancement and a cerebral vessel interpolation (CVI) network that enables 16-fold axial upsampling. The SRN, trained on two-photon fluorescence microscopic data, improves both lateral and axial resolution of NIR-II fluorescence wide-field microscopic images. The CVI network, adapted from video interpolation techniques, generates intermediate frames between acquired axial planes, resulting in smooth and continuous 3D vessel reconstructions. Using this integrated system, we visualize and quantify blood flow dynamics in individual vessels and are capable of measuring blood velocity at different depths. This approach maintains high lateral resolution while achieving rapid volumetric imaging, and is particularly suitable for studying dynamic vascular processes in deep tissue. Our method demonstrates the potential of combining optical engineering with artificial intelligence to advance biological imaging capabilities.展开更多
Rheumatoid arthritis(RA)patients face significant psychological challenges alongside physical symptoms,necessitating a comprehensive understanding of how psychological vulnerability and adaptation patterns evolve thro...Rheumatoid arthritis(RA)patients face significant psychological challenges alongside physical symptoms,necessitating a comprehensive understanding of how psychological vulnerability and adaptation patterns evolve throughout the disease course.This review examined 95 studies(2000-2025)from PubMed,Web of Science,and CNKI databases including longitudinal cohorts,randomized controlled trials,and mixed-methods research,to characterize the complex interplay between biological,psychological,and social factors affecting RA patients’mental health.Findings revealed three distinct vulnerability trajectories(45%persistently low,30%fluctuating improvement,25%persistently high)and four adaptation stages,with critical intervention periods occurring 3-6 months postdiagnosis and during disease flares.Multiple factors significantly influence psychological outcomes,including gender(females showing 1.8-fold increased risk),age(younger patients experiencing 42%higher vulnerability),pain intensity,inflammatory markers,and neuroendocrine dysregulation(48%showing cortisol rhythm disruption).Early psychological intervention(within 3 months of diagnosis)demonstrated robust benefits,reducing depression incidence by 42%with effects persisting 24-36 months,while different modalities showed complementary advantages:Cognitive behavioral therapy for depression(Cohen’s d=0.68),mindfulness for pain acceptance(38%improvement),and peer support for meaning reconstruction(25.6%increase).These findings underscore the importance of integrating routine psychological assessment into standard RA care,developing stage-appropriate interventions,and advancing research toward personalized biopsychosocial approaches that address the dynamic psychological dimensions of the disease.展开更多
Pulsed dynamic electrolysis(PDE),driven by renewable energy,has emerged as an innovative electrocatalytic conversion method,demonstrating significant potential in addressing global energy challenges and promoting sust...Pulsed dynamic electrolysis(PDE),driven by renewable energy,has emerged as an innovative electrocatalytic conversion method,demonstrating significant potential in addressing global energy challenges and promoting sustainable development.Despite significant progress in various electrochemical systems,the regulatory mechanisms of PDE in energy and mass transfer and the lifespan extension of electrolysis systems,particularly in water electrolysis(WE)for hydrogen production,remain insufficiently explored.Therefore,there is an urgent need for a deeper understanding of the unique contributions of PDE in mass transfer enhancement,microenvironment regulation,and hydrogen production optimization,aiming to achieve low-energy consumption,high catalytic activity,and long-term stability in the generation of target products.Here,this review critically examines the microenvironmental effects of PDE on energy and mass transfer,the electrode degradation mechanisms in the lifespan extension of electrolysis systems,and the key factors in enhancing WE for hydrogen production,providing a comprehensive summary of current research progress.The review focuses on the complex regulatory mechanisms of frequency,duty cycle,amplitude,and other factors in hydrogen evolution reaction(HER)performance within PDE strategies,revealing the interrelationships among them.Finally,the potential future directions and challenges for transitioning from laboratory studies to industrial applications are proposed.展开更多
The application of nitrogen fertilizers in agricultural fields can lead to the release of nitrogen-containing gases(NCGs),such as NO_(x),NH_(3) and N_(2)O,which can significantly impact regional atmospheric environmen...The application of nitrogen fertilizers in agricultural fields can lead to the release of nitrogen-containing gases(NCGs),such as NO_(x),NH_(3) and N_(2)O,which can significantly impact regional atmospheric environment and con-tribute to global climate change.However,there remain considerable research gaps in the accurate measurement of NCGs emissions from agricultural fields,hindering the development of effective emission reduction strategies.We improved an open-top dynamic chambers(OTDCs)system and evaluated the performance by comparing the measured and given fluxes of the NCGs.The results showed that the measured fluxes of NO,N_(2)O and NH_(3)were 1%,2%and 7%lower than the given fluxes,respectively.For the determination of NH_(3) concentration,we employed a stripping coil-ion chromatograph(SC-IC)analytical technique,which demonstrated an absorption efficiency for atmospheric NH_(3) exceeding 96.1%across sampling durations of 6 to 60 min.In the summer maize season,we utilized the OTDCs system to measure the exchange fluxes of NO,NH_(3),and N_(2)O from the soil in the North China Plain.Substantial emissions of NO,NH_(3) and N_(2)O were recorded following fertilization,with peaks of 107,309,1239 ng N/(m^(2)·s),respectively.Notably,significant NCGs emissions were observed following sus-tained heavy rainfall one month after fertilization,particularly with NH_(3) peak being 4.5 times higher than that observed immediately after fertilization.Our results demonstrate that the OTDCs system accurately reflects the emission characteristics of soil NCGs and meets the requirements for long-term and continuous flux observation.展开更多
This paper prepared a novel as-cast W-Zr-Ti metallic ESM using high-frequency vacuum induction melting technique.The above ESM performs a typical elastic-brittle material feature and strain rate strengthening behavior...This paper prepared a novel as-cast W-Zr-Ti metallic ESM using high-frequency vacuum induction melting technique.The above ESM performs a typical elastic-brittle material feature and strain rate strengthening behavior.The specimens exhibit violent chemical reaction during the fracture process under the impact loading,and the size distribution of their residual debris follows Rosin-Rammler model.The dynamic fracture toughness is obtained by the fitting of debris length scale,approximately 1.87 MPa·m~(1/2).Microstructure observation on residual debris indicates that the failure process is determined by primary crack propagation under quasi-static compression,while it is affected by multiple cracks propagation in both particle and matrix in the case of dynamic impact.Impact test demonstrates that the novel energetic fragment performs brilliant penetration and combustion effect behind the front target,leading to the effective ignition of fuel tank.For the brittleness of as-cast W-ZrTi ESM,further study conducted bond-based peridynamic(BB-PD)C++computational code to simulate its fracture behavior during penetration.The BB-PD method successfully captured the fracture process and debris cloud formation of the energetic fragment.This paper explores a novel as-cast metallic ESM,and provides an available numerical avenue to the simulation of brittle energetic fragment.展开更多
To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework ba...To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.展开更多
Conductive elastomers combining micromechanical sensitivity,lightweight adaptability,and environmental sustainability are critically needed for advanced flexible electronics requiring precise responsiveness and long-t...Conductive elastomers combining micromechanical sensitivity,lightweight adaptability,and environmental sustainability are critically needed for advanced flexible electronics requiring precise responsiveness and long-term wearability;however,the integration of these properties remains a significant challenge.Here,we present a biomass-derived conductive elastomer featuring a rationally engineered dynamic crosslinked network integrated with a tunable microporous architecture.This structural design imparts pronounced micromechanical sensitivity,an ultralow density(~0.25 g cm^(−3)),and superior mechanical compliance for adaptive deformation.Moreover,the unique micro-spring effect derived from the porous architecture ensures exceptional stretchability(>500%elongation at break)and superior resilience,delivering immediate and stable electrical response under both subtle(<1%)and large(>200%)mechanical stimuli.Intrinsic dynamic interactions endow the elastomer with efficient room temperature self-healing and complete recyclability without compromising performance.First-principles simulations clarify the mechanisms behind micropore formation and the resulting functionality.Beyond its facile and mild fabrication process,this work establishes a scalable route toward high-performance,sustainable conductive elastomers tailored for next-generation soft electronics.展开更多
Composite polymer electrolytes(CPEs)offer a promising solution for all-solid-state lithium-metal batteries(ASSLMBs).However,conventional nanofillers with Lewis-acid-base surfaces make limited contribution to improving...Composite polymer electrolytes(CPEs)offer a promising solution for all-solid-state lithium-metal batteries(ASSLMBs).However,conventional nanofillers with Lewis-acid-base surfaces make limited contribution to improving the overall performance of CPEs due to their difficulty in achieving robust electrochemical and mechanical interfaces simultaneously.Here,by regulating the surface charge characteristics of halloysite nanotube(HNT),we propose a concept of lithium-ion dynamic interface(Li^(+)-DI)engineering in nano-charged CPE(NCCPE).Results show that the surface charge characteristics of HNTs fundamentally change the Li^(+)-DI,and thereof the mechanical and ion-conduction behaviors of the NCCPEs.Particularly,the HNTs with positively charged surface(HNTs+)lead to a higher Li^(+)transference number(0.86)than that of HNTs-(0.73),but a lower toughness(102.13 MJ m^(-3)for HNTs+and 159.69 MJ m^(-3)for HNTs-).Meanwhile,a strong interface compatibilization effect by Li^(+)is observed for especially the HNTs+-involved Li^(+)-DI,which improves the toughness by 2000%compared with the control.Moreover,HNTs+are more effective to weaken the Li^(+)-solvation strength and facilitate the formation of Li F-rich solid-electrolyte interphase of Li metal compared to HNTs-.The resultant Li|NCCPE|LiFePO4cell delivers a capacity of 144.9 m Ah g^(-1)after 400 cycles at 0.5 C and a capacity retention of 78.6%.This study provides deep insights into understanding the roles of surface charges of nanofillers in regulating the mechanical and electrochemical interfaces in ASSLMBs.展开更多
Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating In...Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating Interactive Dynamic Graph Convolution Network(IDGCN)with Temporal Multi-Head Trend-Aware Attention.Its core innovation lies in IDGCN,which uniquely splits sequences into symmetric intervals for interactive feature sharing via dynamic graphs,and a novel attention mechanism incorporating convolutional operations to capture essential local traffic trends—addressing a critical gap in standard attention for continuous data.For 15-and 60-min forecasting on METR-LA,AIDGCN achieves MAEs of 0.75%and 0.39%,and RMSEs of 1.32%and 0.14%,respectively.In the 60-min long-term forecasting of the PEMS-BAY dataset,the AIDGCN out-performs the MRA-BGCN method by 6.28%,4.93%,and 7.17%in terms of MAE,RMSE,and MAPE,respectively.Experimental results demonstrate the superiority of our pro-posed model over state-of-the-art methods.展开更多
Lateral movement represents the most covert and critical phase of Advanced Persistent Threats(APTs),and its detection still faces two primary challenges:sample scarcity and“cold start”of new entities.To address thes...Lateral movement represents the most covert and critical phase of Advanced Persistent Threats(APTs),and its detection still faces two primary challenges:sample scarcity and“cold start”of new entities.To address these challenges,we propose an Uncertainty-Driven Graph Embedding-Enhanced Lateral Movement Detection framework(UGEA-LMD).First,the framework employs event-level incremental encoding on a continuous-time graph to capture fine-grained behavioral evolution,enabling newly appearing nodes to retain temporal contextual awareness even in the absence of historical interactions and thereby fundamentally mitigating the cold-start problem.Second,in the embedding space,we model the dependency structure among feature dimensions using a Gaussian copula to quantify the uncertainty distribution,and generate augmented samples with consistent structural and semantic properties through adaptive sampling,thus expanding the representation space of sparse samples and enhancing the model’s generalization under sparse sample conditions.Unlike static graph methods that cannot model temporal dependencies or data augmentation techniques that depend on predefined structures,UGEA-LMD offers both superior temporaldynamic modeling and structural generalization.Experimental results on the large-scale LANL log dataset demonstrate that,under the transductive setting,UGEA-LMD achieves an AUC of 0.9254;even when 10%of nodes or edges are withheld during training,UGEA-LMD significantly outperforms baseline methods on metrics such as recall and AUC,confirming its robustness and generalization capability in sparse-sample and cold-start scenarios.展开更多
THE mechanical response and deformation mechanisms of pure nickel under nanoindentation were systematically investigated using molecular dynamics(MD)simulations,with a particular focus on the novel interplay between c...THE mechanical response and deformation mechanisms of pure nickel under nanoindentation were systematically investigated using molecular dynamics(MD)simulations,with a particular focus on the novel interplay between crystallographic orientation,grain boundary(GB)proximity,and pore characteristics(size/location).This study compares single-crystal nickel models along[100],[110],and[111]orientations with equiaxed polycrystalline models containing 0,1,and 2.5 nm pores in surface and subsurface configurations.Our results reveal that crystallographic anisotropy manifests as a 24.4%higher elastic modulus and 22.2%greater hardness in[111]-oriented single crystals compared to[100].Pore-GB synergistic effects are found to dominate the deformation behavior:2.5 nm subsurface pores reduce hardness by 25.2%through stress concentration and dislocation annihilation at GBs,whereas surface pores enable mechanical recovery via accelerated dislocation generation post-collapse.Additionally,size-dependent deformation regimes were identified,with 1 nm pores inducing negligible perturbation due to rapid atomic rearrangement,in contrast with persistent softening in 2.5 nm pores.These findings establish atomic-scale design principles for defect engineering in nickel-based aerospace components,demonstrating how crystallographic orientation,pore configuration,and GB interactions collectively govern nanoindentation behavior.展开更多
Organic electrochemical transistor(OECT)devices demonstrate great promising potential for reservoir computing(RC)systems,but their lack of tunable dynamic characteristics limits their application in multi-temporal sca...Organic electrochemical transistor(OECT)devices demonstrate great promising potential for reservoir computing(RC)systems,but their lack of tunable dynamic characteristics limits their application in multi-temporal scale tasks.In this study,we report an OECT-based neuromorphic device with tunable relaxation time(τ)by introducing an additional vertical back-gate electrode into a planar structure.The dual-gate design enablesτreconfiguration from 93 to 541 ms.The tunable relaxation behaviors can be attributed to the combined effects of planar-gate induced electrochemical doping and back-gateinduced electrostatic coupling,as verified by electrochemical impedance spectroscopy analysis.Furthermore,we used theτ-tunable OECT devices as physical reservoirs in the RC system for intelligent driving trajectory prediction,achieving a significant improvement in prediction accuracy from below 69%to 99%.The results demonstrate that theτ-tunable OECT shows a promising candidate for multi-temporal scale neuromorphic computing applications.展开更多
Photo-assisted lithium–sulfur batteries(PALSBs)offer an eco-friendly solution to address the issue of sluggish reaction kinetics of conventional LSBs.However,designing an efficient photoelectrode for practical implem...Photo-assisted lithium–sulfur batteries(PALSBs)offer an eco-friendly solution to address the issue of sluggish reaction kinetics of conventional LSBs.However,designing an efficient photoelectrode for practical implementation remains a significant challenge.Herein,we construct a free-standing polymer–inorganic hybrid photoelectrode with a direct Z-scheme heterostructure to develop high-efficiency PALSBs.Specifically,polypyrrole(PPy)is in situ vapor-phase polymerized on the surface of N-doped TiO_(2) nanorods supported on carbon cloth(N-TiO_(2)/CC),thereby forming a well-defined p–n heterojunction.This architecture efficiently facilitates the carrier separation of photo-generated electron–hole pairs and significantly enhances carrier transport by creating a built-in electric field.Thus,the PPy@N-TiO_(2)/CC can simultaneously act as a photocatalyst and an electrocatalyst to accelerate the reduction and evolution of sulfur,enabling ultrafast sulfur redox dynamics,as convincingly validated by both theoretical simulations and experimental results.Consequently,the PPy@N-TiO_(2)/CC PALSB achieves a high discharge capacity of 1653 mAh g−1,reaching 98.7%of the theoretical value.Furthermore,5 h of photo-charging without external voltage enables the PALSB to deliver a discharge capacity of 333 mAh g−1,achieving dual-mode energy harvesting capabilities.This work successfully integrates solar energy conversion and storage within a rechargeable battery system,providing a promising strategy for sustainable energy storage technologies.展开更多
Compared to the well-studied two-dimensional(2D)ferroelectricity,the appearance of 2D antiferroelectricity is much rarer,where local dipoles from the nonequivalent sublattices within 2D monolayers are oppositely orien...Compared to the well-studied two-dimensional(2D)ferroelectricity,the appearance of 2D antiferroelectricity is much rarer,where local dipoles from the nonequivalent sublattices within 2D monolayers are oppositely oriented.Using NbOCl_(2) monolayer with competing ferroelectric(FE)and antiferroelectric(AFE)phases as a 2D material platform,we demonstrate the emergence of intrinsic antiferroelectricity in NbOCl_(2) monolayer under experimentally accessible shear strain,along with new functionality associated with electric field-induced AFE-to-FE phase transition.Specifically,the complex configuration space accommodating FE and AFE phases,polarization switching kinetics,and finite temperature thermodynamic properties of 2D NbOCl_(2) are all accurately predicted by large-scale molecular dynamics simulations based on deep learning interatomic potential model.Moreover,room temperature stable antiferroelectricity with low polarization switching barrier and one-dimensional collinear polarization arrangement is predicted in shear-deformed NbOCl_(2) monolayer.The transition from AFE to FE phase in 2D NbOCl_(2) can be triggered by a low critical electric field,leading to a double polarization–electric(P–E)loop with small hysteresis.A new type of optoelectronic device composed of AFE-NbOCl_(2) is proposed,enabling electric“writing”and nonlinear optical“reading”logical operation with fast operation speed and low power consumption.展开更多
Mitochondrial dysfunction has emerged as a critical factor in the etiology of various neurodevelopmental disorders, including autism spectrum disorders, attention-deficit/hyperactivity disorder, and Rett syndrome. Alt...Mitochondrial dysfunction has emerged as a critical factor in the etiology of various neurodevelopmental disorders, including autism spectrum disorders, attention-deficit/hyperactivity disorder, and Rett syndrome. Although these conditions differ in clinical presentation, they share fundamental pathological features that may stem from abnormal mitochondrial dynamics and impaired autophagic clearance, which contribute to redox imbalance and oxidative stress in neurons. This review aimed to elucidate the relationship between mitochondrial dynamics dysfunction and neurodevelopmental disorders. Mitochondria are highly dynamic organelles that undergo continuous fusion and fission to meet the substantial energy demands of neural cells. Dysregulation of these processes, as observed in certain neurodevelopmental disorders, causes accumulation of damaged mitochondria, exacerbating oxidative damage and impairing neuronal function. The phosphatase and tensin homolog-induced putative kinase 1/E3 ubiquitin-protein ligase pathway is crucial for mitophagy, the process of selectively removing malfunctioning mitochondria. Mutations in genes encoding mitochondrial fusion proteins have been identified in autism spectrum disorders, linking disruptions in the fusion-fission equilibrium to neurodevelopmental impairments. Additionally, animal models of Rett syndrome have shown pronounced defects in mitophagy, reinforcing the notion that mitochondrial quality control is indispensable for neuronal health. Clinical studies have highlighted the importance of mitochondrial disturbances in neurodevelopmental disorders. In autism spectrum disorders, elevated oxidative stress markers and mitochondrial DNA deletions indicate compromised mitochondrial function. Attention-deficit/hyperactivity disorder has also been associated with cognitive deficits linked to mitochondrial dysfunction and oxidative stress. Moreover, induced pluripotent stem cell models derived from patients with Rett syndrome have shown impaired mitochondrial dynamics and heightened vulnerability to oxidative injury, suggesting the role of defective mitochondrial homeostasis in these disorders. From a translational standpoint, multiple therapeutic approaches targeting mitochondrial pathways show promise. Interventions aimed at preserving normal fusion-fission cycles or enhancing mitophagy can reduce oxidative damage by limiting the accumulation of defective mitochondria. Pharmacological modulation of mitochondrial permeability and upregulation of peroxisome proliferator-activated receptor gamma coactivator 1-alpha, an essential regulator of mitochondrial biogenesis, may also ameliorate cellular energy deficits. Identifying early biomarkers of mitochondrial impairment is crucial for precision medicine, since it can help clinicians tailor interventions to individual patient profiles and improve prognoses. Furthermore, integrating mitochondria-focused strategies with established therapies, such as antioxidants or behavioral interventions, may enhance treatment efficacy and yield better clinical outcomes. Leveraging these pathways could open avenues for regenerative strategies, given the influence of mitochondria on neuronal repair and plasticity. In conclusion, this review indicates mitochondrial homeostasis as a unifying therapeutic axis within neurodevelopmental pathophysiology. Disruptions in mitochondrial dynamics and autophagic clearance converge on oxidative stress, and researchers should prioritize validating these interventions in clinical settings to advance precision medicine and enhance outcomes for individuals affected by neurodevelopmental disorders.展开更多
A 3D compressible nonhydrostatic dynamic core based on a three-point multi-moment constrained finite-volume (MCV) method is developed by extending the previous 2D nonhydrostatic atmospheric dynamics to 3D on a terrain...A 3D compressible nonhydrostatic dynamic core based on a three-point multi-moment constrained finite-volume (MCV) method is developed by extending the previous 2D nonhydrostatic atmospheric dynamics to 3D on a terrainfollowing grid. The MCV algorithm defines two types of moments: the point-wise value (PV) and the volume-integrated average (VIA). The unknowns (PV values) are defined at the solution points within each cell and are updated through the time evolution formulations derived from the governing equations. Rigorous numerical conservation is ensured by a constraint on the VIA moment through the flux form formulation. The 3D atmospheric dynamic core reported in this paper is based on a three-point MCV method and has some advantages in comparison with other existing methods, such as uniform third-order accuracy, a compact stencil, and algorithmic simplicity. To check the performance of the 3D nonhydrostatic dynamic core, various benchmark test cases are performed. All the numerical results show that the present dynamic core is very competitive when compared to other existing advanced models, and thus lays the foundation for further developing global atmospheric models in the near future.展开更多
Hydraulic circuits with high speed on/off valve(HSV)for servo control have become commonplace in aerospace.However,the individual valve that is not volume-optimized results in a large total size of hydraulic control s...Hydraulic circuits with high speed on/off valve(HSV)for servo control have become commonplace in aerospace.However,the individual valve that is not volume-optimized results in a large total size of hydraulic control system,diminishing the practicality.To address this issue,the high-precision equivalent reluctance model of the HSV is established by employing an equivalent magnetic circuit,on which the dynamic characteristic of the HSV,as well as the effects of structural parameters on switching behaviour,are investigated.Based on this model,multi-objective optimization is adopted to design an HSV with faster dynamic performance and smaller volume,NSGA-II genetic algorithm is applied to obtain the Pareto front of the desired objectives.To assess the impact before and after optimization,an HSV based on the optimized structure is manufactured and tested.The experimental results show that the optimized HSV reduces 47.1%of its solenoid volume while improving opening and closing dynamic performance by 14.8%and 43.0%respectively,increasing maximum switching frequency by 6.2%,and expanding flow linear control area by 6.7%.These results validate the optimized structure and indicate that the optimization method provided in the paper is beneficial for developing superior HSV.展开更多
The cardiovascular system with a lumped parameter model is treated, in which the Starling model is used to simulate left ventricle and the four-element Burattini & Gnudi model is used in the description of...The cardiovascular system with a lumped parameter model is treated, in which the Starling model is used to simulate left ventricle and the four-element Burattini & Gnudi model is used in the description of arterial system. Moreover, the feedback action of arterial pressure on cardiac cycle is taken into account. The phenomenon of mechanical periodicity (MP) of end diastolic volume (EDV) of left ventricle is successfully simulated by solving a series of one-dimensional discrete nonlinear dynamical equations. The effects of cardiovascular parameters on MP is also discussed.展开更多
One of the potential risks associated with subsurface storage of CO_2 is the seepage of CO_2 through existing faults and fractures. There have been a number of studies devoted to this topic. Some of these studies show...One of the potential risks associated with subsurface storage of CO_2 is the seepage of CO_2 through existing faults and fractures. There have been a number of studies devoted to this topic. Some of these studies show that geochemistry, especially mineralization, plays an important role in rendering the faults as conduits for CO_2 movement while others show that mineralization due to CO_2 injection can result in seep migration and flow diversion. Therefore, understanding the changes in reservoir properties due to pore alterations is important to ensure safe long term CO_2 storage in the subsurface. We study the changes in the Representative Elementary Volume（REV） of a rock due to reactive kinetics over a time, using a statistical approach and pore-scale CO_2-rock interactiondata.The goal of this study is to obtain the REV of a rock property that accounts for pore-scale changes over time due to reactive kinetics, and we call this as spatiotemporal REV. Scale-up results suggest that the REV changes with time when CO_2-rock interaction is considered. It is hypothesized that the alteration in pore structure introduces more heterogeneity in the rock, and because of this the magnitude of REV increases. It is possible that these noticeable changes in REV at pore-scale may have an impact when analyzed at the reservoir scale.展开更多
The examination of an unstructured finite volume method for structural dynamics is assessed for simulations of systematic impact dynamics. A robust display dual-time stepping method is utilized to obtain time accurate...The examination of an unstructured finite volume method for structural dynamics is assessed for simulations of systematic impact dynamics. A robust display dual-time stepping method is utilized to obtain time accurate solutions. The study of impact dynamics is a complex problem that should consider strength models and state equations to describe the mechanical behavior of materials. The current method has several features, l） Discrete equations of unstructured finite volume method naturally follow the conservation law. 2） Display dual-time stepping method is suitable for the analysis of impact dynamic problems of time accurate solutions. 3） The method did not produce grid distortion when large deformation appeared. The method is validated by the problem of impact dynamics of an elastic plate with initial conditions and material properties. The results validate the finite element numerical data展开更多
基金supported by the National Key R&D Program of China (No. 2024YFF1206700)the National Natural Science Foundation of China (No. U23A20487)the Hangzhou Chengxi Sci-tech Innovation Corridor Management Committee.
文摘Three-dimensional (3D) visualization of dynamic biological processes in deep tissue remains challenging due to the trade-off between temporal resolution and imaging depth. Here, we present a novel near-infrared-II (NIR-II, 900–1880nm) fluorescence volumetric microscopic imaging method that combines an electrically tunable lens (ETL) with deep learning approaches for rapid 3D imaging. The technology achieves volumetric imaging at 4.2 frames per second (fps) across a 200 μm depth range in live mouse brain vasculature. Two specialized neural networks are utilized: a scale-recurrent network (SRN) for image enhancement and a cerebral vessel interpolation (CVI) network that enables 16-fold axial upsampling. The SRN, trained on two-photon fluorescence microscopic data, improves both lateral and axial resolution of NIR-II fluorescence wide-field microscopic images. The CVI network, adapted from video interpolation techniques, generates intermediate frames between acquired axial planes, resulting in smooth and continuous 3D vessel reconstructions. Using this integrated system, we visualize and quantify blood flow dynamics in individual vessels and are capable of measuring blood velocity at different depths. This approach maintains high lateral resolution while achieving rapid volumetric imaging, and is particularly suitable for studying dynamic vascular processes in deep tissue. Our method demonstrates the potential of combining optical engineering with artificial intelligence to advance biological imaging capabilities.
基金Supported by Chongqing Health Commission and Chongqing Science and Technology Bureau,No.2023MSXM182。
文摘Rheumatoid arthritis(RA)patients face significant psychological challenges alongside physical symptoms,necessitating a comprehensive understanding of how psychological vulnerability and adaptation patterns evolve throughout the disease course.This review examined 95 studies(2000-2025)from PubMed,Web of Science,and CNKI databases including longitudinal cohorts,randomized controlled trials,and mixed-methods research,to characterize the complex interplay between biological,psychological,and social factors affecting RA patients’mental health.Findings revealed three distinct vulnerability trajectories(45%persistently low,30%fluctuating improvement,25%persistently high)and four adaptation stages,with critical intervention periods occurring 3-6 months postdiagnosis and during disease flares.Multiple factors significantly influence psychological outcomes,including gender(females showing 1.8-fold increased risk),age(younger patients experiencing 42%higher vulnerability),pain intensity,inflammatory markers,and neuroendocrine dysregulation(48%showing cortisol rhythm disruption).Early psychological intervention(within 3 months of diagnosis)demonstrated robust benefits,reducing depression incidence by 42%with effects persisting 24-36 months,while different modalities showed complementary advantages:Cognitive behavioral therapy for depression(Cohen’s d=0.68),mindfulness for pain acceptance(38%improvement),and peer support for meaning reconstruction(25.6%increase).These findings underscore the importance of integrating routine psychological assessment into standard RA care,developing stage-appropriate interventions,and advancing research toward personalized biopsychosocial approaches that address the dynamic psychological dimensions of the disease.
基金financially supported by the Key Research and Development Program of Heilongjiang Province(No.2024ZXJ03C06)National Natural Science Foundation of China(No.52476192,No.52106237)+1 种基金Natural Science Foundation of Heilongjiang Province(No.YQ2022E027)Technology Project of China Datang Technology Innovation Co.,Ltd(No.DTKC-2024-20610).
文摘Pulsed dynamic electrolysis(PDE),driven by renewable energy,has emerged as an innovative electrocatalytic conversion method,demonstrating significant potential in addressing global energy challenges and promoting sustainable development.Despite significant progress in various electrochemical systems,the regulatory mechanisms of PDE in energy and mass transfer and the lifespan extension of electrolysis systems,particularly in water electrolysis(WE)for hydrogen production,remain insufficiently explored.Therefore,there is an urgent need for a deeper understanding of the unique contributions of PDE in mass transfer enhancement,microenvironment regulation,and hydrogen production optimization,aiming to achieve low-energy consumption,high catalytic activity,and long-term stability in the generation of target products.Here,this review critically examines the microenvironmental effects of PDE on energy and mass transfer,the electrode degradation mechanisms in the lifespan extension of electrolysis systems,and the key factors in enhancing WE for hydrogen production,providing a comprehensive summary of current research progress.The review focuses on the complex regulatory mechanisms of frequency,duty cycle,amplitude,and other factors in hydrogen evolution reaction(HER)performance within PDE strategies,revealing the interrelationships among them.Finally,the potential future directions and challenges for transitioning from laboratory studies to industrial applications are proposed.
基金supported by the National Key Research and Develop-ment Program(No.2022YFC3701103)the National Natural Science Foundation of China(Nos.42130714 and 41931287).
文摘The application of nitrogen fertilizers in agricultural fields can lead to the release of nitrogen-containing gases(NCGs),such as NO_(x),NH_(3) and N_(2)O,which can significantly impact regional atmospheric environment and con-tribute to global climate change.However,there remain considerable research gaps in the accurate measurement of NCGs emissions from agricultural fields,hindering the development of effective emission reduction strategies.We improved an open-top dynamic chambers(OTDCs)system and evaluated the performance by comparing the measured and given fluxes of the NCGs.The results showed that the measured fluxes of NO,N_(2)O and NH_(3)were 1%,2%and 7%lower than the given fluxes,respectively.For the determination of NH_(3) concentration,we employed a stripping coil-ion chromatograph(SC-IC)analytical technique,which demonstrated an absorption efficiency for atmospheric NH_(3) exceeding 96.1%across sampling durations of 6 to 60 min.In the summer maize season,we utilized the OTDCs system to measure the exchange fluxes of NO,NH_(3),and N_(2)O from the soil in the North China Plain.Substantial emissions of NO,NH_(3) and N_(2)O were recorded following fertilization,with peaks of 107,309,1239 ng N/(m^(2)·s),respectively.Notably,significant NCGs emissions were observed following sus-tained heavy rainfall one month after fertilization,particularly with NH_(3) peak being 4.5 times higher than that observed immediately after fertilization.Our results demonstrate that the OTDCs system accurately reflects the emission characteristics of soil NCGs and meets the requirements for long-term and continuous flux observation.
文摘This paper prepared a novel as-cast W-Zr-Ti metallic ESM using high-frequency vacuum induction melting technique.The above ESM performs a typical elastic-brittle material feature and strain rate strengthening behavior.The specimens exhibit violent chemical reaction during the fracture process under the impact loading,and the size distribution of their residual debris follows Rosin-Rammler model.The dynamic fracture toughness is obtained by the fitting of debris length scale,approximately 1.87 MPa·m~(1/2).Microstructure observation on residual debris indicates that the failure process is determined by primary crack propagation under quasi-static compression,while it is affected by multiple cracks propagation in both particle and matrix in the case of dynamic impact.Impact test demonstrates that the novel energetic fragment performs brilliant penetration and combustion effect behind the front target,leading to the effective ignition of fuel tank.For the brittleness of as-cast W-ZrTi ESM,further study conducted bond-based peridynamic(BB-PD)C++computational code to simulate its fracture behavior during penetration.The BB-PD method successfully captured the fracture process and debris cloud formation of the energetic fragment.This paper explores a novel as-cast metallic ESM,and provides an available numerical avenue to the simulation of brittle energetic fragment.
基金supported by the confidential research grant No.a8317。
文摘To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.
基金supported by National Natural Science Foundation of China(No.52103044)Double First-Class Initiative University of Science and Technology of China(KY2400000037)the Young Talent Programme(GG2400007009).
文摘Conductive elastomers combining micromechanical sensitivity,lightweight adaptability,and environmental sustainability are critically needed for advanced flexible electronics requiring precise responsiveness and long-term wearability;however,the integration of these properties remains a significant challenge.Here,we present a biomass-derived conductive elastomer featuring a rationally engineered dynamic crosslinked network integrated with a tunable microporous architecture.This structural design imparts pronounced micromechanical sensitivity,an ultralow density(~0.25 g cm^(−3)),and superior mechanical compliance for adaptive deformation.Moreover,the unique micro-spring effect derived from the porous architecture ensures exceptional stretchability(>500%elongation at break)and superior resilience,delivering immediate and stable electrical response under both subtle(<1%)and large(>200%)mechanical stimuli.Intrinsic dynamic interactions endow the elastomer with efficient room temperature self-healing and complete recyclability without compromising performance.First-principles simulations clarify the mechanisms behind micropore formation and the resulting functionality.Beyond its facile and mild fabrication process,this work establishes a scalable route toward high-performance,sustainable conductive elastomers tailored for next-generation soft electronics.
基金the financial support from the National Natural Science Foundation of China(52203123 and 52473248)State Key Laboratory of Polymer Materials Engineering(sklpme2024-2-04)+1 种基金the Fundamental Research Funds for the Central Universitiessponsored by the Double First-Class Construction Funds of Sichuan University。
文摘Composite polymer electrolytes(CPEs)offer a promising solution for all-solid-state lithium-metal batteries(ASSLMBs).However,conventional nanofillers with Lewis-acid-base surfaces make limited contribution to improving the overall performance of CPEs due to their difficulty in achieving robust electrochemical and mechanical interfaces simultaneously.Here,by regulating the surface charge characteristics of halloysite nanotube(HNT),we propose a concept of lithium-ion dynamic interface(Li^(+)-DI)engineering in nano-charged CPE(NCCPE).Results show that the surface charge characteristics of HNTs fundamentally change the Li^(+)-DI,and thereof the mechanical and ion-conduction behaviors of the NCCPEs.Particularly,the HNTs with positively charged surface(HNTs+)lead to a higher Li^(+)transference number(0.86)than that of HNTs-(0.73),but a lower toughness(102.13 MJ m^(-3)for HNTs+and 159.69 MJ m^(-3)for HNTs-).Meanwhile,a strong interface compatibilization effect by Li^(+)is observed for especially the HNTs+-involved Li^(+)-DI,which improves the toughness by 2000%compared with the control.Moreover,HNTs+are more effective to weaken the Li^(+)-solvation strength and facilitate the formation of Li F-rich solid-electrolyte interphase of Li metal compared to HNTs-.The resultant Li|NCCPE|LiFePO4cell delivers a capacity of 144.9 m Ah g^(-1)after 400 cycles at 0.5 C and a capacity retention of 78.6%.This study provides deep insights into understanding the roles of surface charges of nanofillers in regulating the mechanical and electrochemical interfaces in ASSLMBs.
文摘Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating Interactive Dynamic Graph Convolution Network(IDGCN)with Temporal Multi-Head Trend-Aware Attention.Its core innovation lies in IDGCN,which uniquely splits sequences into symmetric intervals for interactive feature sharing via dynamic graphs,and a novel attention mechanism incorporating convolutional operations to capture essential local traffic trends—addressing a critical gap in standard attention for continuous data.For 15-and 60-min forecasting on METR-LA,AIDGCN achieves MAEs of 0.75%and 0.39%,and RMSEs of 1.32%and 0.14%,respectively.In the 60-min long-term forecasting of the PEMS-BAY dataset,the AIDGCN out-performs the MRA-BGCN method by 6.28%,4.93%,and 7.17%in terms of MAE,RMSE,and MAPE,respectively.Experimental results demonstrate the superiority of our pro-posed model over state-of-the-art methods.
基金supported by the Zhongyuan University of Technology Discipline Backbone Teacher Support Program Project(No.GG202417)the Key Research and Development Program of Henan under Grant 251111212000.
文摘Lateral movement represents the most covert and critical phase of Advanced Persistent Threats(APTs),and its detection still faces two primary challenges:sample scarcity and“cold start”of new entities.To address these challenges,we propose an Uncertainty-Driven Graph Embedding-Enhanced Lateral Movement Detection framework(UGEA-LMD).First,the framework employs event-level incremental encoding on a continuous-time graph to capture fine-grained behavioral evolution,enabling newly appearing nodes to retain temporal contextual awareness even in the absence of historical interactions and thereby fundamentally mitigating the cold-start problem.Second,in the embedding space,we model the dependency structure among feature dimensions using a Gaussian copula to quantify the uncertainty distribution,and generate augmented samples with consistent structural and semantic properties through adaptive sampling,thus expanding the representation space of sparse samples and enhancing the model’s generalization under sparse sample conditions.Unlike static graph methods that cannot model temporal dependencies or data augmentation techniques that depend on predefined structures,UGEA-LMD offers both superior temporaldynamic modeling and structural generalization.Experimental results on the large-scale LANL log dataset demonstrate that,under the transductive setting,UGEA-LMD achieves an AUC of 0.9254;even when 10%of nodes or edges are withheld during training,UGEA-LMD significantly outperforms baseline methods on metrics such as recall and AUC,confirming its robustness and generalization capability in sparse-sample and cold-start scenarios.
基金The National Natural Science Foundation of China(Grant No.12462006)Beijing Institute of Structure and Environment Engineering Joint Innovation Fund(No.BQJJ202414).
文摘THE mechanical response and deformation mechanisms of pure nickel under nanoindentation were systematically investigated using molecular dynamics(MD)simulations,with a particular focus on the novel interplay between crystallographic orientation,grain boundary(GB)proximity,and pore characteristics(size/location).This study compares single-crystal nickel models along[100],[110],and[111]orientations with equiaxed polycrystalline models containing 0,1,and 2.5 nm pores in surface and subsurface configurations.Our results reveal that crystallographic anisotropy manifests as a 24.4%higher elastic modulus and 22.2%greater hardness in[111]-oriented single crystals compared to[100].Pore-GB synergistic effects are found to dominate the deformation behavior:2.5 nm subsurface pores reduce hardness by 25.2%through stress concentration and dislocation annihilation at GBs,whereas surface pores enable mechanical recovery via accelerated dislocation generation post-collapse.Additionally,size-dependent deformation regimes were identified,with 1 nm pores inducing negligible perturbation due to rapid atomic rearrangement,in contrast with persistent softening in 2.5 nm pores.These findings establish atomic-scale design principles for defect engineering in nickel-based aerospace components,demonstrating how crystallographic orientation,pore configuration,and GB interactions collectively govern nanoindentation behavior.
基金supported by the National Key Research and Development Program of China under Grant 2022YFB3608300in part by the National Nature Science Foundation of China(NSFC)under Grants 62404050,U2341218,62574056,62204052。
文摘Organic electrochemical transistor(OECT)devices demonstrate great promising potential for reservoir computing(RC)systems,but their lack of tunable dynamic characteristics limits their application in multi-temporal scale tasks.In this study,we report an OECT-based neuromorphic device with tunable relaxation time(τ)by introducing an additional vertical back-gate electrode into a planar structure.The dual-gate design enablesτreconfiguration from 93 to 541 ms.The tunable relaxation behaviors can be attributed to the combined effects of planar-gate induced electrochemical doping and back-gateinduced electrostatic coupling,as verified by electrochemical impedance spectroscopy analysis.Furthermore,we used theτ-tunable OECT devices as physical reservoirs in the RC system for intelligent driving trajectory prediction,achieving a significant improvement in prediction accuracy from below 69%to 99%.The results demonstrate that theτ-tunable OECT shows a promising candidate for multi-temporal scale neuromorphic computing applications.
基金financial support from the National Natural Science Foundation of China(22109127)the Chinese Postdoctoral Science Foundation(2021M702666),+1 种基金he Research Fund of the State Key Laboratory of Solidification Processing(NPU),China(Grant No.2023-TS-02)financial support from the Youth Project of"Shaanxi High-level Talents Introduction Plan"and the Key Laboratory of Advanced Energy Materials Chemistry(Ministry of Education)are also sincerely appreciated.
文摘Photo-assisted lithium–sulfur batteries(PALSBs)offer an eco-friendly solution to address the issue of sluggish reaction kinetics of conventional LSBs.However,designing an efficient photoelectrode for practical implementation remains a significant challenge.Herein,we construct a free-standing polymer–inorganic hybrid photoelectrode with a direct Z-scheme heterostructure to develop high-efficiency PALSBs.Specifically,polypyrrole(PPy)is in situ vapor-phase polymerized on the surface of N-doped TiO_(2) nanorods supported on carbon cloth(N-TiO_(2)/CC),thereby forming a well-defined p–n heterojunction.This architecture efficiently facilitates the carrier separation of photo-generated electron–hole pairs and significantly enhances carrier transport by creating a built-in electric field.Thus,the PPy@N-TiO_(2)/CC can simultaneously act as a photocatalyst and an electrocatalyst to accelerate the reduction and evolution of sulfur,enabling ultrafast sulfur redox dynamics,as convincingly validated by both theoretical simulations and experimental results.Consequently,the PPy@N-TiO_(2)/CC PALSB achieves a high discharge capacity of 1653 mAh g−1,reaching 98.7%of the theoretical value.Furthermore,5 h of photo-charging without external voltage enables the PALSB to deliver a discharge capacity of 333 mAh g−1,achieving dual-mode energy harvesting capabilities.This work successfully integrates solar energy conversion and storage within a rechargeable battery system,providing a promising strategy for sustainable energy storage technologies.
基金supported by the National Natural Science Foundation of China (Grant No.11574244 for G.Y.G.)the XJTU Research Fund for AI Science (Grant No.2025YXYC011 for G.Y.G.)the Hong Kong Global STEM Professorship Scheme (for X.C.Z.)。
文摘Compared to the well-studied two-dimensional(2D)ferroelectricity,the appearance of 2D antiferroelectricity is much rarer,where local dipoles from the nonequivalent sublattices within 2D monolayers are oppositely oriented.Using NbOCl_(2) monolayer with competing ferroelectric(FE)and antiferroelectric(AFE)phases as a 2D material platform,we demonstrate the emergence of intrinsic antiferroelectricity in NbOCl_(2) monolayer under experimentally accessible shear strain,along with new functionality associated with electric field-induced AFE-to-FE phase transition.Specifically,the complex configuration space accommodating FE and AFE phases,polarization switching kinetics,and finite temperature thermodynamic properties of 2D NbOCl_(2) are all accurately predicted by large-scale molecular dynamics simulations based on deep learning interatomic potential model.Moreover,room temperature stable antiferroelectricity with low polarization switching barrier and one-dimensional collinear polarization arrangement is predicted in shear-deformed NbOCl_(2) monolayer.The transition from AFE to FE phase in 2D NbOCl_(2) can be triggered by a low critical electric field,leading to a double polarization–electric(P–E)loop with small hysteresis.A new type of optoelectronic device composed of AFE-NbOCl_(2) is proposed,enabling electric“writing”and nonlinear optical“reading”logical operation with fast operation speed and low power consumption.
文摘Mitochondrial dysfunction has emerged as a critical factor in the etiology of various neurodevelopmental disorders, including autism spectrum disorders, attention-deficit/hyperactivity disorder, and Rett syndrome. Although these conditions differ in clinical presentation, they share fundamental pathological features that may stem from abnormal mitochondrial dynamics and impaired autophagic clearance, which contribute to redox imbalance and oxidative stress in neurons. This review aimed to elucidate the relationship between mitochondrial dynamics dysfunction and neurodevelopmental disorders. Mitochondria are highly dynamic organelles that undergo continuous fusion and fission to meet the substantial energy demands of neural cells. Dysregulation of these processes, as observed in certain neurodevelopmental disorders, causes accumulation of damaged mitochondria, exacerbating oxidative damage and impairing neuronal function. The phosphatase and tensin homolog-induced putative kinase 1/E3 ubiquitin-protein ligase pathway is crucial for mitophagy, the process of selectively removing malfunctioning mitochondria. Mutations in genes encoding mitochondrial fusion proteins have been identified in autism spectrum disorders, linking disruptions in the fusion-fission equilibrium to neurodevelopmental impairments. Additionally, animal models of Rett syndrome have shown pronounced defects in mitophagy, reinforcing the notion that mitochondrial quality control is indispensable for neuronal health. Clinical studies have highlighted the importance of mitochondrial disturbances in neurodevelopmental disorders. In autism spectrum disorders, elevated oxidative stress markers and mitochondrial DNA deletions indicate compromised mitochondrial function. Attention-deficit/hyperactivity disorder has also been associated with cognitive deficits linked to mitochondrial dysfunction and oxidative stress. Moreover, induced pluripotent stem cell models derived from patients with Rett syndrome have shown impaired mitochondrial dynamics and heightened vulnerability to oxidative injury, suggesting the role of defective mitochondrial homeostasis in these disorders. From a translational standpoint, multiple therapeutic approaches targeting mitochondrial pathways show promise. Interventions aimed at preserving normal fusion-fission cycles or enhancing mitophagy can reduce oxidative damage by limiting the accumulation of defective mitochondria. Pharmacological modulation of mitochondrial permeability and upregulation of peroxisome proliferator-activated receptor gamma coactivator 1-alpha, an essential regulator of mitochondrial biogenesis, may also ameliorate cellular energy deficits. Identifying early biomarkers of mitochondrial impairment is crucial for precision medicine, since it can help clinicians tailor interventions to individual patient profiles and improve prognoses. Furthermore, integrating mitochondria-focused strategies with established therapies, such as antioxidants or behavioral interventions, may enhance treatment efficacy and yield better clinical outcomes. Leveraging these pathways could open avenues for regenerative strategies, given the influence of mitochondria on neuronal repair and plasticity. In conclusion, this review indicates mitochondrial homeostasis as a unifying therapeutic axis within neurodevelopmental pathophysiology. Disruptions in mitochondrial dynamics and autophagic clearance converge on oxidative stress, and researchers should prioritize validating these interventions in clinical settings to advance precision medicine and enhance outcomes for individuals affected by neurodevelopmental disorders.
基金supported by the National Key Research and Development Program of China (Grant Nos. 2017YFC1501901 and 2017YFA0603901)the Beijing Natural Science Foundation (Grant No. JQ18001)
文摘A 3D compressible nonhydrostatic dynamic core based on a three-point multi-moment constrained finite-volume (MCV) method is developed by extending the previous 2D nonhydrostatic atmospheric dynamics to 3D on a terrainfollowing grid. The MCV algorithm defines two types of moments: the point-wise value (PV) and the volume-integrated average (VIA). The unknowns (PV values) are defined at the solution points within each cell and are updated through the time evolution formulations derived from the governing equations. Rigorous numerical conservation is ensured by a constraint on the VIA moment through the flux form formulation. The 3D atmospheric dynamic core reported in this paper is based on a three-point MCV method and has some advantages in comparison with other existing methods, such as uniform third-order accuracy, a compact stencil, and algorithmic simplicity. To check the performance of the 3D nonhydrostatic dynamic core, various benchmark test cases are performed. All the numerical results show that the present dynamic core is very competitive when compared to other existing advanced models, and thus lays the foundation for further developing global atmospheric models in the near future.
基金Supported by the National Natural Science Foundation of China(No.52005441)Natural Science Foundation of Zhejiang Province(No.LQ21E050017)+4 种基金Young Elite Scientist Sponsorship Program by CAST(No.2022QNRC001)State Key Laboratory of Mechanical System and Vibration(No.MSV202316)"Pioneer"and"Leading Goose"R&D Program of Zhejiang Province(Nos.2022C01122,2022C01132)the Fundamental Research Funds for the Provincial Universities of Zhejiang(No.RFA2023007)the Research Project of ZJUT(No.GYY-ZH2023075).
文摘Hydraulic circuits with high speed on/off valve(HSV)for servo control have become commonplace in aerospace.However,the individual valve that is not volume-optimized results in a large total size of hydraulic control system,diminishing the practicality.To address this issue,the high-precision equivalent reluctance model of the HSV is established by employing an equivalent magnetic circuit,on which the dynamic characteristic of the HSV,as well as the effects of structural parameters on switching behaviour,are investigated.Based on this model,multi-objective optimization is adopted to design an HSV with faster dynamic performance and smaller volume,NSGA-II genetic algorithm is applied to obtain the Pareto front of the desired objectives.To assess the impact before and after optimization,an HSV based on the optimized structure is manufactured and tested.The experimental results show that the optimized HSV reduces 47.1%of its solenoid volume while improving opening and closing dynamic performance by 14.8%and 43.0%respectively,increasing maximum switching frequency by 6.2%,and expanding flow linear control area by 6.7%.These results validate the optimized structure and indicate that the optimization method provided in the paper is beneficial for developing superior HSV.
文摘The cardiovascular system with a lumped parameter model is treated, in which the Starling model is used to simulate left ventricle and the four-element Burattini & Gnudi model is used in the description of arterial system. Moreover, the feedback action of arterial pressure on cardiac cycle is taken into account. The phenomenon of mechanical periodicity (MP) of end diastolic volume (EDV) of left ventricle is successfully simulated by solving a series of one-dimensional discrete nonlinear dynamical equations. The effects of cardiovascular parameters on MP is also discussed.
基金supported by the Center for Frontiers of Subsurface Energy Security (CFSES), UT Austinfunded by Basic Energy Sciences at the U.S.Department of Energy
文摘One of the potential risks associated with subsurface storage of CO_2 is the seepage of CO_2 through existing faults and fractures. There have been a number of studies devoted to this topic. Some of these studies show that geochemistry, especially mineralization, plays an important role in rendering the faults as conduits for CO_2 movement while others show that mineralization due to CO_2 injection can result in seep migration and flow diversion. Therefore, understanding the changes in reservoir properties due to pore alterations is important to ensure safe long term CO_2 storage in the subsurface. We study the changes in the Representative Elementary Volume（REV） of a rock due to reactive kinetics over a time, using a statistical approach and pore-scale CO_2-rock interactiondata.The goal of this study is to obtain the REV of a rock property that accounts for pore-scale changes over time due to reactive kinetics, and we call this as spatiotemporal REV. Scale-up results suggest that the REV changes with time when CO_2-rock interaction is considered. It is hypothesized that the alteration in pore structure introduces more heterogeneity in the rock, and because of this the magnitude of REV increases. It is possible that these noticeable changes in REV at pore-scale may have an impact when analyzed at the reservoir scale.
文摘The examination of an unstructured finite volume method for structural dynamics is assessed for simulations of systematic impact dynamics. A robust display dual-time stepping method is utilized to obtain time accurate solutions. The study of impact dynamics is a complex problem that should consider strength models and state equations to describe the mechanical behavior of materials. The current method has several features, l） Discrete equations of unstructured finite volume method naturally follow the conservation law. 2） Display dual-time stepping method is suitable for the analysis of impact dynamic problems of time accurate solutions. 3） The method did not produce grid distortion when large deformation appeared. The method is validated by the problem of impact dynamics of an elastic plate with initial conditions and material properties. The results validate the finite element numerical data
