The fusion excitation functions for 12 colliding systems with 96≤Z_(1)Z_(2)≤608 are analyzed using coupled-channel(CC)calculations based on the M3Y double-folding(DF)potential supplemented with a repulsive potential...The fusion excitation functions for 12 colliding systems with 96≤Z_(1)Z_(2)≤608 are analyzed using coupled-channel(CC)calculations based on the M3Y double-folding(DF)potential supplemented with a repulsive potential that takes into account the incompressibility of the nuclear matter.We also applied the polarization effects of hot nuclear matter(PEHNM)on the calculations of the bare nucleus-nucleus interaction potential within the framework of the modified density-dependent Seyler-Blanchard(SB)approach in the T^(2)approximation.Our results reveal that we obtain a nice description of the experimental data of different fusion systems when we use the present theoretical approach to calculate the energy-dependent values of the fusion cross sections.In this paper,the influence of the PEHNM on the surface diffuseness parameter of the Woods-Saxon(WS)potential is also studied.In order to reach this goal,we extract the corresponding values of this parameter based on the modified form of the DF potential(M3Y+Repulsion+polarization).We find that the extracted values are located in a range between a=0.61 and 0.80 fm at different incident energies.It seems that the polarization effects of hot nuclear matter play a key role in describing the abnormally large values of the nuclear potential diffusenesses in the heavy-ion fusion reactions.Additionally,the regular decreasing trend for the diffuseness parameter of the nucleus-nucleus potential with the increase in the bombarding energies is also observed.展开更多
A radial basis function network(RBFN)approach is adopted for the first time to optimize the calculation of$\alpha$decay half-life in the generalized liquid drop model(GLDM),while concurrently incorporating the surface...A radial basis function network(RBFN)approach is adopted for the first time to optimize the calculation of$\alpha$decay half-life in the generalized liquid drop model(GLDM),while concurrently incorporating the surface diffuseness effect.The calculations presented herein agree closely with the experimental half-lives for 68 superheavy nuclei(SHN),achieving a remarkable reduction of 40%in the root-mean-square(rms)deviations of half-lives.Furthermore,using the RBFN method,the half-lives for four SHN isotopes,252-288Rf,272-310Fl,286-316119,and 292-318120,are predicted using the improved GLDM with the diffuseness correction and the decay energies from WS4 and FRDM as inputs.Therefore,we conclude that the diffuseness effect should be embodied in the proximity energy.Moreover,increased application of neural network methods in nuclear reaction studies is encouraged.展开更多
Cerebral small vessel disease encompasses a group of neurological disorders characterized by injury to small blood vessels,often leading to stroke and dementia.Due to its diverse etiologies and complex pathological me...Cerebral small vessel disease encompasses a group of neurological disorders characterized by injury to small blood vessels,often leading to stroke and dementia.Due to its diverse etiologies and complex pathological mechanisms,preventing and treating cerebral small vessel vasculopathy is challenging.Recent studies have shown that the glymphatic system plays a crucial role in interstitial solute clearance and the maintenance of brain homeostasis.Increasing evidence also suggests that dysfunction in glymphatic clearance is a key factor in the progression of cerebral small vessel disease.This review begins with a comprehensive introduction to the structure,function,and driving factors of the glymphatic system,highlighting its essential role in brain waste clearance.Afterwards,cerebral small vessel disease was reviewed from the perspective of the glymphatic system,after which the mechanisms underlying their correlation were summarized.Glymphatic dysfunction may lead to the accumulation of metabolic waste in the brain,thereby exacerbating the pathological processes associated with cerebral small vessel disease.The review also discussed the direct evidence of glymphatic dysfunction in patients and animal models exhibiting two subtypes of cerebral small vessel disease:arteriolosclerosis-related cerebral small vessel disease and amyloid-related cerebral small vessel disease.Diffusion tensor image analysis along the perivascular space is an important non-invasive tool for assessing the clearance function of the glymphatic system.However,the effectiveness of its parameters needs to be enhanced.Among various nervous system diseases,including cerebral small vessel disease,glymphatic failure may be a common final pathway toward dementia.Overall,this review summarizes prevention and treatment strategies that target glymphatic drainage and will offer valuable insight for developing novel treatments for cerebral small vessel disease.展开更多
Fine-grained nuclear graphite is a key material in high-temperature gas-cooled reactors(HTGRs).During air ingress accidents,core graphite components undergo severe oxidation,threatening structural integrity.Therefore,...Fine-grained nuclear graphite is a key material in high-temperature gas-cooled reactors(HTGRs).During air ingress accidents,core graphite components undergo severe oxidation,threatening structural integrity.Therefore,understanding the oxidation behavior of nuclear graphite is essential for reactor safety.The influence of oxidation involves multiple factors,including temperature,sample size,oxidant,impurities,filler type and size,etc.The size of the filler particles plays a crucial role in this study.Five ultrafine-and superfine-grained nuclear graphite samples(5.9-34.4μm)are manufactured using identical raw materials and manufacturing processes.Isothermal oxidation tests conducted at 650℃-750℃ are used to study the oxidation behavior.Additionally,comprehensive characterization is performed to analyze the crystal structure,surface morphology,and nanoscale to microscale pore structure of the samples.Results indicate that oxidation behavior cannot be predicted solely based on filler grain size.Reactive site concentration,characterized by active surface area,dominates the chemical reaction kinetics,whereas pore tortuosity,quantified by the structural parameterΨ,plays a key role in regulating oxidant diffusion.These findings clarify the dual role of microstructure in oxidation mechanisms and establish a theoretical and experimental basis for the design of high-performance nuclear graphite capable of long-term service in high-temperature gas-cooled reactors.展开更多
The fast solution of linear equations has always been one of the hot spots in scientific computing.A kind of the diagonal matrix splitting iteration methods are provided,which is different from the classical matrix sp...The fast solution of linear equations has always been one of the hot spots in scientific computing.A kind of the diagonal matrix splitting iteration methods are provided,which is different from the classical matrix splitting methods.Taking the decomposition of the diagonal elements for coefficient matrix as the key point,some new preconditioners are constructed.Taking the tri-diagonal coefficient matrix as an example,the convergence domains and optimal relaxation factor of the new method are analyzed theoretically.The presented new iteration methods are applied to solve linear algebraic equations,even 2D and 3D diffusion problems with the fully implicit discretization.The results of numerical experiments are matched with the theoretical analysis,and show that the iteration numbers are reduced greatly.The superiorities of presented iteration methods exceed some classical iteration methods dramatically.展开更多
Scalable simulation leveraging real-world data plays an essential role in advancing autonomous driving,owing to its efficiency and applicability in both training and evaluating algorithms.Consequently,there has been i...Scalable simulation leveraging real-world data plays an essential role in advancing autonomous driving,owing to its efficiency and applicability in both training and evaluating algorithms.Consequently,there has been increasing attention on generating highly realistic and consistent driving videos,particularly those involving viewpoint changes guided by the control commands or trajectories of ego vehicles.However,current reconstruction approaches,such as Neural Radiance Fields and 3D Gaussian Splatting,frequently suffer from limited generalization and depend on substantial input data.Meanwhile,2D generative models,though capable of producing unknown scenes,still have room for improvement in terms of coherence and visual realism.To overcome these challenges,we introduce GenScene,a world model that synthesizes front-view driving videos conditioned on trajectories.A new temporal module is presented to improve video consistency by extracting the global context of each frame,calculating relationships of frames using these global representations,and fusing frame contexts accordingly.Moreover,we propose an innovative attention mechanism that computes relations of pixels within each frame and pixels in the corresponding window range of the initial frame.Extensive experiments show that our approach surpasses various state-of-the-art models in driving video generation,and the introduced modules contribute significantly to model performance.This work establishes a new paradigm for goal-oriented video synthesis in autonomous driving,which facilitates on-demand simulation to expedite algorithm development.展开更多
In this paper,we are concerned with the stability of traveling wavefronts of a Belousov-Zhabotinsky model with mixed nonlocal and degenerate diffusions.Such a system can be used to study the competition among nonlocal...In this paper,we are concerned with the stability of traveling wavefronts of a Belousov-Zhabotinsky model with mixed nonlocal and degenerate diffusions.Such a system can be used to study the competition among nonlocally diffusive species and degenerately diffusive species.We prove that the traveling wavefronts are exponentially stable,when the initial perturbation around the traveling waves decays exponentially as x→-∞,but in other locations,the initial data can be arbitrarily large.The adopted methods are the weighted energy with the comparison principle and squeezing technique.展开更多
Injecting impure CO_(2)for enhanced gas recovery(CO_(2)-EGR)offers a dual benefit by improving natural gas extraction while enabling CO_(2)sequestration.However,the interactions between CO_(2),N_(2),and CH_(4)under re...Injecting impure CO_(2)for enhanced gas recovery(CO_(2)-EGR)offers a dual benefit by improving natural gas extraction while enabling CO_(2)sequestration.However,the interactions between CO_(2),N_(2),and CH_(4)under reservoir conditions require further investigation.This study employs Grand Canonical Monte Carlo(GCMC)and Molecular Dynamics(MD)simulations to quantify the adsorption and diffusion behaviors of CO_(2),N_(2),and CH_(4)in quartz nanopores over a pressure range of 1-24 MPa under varying water saturations and gas compositions.The results indicate that:(1)CO_(2)exhibits the broadest energy distribution and the strongest adsorption stability,occupying about 20%-30%more adsorption sites than CH_(4)or N_(2)and showing the least sensitivity to water saturation,with only a 30%reduction at 50%saturation,compared to 60%for CH_(4),giving CO_(2)a clear competitive advantage.(2)The adsorption and desorption behaviors are strongly pressure dependent,as increasing pressure reduces the adsorption layer area and shifts gas distribution from adsorption dominated to free phase.Competitive adsorption analysis reveals that while CO_(2)dominates displacement at low pressures,mixtures that contain N_(2)achieve higher CH_(4)desorption efficiency above 13 MPa by mitigating diffusion resistance.(3)A higher N_(2)fraction improves CH_(4)diffusion coefficients,thereby facilitating gas mobility and ensuring superior recovery performance under high-pressure conditions.This study advances the fundamental knowledge of microscale gas behavior in tight sandstones and supports the feasibility of impure CO_(2)injection as a practical strategy for sustainable gas production.展开更多
This research explores the influence of crystallinity on gas chromatographic(GC) separation using covalent organic frameworks(COFs) as stationary phases.Three COF materials(CTF-DCBs) with varying crystallinity were sy...This research explores the influence of crystallinity on gas chromatographic(GC) separation using covalent organic frameworks(COFs) as stationary phases.Three COF materials(CTF-DCBs) with varying crystallinity were synthesized and characterized.CTF-DCB-1,with superior crystallinity,demonstrated highselectivity GC separation of benzene isomers as well as styrene/phenylacetylene mixtures,while CTFDCB-2 and CTF-DCB-3 exhibited lower crystallinity and worse separation performance.Thermodynamic and kinetic tests showed that CTF-DCB-1 had the worst thermodynamic adsorption but low diffusion mass transfer resistance,which resulted in the best separation.Therefore,optimizing the crystallinity of COFs is necessary for balancing the kinetic diffusion and thermodynamic interactions towards the analytes,achieving high-performance GC stationary phases.展开更多
Prussian blue analogs(PBAs)have emerged as environmentally friendly and structurally tunable cathode materials for aqueous ammonium-ion batteries(AIBs).However,the fundamental role of crystalline H_(2)O in regulating ...Prussian blue analogs(PBAs)have emerged as environmentally friendly and structurally tunable cathode materials for aqueous ammonium-ion batteries(AIBs).However,the fundamental role of crystalline H_(2)O in regulating ammonium-ion storage and transport remains poorly understood.In this study,we present a comprehensive comparison between hydrated NH_(4)NiHCF-H_(2)O and its anhydrous counterpart NH_(4)NiHCF,revealing the critical contribution of interstitial water to electrochemical performance.Structural and spectroscopic analyses confirm that interstitial water forms robust hydrogen bonds with NH_(4)+ions,stabilizing the PBA framework and mitigating structural degradation during cycling.Electrochemical measurements show that NH_(4)NiHCF-H_(2)O delivers a significantly higher specific capacity of 61 mA h g^(−1)at 0.2 C and markedly improved rate performance compared to NH_(4)NiHCF(48 mA h g^(−1)at 0.2 C).Kinetic analysis reveals that interstitial water enhances NH_(4)+diffusion,as evidenced by higher diffusion coefficients.Furthermore,density functional theory(DFT)calculations demonstrate that crystal water acts as a hydrogen bond acceptor,preferentially interacting with NH_(4)+and reducing the migration energy barrier,thereby facilitating fast ion transport.This work provides fundamental insights into the role of crystal water in PBAs and offers a rational design strategy for improving the kinetics,structural stability of PBAs cathodes for AIBs.展开更多
This paper examines how natural gas disperses vertically when high-pressure pipelines with large openings fail in unconfined environments,providing insight into hazardous gas cloud development and behavior.A comprehen...This paper examines how natural gas disperses vertically when high-pressure pipelines with large openings fail in unconfined environments,providing insight into hazardous gas cloud development and behavior.A comprehensive study was conducted using a full-scale field experiment(1,219 mm diameter,12 MPa pressure,100 mm aperture)combined with a validated computational fluid dynamics(CFD)numerical simulation model to systematically analyze the coupling effects of pipeline pressure and ambient wind speed.The results indicate that:(1)Pipeline pressure determines the vertical jet scale,where jet height is positively correlated with pressure;at 12 MPa,the maximum jet height reaches 69.4 m(approximately 2.65 times that at 4 MPa),and the lower explosive limit(LEL)cloud area follows a quadratic polynomial trend.(2)Ambient wind speed significantly alters the diffusion trajectory;at a wind speed of 10 m/s,the LEL gas cloud area expands by 1.69 times compared to calm conditions,while the jet height is suppressed to 29.9%of the calm wind value.(3)Our developed dynamic prediction model for the hazardous gas-cloud region achieves a determination coefficient of 0.975 and maintaining prediction errors maintained within approximately 12%.The proposed empirical correlations and dynamic prediction model provide essential quantitative data support for safety-distance design and emergency-response decision-making for high-pressure natural gas pipelines.展开更多
Cation disordering is a common issue in Ni-rich cathodes that significantly degrades cycle life and compromises safety.The cubic rock-salt phase formation and the slow oxidation kinetics of Ni^(2+)during solid-state s...Cation disordering is a common issue in Ni-rich cathodes that significantly degrades cycle life and compromises safety.The cubic rock-salt phase formation and the slow oxidation kinetics of Ni^(2+)during solid-state sintering are widely recognized as the principal causes of these structural defects.To solve this issue,a topotactic soft-chemical precursor engineering strategy is proposed for use in aqueous solution.By utilizing the layered structure of the precursor,this method allows for selective proton extraction and efficient Ni^(2+)oxidation,along with rapid Li+intercalation to form a layered lithiated intermediate.This intermediate crystallizes without further phase transitions during subsequent heat treatment,preventing structural defects caused by complex phase evolution and slow ion diffusion.The resulting cathode exhibits a long-range ordered layered structure and a uniform phase distribution,enabling efficient Li+insertion and extraction.Electrochemical tests reveal a high discharge capacity of 229.6 mAh g^(−1)and an initial coulombic efficiency of 95.77%at 0.1 C,greatly exceeding the performance of a conventionally synthesized cathode(210.3 mAh g^(−1),88.93%).Improved Li^(+)transport kinetics reduces phase-transition hysteresis and alleviates stress concentration,resulting in better cycling stability with a capacity retention of 85.3%after 300 cycles,compared to 61.5%for the conventional sample.This work presents a scalable and effective synthesis route for Ni-rich cathodes with reduced structural disorder and extended lifespan,providing valuable insights into how the regulation of intermediate phases influences electrochemical performance in high-performance Ni-rich cathodes.展开更多
Some patients with systemic lupus erythematosus experience neuropsychiatric symptoms.Although magnetic resonance imaging can detect abnormal signals in the white matter of the brain,conventional methods often struggle...Some patients with systemic lupus erythematosus experience neuropsychiatric symptoms.Although magnetic resonance imaging can detect abnormal signals in the white matter of the brain,conventional methods often struggle to accurately capture microstructural changes.Various diffusion models have been used to study white matter in systemic lupus erythematosus;however,comparative analyses of their sensitivity and specificity for detecting microstructural changes remain insufficient.To address this,our team designed a diagnostic trial that used multimodal diffusion imaging techniques to observe white matter microstructural changes in patients with systemic lupus erythematosus who had neuropsychiatric symptoms,with an aim to identify key diagnostic biomarkers for these patients.Patients with active lupus who received treatment at the Department of Rheumatology and Immunology,The First Affiliated Hospital of China Medical University,from September 2023 to March 2024 were recruited.According to the standards of the American College of Rheumatology,patients with systemic lupus erythematosus who had neuropsychiatric symptoms were assigned to the systemic lupus erythematosus group,whereas those without neuropsychiatric symptoms were assigned to the non-systemic lupus erythematosus group.Additionally,healthy volunteers matched by region,sex,and age were recruited as controls.All three groups underwent the same diffusion magnetic resonance imaging examination protocol to compare differences in diffusion parameters.Advanced diffusion imaging models were able to sensitively detect microstructural changes in the white matter fibers of patients with systemic lupus erythematosus who had neuropsychiatric symptoms,with specific diffusion parameters showing significant abnormalities in key brain regions.In the left superior longitudinal fasciculus subregion and the right thalamic radiations of patients with systemic lupus erythematosus who had neuropsychiatric symptoms,we also identified abnormal diffusion characteristics that were clearly correlated with disease activity,suggesting that microstructural changes in these areas may reflect the dynamic process of neuroinflammatory damage.The present study addresses critical challenges in the diagnosis of systemic lupus erythematosus by identifying specific white matter imaging biomarkers and elucidating the association between microstructural damage and clinical manifestations.The main contributions of our study include:1)establishing axial regression probability parameters from mean apparent propagator magnetic resonance imaging as sensitive biomarkers for systemic lupus erythematosus,particularly in the third subregion of the left superior longitudinal fasciculus;2)demonstrating that multimodal diffusion imaging may be superior to conventional diffusion tensor imaging for detecting white matter microstructural abnormalities in patients with systemic lupus erythematosus;and 3)integrating tract-based spatial statistics with clinically relevant analyses to link imaging findings to pathological mechanisms.展开更多
Inverse design of advanced materials represents a pivotal challenge in materials science.Leveraging the latent space of Variational Autoencoders(VAEs)for material optimization has emerged as a significant advancement ...Inverse design of advanced materials represents a pivotal challenge in materials science.Leveraging the latent space of Variational Autoencoders(VAEs)for material optimization has emerged as a significant advancement in the field of material inverse design.However,VAEs are inherently prone to generating blurred images,posing challenges for precise inverse design and microstructure manufacturing.While increasing the dimensionality of the VAE latent space can mitigate reconstruction blurriness to some extent,it simultaneously imposes a substantial burden on target optimization due to an excessively high search space.To address these limitations,this study adopts a Variational Autoencoder guided Conditional Diffusion Generative Model(VAE-CDGM)framework integrated with Bayesian optimization to achieve the inverse design of composite materials with targeted mechanical properties.The VAE-CDGM model synergizes the strengths of VAEs and Denoising Diffusion Probabilistic Models(DDPM),enabling the generation of high-quality,sharp images while preserving a manipulable latent space.To accommodate varying dimensional requirements of the latent space,two optimization strategies are proposed.When the latent space dimensionality is excessively high,SHapley Additive exPlanations(SHAP)sensitivity analysis is employed to identify critical latent features for optimization within a reduced subspace.Conversely,direct optimization is performed in the low-dimensional latent space of VAE-CDGM when dimensionality is modest.The results demonstrate that both strategies accurately achieve the targeted design of composite materials while circumventing the blurred reconstruction flaws of VAEs,which offers a novel pathway for the precise design of advanced materials.展开更多
This study integrates experimental investigation with molecular dynamics simulations to elucidate the hydrogen transport mechanisms in polyetheretherketone(PEEK)and polytetrafluoroethylene(PTFE),offering fundamental i...This study integrates experimental investigation with molecular dynamics simulations to elucidate the hydrogen transport mechanisms in polyetheretherketone(PEEK)and polytetrafluoroethylene(PTFE),offering fundamental insights into the barrier properties of high-performance polymeric materials.Experimental results demonstrate that PEEK exhibits superior hydrogen barrier performance compared to PTFE at both ambient and elevated temperatures.However,detailed molecular dynamics simulations uncover a distinctive,enthalpy-driven"high solubility-low diffusivity"transport mechanism:although PEEK displays higher hydrogen solubility due to its stronger thermodynamic affinity,its diffusion coefficient is markedly lower than that of PTFE.This mechanism remains operative across a broad operational temperature range(233 K to358 K),yet its influence on overall permeability is strongly temperature-dependent.At room and high temperatures,the exceptionally low diffusivity of PEEK governs the entire permeation process,establishing its effectiveness as a high-performance hydrogen barrier material.In contrast,under low-temperature conditions(e.g.,233 K),the general suppression of diffusion allows the high solubility of PEEK to dominate,resulting in greater overall permeability than PTFE and giving rise to a performance“reversal”phenomenon.This distinct transport behavior originates from the strong non-covalent interactions between hydrogen molecules and the aromatic rings as well as polar functional groups present in the amorphous regions of PEEK,which simultaneously enhance solubility and impose significant kinetic energy barriers.The"structure-mechanism"correlation framework established in this work provides a robust theoretical foundation for the rational design of next-generation hydrogen barrier materials tailored to specific operational temperature requirements.展开更多
Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frame...Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.展开更多
AIM:To investigate the clinical characteristics and treatment outcomes,including visual function and overall survival(OS)of patients with ocular adnexal diffuse large B-cell lymphoma(OA-DLBCL).METHODS:This retrospecti...AIM:To investigate the clinical characteristics and treatment outcomes,including visual function and overall survival(OS)of patients with ocular adnexal diffuse large B-cell lymphoma(OA-DLBCL).METHODS:This retrospective cohort study enrolled 29 patients diagnosed with OA-DLBCL based on histopathological biopsy between 2006 and 2023.Patients were stratified into two subgroups:primary OA-DLBCL(no prior history of lymphoma)and secondary OA-DLBCL(history of DLBCL at non-ocular adnexal sites).OS was defined as the time interval from OA-DLBCL diagnosis to death from any cause.Survival analysis was performed using the Kaplan–Meier method,and prognostic factors affecting OS were identified using multivariate Cox proportional hazards regression with a stepwise selection approach.RESULTS:The cohort included 24 patients with primary OA-DLBCL(13 males,11 females;mean age:61.36±18.29y)and 5 patients with secondary OA-DLBCL(2 males,3 females;mean age:50.94±18.17y).Among the primary OA-DLBCL subgroup,12 patients(50%)presented with advanced disease(Ann Arbor stage IIIE–IV),and 16 patients(66%)were classified as T4 disease according to the tumor-node-metastasis(TNM)staging system.The mean final visual acuity was 1.72±1.10 in the primary group and 0.90±1.18 in the secondary group.The 5-year OS rate for the entire cohort was 27.7%.Multivariate analysis identified five factors significantly associated with poor survival outcomes:epiphora[adjusted hazard ratio(aHR),36.95],atherosclerotic cardiovascular disease(aHR,10.08),human immunodeficiency virus(HIV)infection(aHR,12.47),M1 stage(aHR,6.99),and secondary OA-DLBCL(aHR,6.03;all P<0.05).The median OS was 1.68y for primary OA-DLBCL and 1.12y for secondary OA-DLBCL.CONCLUSION:A substantial proportion of patients with primary OA-DLBCL present with advanced-stage disease at diagnosis.Epiphora,atherosclerotic cardiovascular disease,HIV infection,M1 stage,and secondary OA-DLBCL are independent prognostic factors for poor survival outcomes.These findings emphasize the urgent need for optimized therapeutic strategies and early screening protocols to improve the management of OA-DLBCL,particularly in developing countries.展开更多
Physics-informed neural networks(PINNs),as a novel artificial intelligence method for solving partial differential equations,are applicable to solve both forward and inverse problems.This study evaluates the performan...Physics-informed neural networks(PINNs),as a novel artificial intelligence method for solving partial differential equations,are applicable to solve both forward and inverse problems.This study evaluates the performance of PINNs in solving the temperature diffusion equation of the seawater across six scenarios,including forward and inverse problems under three different boundary conditions.Results demonstrate that PINNs achieved consistently higher accuracy with the Dirichlet and Neumann boundary conditions compared to the Robin boundary condition for both forward and inverse problems.Inaccurate weighting of terms in the loss function can reduce model accuracy.Additionally,the sensitivity of model performance to the positioning of sampling points varied between different boundary conditions.In particular,the model under the Dirichlet boundary condition exhibited superior robustness to variations in point positions during the solutions of inverse problems.In contrast,for the Neumann and Robin boundary conditions,accuracy declines when points were sampled from identical positions or at the same time.Subsequently,the Argo observations were used to reconstruct the vertical diffusion of seawater temperature in the north-central Pacific for the applicability of PINNs in the real ocean.The PINNs successfully captured the vertical diffusion characteristics of seawater temperature,reflected the seasonal changes of vertical temperature under different topographic conditions,and revealed the influence of topography on the temperature diffusion coefficient.The PINNs were proved effective in solving the temperature diffusion equation of seawater with limited data,providing a promising technique for simulating or predicting ocean phenomena using sparse observations.展开更多
文摘The fusion excitation functions for 12 colliding systems with 96≤Z_(1)Z_(2)≤608 are analyzed using coupled-channel(CC)calculations based on the M3Y double-folding(DF)potential supplemented with a repulsive potential that takes into account the incompressibility of the nuclear matter.We also applied the polarization effects of hot nuclear matter(PEHNM)on the calculations of the bare nucleus-nucleus interaction potential within the framework of the modified density-dependent Seyler-Blanchard(SB)approach in the T^(2)approximation.Our results reveal that we obtain a nice description of the experimental data of different fusion systems when we use the present theoretical approach to calculate the energy-dependent values of the fusion cross sections.In this paper,the influence of the PEHNM on the surface diffuseness parameter of the Woods-Saxon(WS)potential is also studied.In order to reach this goal,we extract the corresponding values of this parameter based on the modified form of the DF potential(M3Y+Repulsion+polarization).We find that the extracted values are located in a range between a=0.61 and 0.80 fm at different incident energies.It seems that the polarization effects of hot nuclear matter play a key role in describing the abnormally large values of the nuclear potential diffusenesses in the heavy-ion fusion reactions.Additionally,the regular decreasing trend for the diffuseness parameter of the nucleus-nucleus potential with the increase in the bombarding energies is also observed.
基金Supported by the National Natural Science Foundation of China(11947229,11675223,11675066)the China Postdoctoral Science Foundation(2019M663853)the Fundamental Research Funds for the Central Universities(lzujbky-2017-ot04)and Feitian Scholar Project of Gansu province。
文摘A radial basis function network(RBFN)approach is adopted for the first time to optimize the calculation of$\alpha$decay half-life in the generalized liquid drop model(GLDM),while concurrently incorporating the surface diffuseness effect.The calculations presented herein agree closely with the experimental half-lives for 68 superheavy nuclei(SHN),achieving a remarkable reduction of 40%in the root-mean-square(rms)deviations of half-lives.Furthermore,using the RBFN method,the half-lives for four SHN isotopes,252-288Rf,272-310Fl,286-316119,and 292-318120,are predicted using the improved GLDM with the diffuseness correction and the decay energies from WS4 and FRDM as inputs.Therefore,we conclude that the diffuseness effect should be embodied in the proximity energy.Moreover,increased application of neural network methods in nuclear reaction studies is encouraged.
基金supported by the National Natural Science Foundation of China,No.82274304(to YH)the Major Clinical Study Projects of Shanghai Shenkang Hospital Development Center,No.SHDC2020CR2046B(to YH)Shanghai Municipal Health Commission Talent Plan,No.2022LJ010(to YH).
文摘Cerebral small vessel disease encompasses a group of neurological disorders characterized by injury to small blood vessels,often leading to stroke and dementia.Due to its diverse etiologies and complex pathological mechanisms,preventing and treating cerebral small vessel vasculopathy is challenging.Recent studies have shown that the glymphatic system plays a crucial role in interstitial solute clearance and the maintenance of brain homeostasis.Increasing evidence also suggests that dysfunction in glymphatic clearance is a key factor in the progression of cerebral small vessel disease.This review begins with a comprehensive introduction to the structure,function,and driving factors of the glymphatic system,highlighting its essential role in brain waste clearance.Afterwards,cerebral small vessel disease was reviewed from the perspective of the glymphatic system,after which the mechanisms underlying their correlation were summarized.Glymphatic dysfunction may lead to the accumulation of metabolic waste in the brain,thereby exacerbating the pathological processes associated with cerebral small vessel disease.The review also discussed the direct evidence of glymphatic dysfunction in patients and animal models exhibiting two subtypes of cerebral small vessel disease:arteriolosclerosis-related cerebral small vessel disease and amyloid-related cerebral small vessel disease.Diffusion tensor image analysis along the perivascular space is an important non-invasive tool for assessing the clearance function of the glymphatic system.However,the effectiveness of its parameters needs to be enhanced.Among various nervous system diseases,including cerebral small vessel disease,glymphatic failure may be a common final pathway toward dementia.Overall,this review summarizes prevention and treatment strategies that target glymphatic drainage and will offer valuable insight for developing novel treatments for cerebral small vessel disease.
基金supported by the National Key Research and Development Program of China(2024YFA1612900)the National Natural Science Foundation of China(Grant No.52103365 and No.12375270)the Guangdong Innovative and Entrepreneurial Research Team Program,China(Grant No.2021ZT09L227).
文摘Fine-grained nuclear graphite is a key material in high-temperature gas-cooled reactors(HTGRs).During air ingress accidents,core graphite components undergo severe oxidation,threatening structural integrity.Therefore,understanding the oxidation behavior of nuclear graphite is essential for reactor safety.The influence of oxidation involves multiple factors,including temperature,sample size,oxidant,impurities,filler type and size,etc.The size of the filler particles plays a crucial role in this study.Five ultrafine-and superfine-grained nuclear graphite samples(5.9-34.4μm)are manufactured using identical raw materials and manufacturing processes.Isothermal oxidation tests conducted at 650℃-750℃ are used to study the oxidation behavior.Additionally,comprehensive characterization is performed to analyze the crystal structure,surface morphology,and nanoscale to microscale pore structure of the samples.Results indicate that oxidation behavior cannot be predicted solely based on filler grain size.Reactive site concentration,characterized by active surface area,dominates the chemical reaction kinetics,whereas pore tortuosity,quantified by the structural parameterΨ,plays a key role in regulating oxidant diffusion.These findings clarify the dual role of microstructure in oxidation mechanisms and establish a theoretical and experimental basis for the design of high-performance nuclear graphite capable of long-term service in high-temperature gas-cooled reactors.
基金The National Natural Science Foundations of China (12202219)the Natural Science Foundations of Ningxia (2024AAC02009, 2023AAC05001)the Ningxia Youth Top Talents Training Project。
文摘The fast solution of linear equations has always been one of the hot spots in scientific computing.A kind of the diagonal matrix splitting iteration methods are provided,which is different from the classical matrix splitting methods.Taking the decomposition of the diagonal elements for coefficient matrix as the key point,some new preconditioners are constructed.Taking the tri-diagonal coefficient matrix as an example,the convergence domains and optimal relaxation factor of the new method are analyzed theoretically.The presented new iteration methods are applied to solve linear algebraic equations,even 2D and 3D diffusion problems with the fully implicit discretization.The results of numerical experiments are matched with the theoretical analysis,and show that the iteration numbers are reduced greatly.The superiorities of presented iteration methods exceed some classical iteration methods dramatically.
基金supported by the Cultivation Program for Major Scientific Research Projects of Harbin Institute of Technology(ZDXMPY20180109).
文摘Scalable simulation leveraging real-world data plays an essential role in advancing autonomous driving,owing to its efficiency and applicability in both training and evaluating algorithms.Consequently,there has been increasing attention on generating highly realistic and consistent driving videos,particularly those involving viewpoint changes guided by the control commands or trajectories of ego vehicles.However,current reconstruction approaches,such as Neural Radiance Fields and 3D Gaussian Splatting,frequently suffer from limited generalization and depend on substantial input data.Meanwhile,2D generative models,though capable of producing unknown scenes,still have room for improvement in terms of coherence and visual realism.To overcome these challenges,we introduce GenScene,a world model that synthesizes front-view driving videos conditioned on trajectories.A new temporal module is presented to improve video consistency by extracting the global context of each frame,calculating relationships of frames using these global representations,and fusing frame contexts accordingly.Moreover,we propose an innovative attention mechanism that computes relations of pixels within each frame and pixels in the corresponding window range of the initial frame.Extensive experiments show that our approach surpasses various state-of-the-art models in driving video generation,and the introduced modules contribute significantly to model performance.This work establishes a new paradigm for goal-oriented video synthesis in autonomous driving,which facilitates on-demand simulation to expedite algorithm development.
基金Supported by the National Natural Science Foundation of China(Grant No.12261081).
文摘In this paper,we are concerned with the stability of traveling wavefronts of a Belousov-Zhabotinsky model with mixed nonlocal and degenerate diffusions.Such a system can be used to study the competition among nonlocally diffusive species and degenerately diffusive species.We prove that the traveling wavefronts are exponentially stable,when the initial perturbation around the traveling waves decays exponentially as x→-∞,but in other locations,the initial data can be arbitrarily large.The adopted methods are the weighted energy with the comparison principle and squeezing technique.
基金supported by the National Natural Science Foundation of China(Grant No.U23A2022)the National Natural Science Foundation of China(Grant No.52474047)+2 种基金the Natural Science Foundation of Chongqing(Grant No.CSTB2024NSCQ-MSX0951)the Natural Science Foundation of Sichuan Province(Grant No.2025ZNSFSC1357)the National Science and Technology Major Project(Grant No.2025ZD1404307).
文摘Injecting impure CO_(2)for enhanced gas recovery(CO_(2)-EGR)offers a dual benefit by improving natural gas extraction while enabling CO_(2)sequestration.However,the interactions between CO_(2),N_(2),and CH_(4)under reservoir conditions require further investigation.This study employs Grand Canonical Monte Carlo(GCMC)and Molecular Dynamics(MD)simulations to quantify the adsorption and diffusion behaviors of CO_(2),N_(2),and CH_(4)in quartz nanopores over a pressure range of 1-24 MPa under varying water saturations and gas compositions.The results indicate that:(1)CO_(2)exhibits the broadest energy distribution and the strongest adsorption stability,occupying about 20%-30%more adsorption sites than CH_(4)or N_(2)and showing the least sensitivity to water saturation,with only a 30%reduction at 50%saturation,compared to 60%for CH_(4),giving CO_(2)a clear competitive advantage.(2)The adsorption and desorption behaviors are strongly pressure dependent,as increasing pressure reduces the adsorption layer area and shifts gas distribution from adsorption dominated to free phase.Competitive adsorption analysis reveals that while CO_(2)dominates displacement at low pressures,mixtures that contain N_(2)achieve higher CH_(4)desorption efficiency above 13 MPa by mitigating diffusion resistance.(3)A higher N_(2)fraction improves CH_(4)diffusion coefficients,thereby facilitating gas mobility and ensuring superior recovery performance under high-pressure conditions.This study advances the fundamental knowledge of microscale gas behavior in tight sandstones and supports the feasibility of impure CO_(2)injection as a practical strategy for sustainable gas production.
基金supported by the National Natural Science Foundation of China (Nos.22174067,22204078,and 22374077)the Natural Science Foundation of Jiangsu Province of China (No.BK20220370)+3 种基金Jiangsu Provincial Department of Education (No.22KJB150009)State Key Laboratory of Analytical Chemistry for Life Science (No.SKLACLS2218)the Priority Academic Program Development of Jiangsu Higher Education Institutions,Jiangsu Association for Science and Technology (No.TJ-2023-076)Shanghai Synchrotron Radiation Facility Beamline BL17B1 (No.2021-NFPSPT-006657)。
文摘This research explores the influence of crystallinity on gas chromatographic(GC) separation using covalent organic frameworks(COFs) as stationary phases.Three COF materials(CTF-DCBs) with varying crystallinity were synthesized and characterized.CTF-DCB-1,with superior crystallinity,demonstrated highselectivity GC separation of benzene isomers as well as styrene/phenylacetylene mixtures,while CTFDCB-2 and CTF-DCB-3 exhibited lower crystallinity and worse separation performance.Thermodynamic and kinetic tests showed that CTF-DCB-1 had the worst thermodynamic adsorption but low diffusion mass transfer resistance,which resulted in the best separation.Therefore,optimizing the crystallinity of COFs is necessary for balancing the kinetic diffusion and thermodynamic interactions towards the analytes,achieving high-performance GC stationary phases.
基金supported by the National Natural Science Foundation of China(52172227)the Natural Science Foundation of Hubei Province(2023AFA114)+2 种基金the Guizhou Provincial Key Technology R&D Program(ZD[2025]019)Additional funding was provided by the Startup Fund(20QD80 and 22QD28)The authors also acknowledge support from the Science&Technology Top Talents Program of Guizhou Province([2024]349).We gratefully acknowledge Beijing SciStar Technology Co.,Ltd.for in-situ measurements and analysis.
文摘Prussian blue analogs(PBAs)have emerged as environmentally friendly and structurally tunable cathode materials for aqueous ammonium-ion batteries(AIBs).However,the fundamental role of crystalline H_(2)O in regulating ammonium-ion storage and transport remains poorly understood.In this study,we present a comprehensive comparison between hydrated NH_(4)NiHCF-H_(2)O and its anhydrous counterpart NH_(4)NiHCF,revealing the critical contribution of interstitial water to electrochemical performance.Structural and spectroscopic analyses confirm that interstitial water forms robust hydrogen bonds with NH_(4)+ions,stabilizing the PBA framework and mitigating structural degradation during cycling.Electrochemical measurements show that NH_(4)NiHCF-H_(2)O delivers a significantly higher specific capacity of 61 mA h g^(−1)at 0.2 C and markedly improved rate performance compared to NH_(4)NiHCF(48 mA h g^(−1)at 0.2 C).Kinetic analysis reveals that interstitial water enhances NH_(4)+diffusion,as evidenced by higher diffusion coefficients.Furthermore,density functional theory(DFT)calculations demonstrate that crystal water acts as a hydrogen bond acceptor,preferentially interacting with NH_(4)+and reducing the migration energy barrier,thereby facilitating fast ion transport.This work provides fundamental insights into the role of crystal water in PBAs and offers a rational design strategy for improving the kinetics,structural stability of PBAs cathodes for AIBs.
基金supported by the National Natural Science Foundation of China(Grant No.52574278)the Xinjiang Uygur Autonomous Region Key R&D Program Project(Grant No.2024B01003).
文摘This paper examines how natural gas disperses vertically when high-pressure pipelines with large openings fail in unconfined environments,providing insight into hazardous gas cloud development and behavior.A comprehensive study was conducted using a full-scale field experiment(1,219 mm diameter,12 MPa pressure,100 mm aperture)combined with a validated computational fluid dynamics(CFD)numerical simulation model to systematically analyze the coupling effects of pipeline pressure and ambient wind speed.The results indicate that:(1)Pipeline pressure determines the vertical jet scale,where jet height is positively correlated with pressure;at 12 MPa,the maximum jet height reaches 69.4 m(approximately 2.65 times that at 4 MPa),and the lower explosive limit(LEL)cloud area follows a quadratic polynomial trend.(2)Ambient wind speed significantly alters the diffusion trajectory;at a wind speed of 10 m/s,the LEL gas cloud area expands by 1.69 times compared to calm conditions,while the jet height is suppressed to 29.9%of the calm wind value.(3)Our developed dynamic prediction model for the hazardous gas-cloud region achieves a determination coefficient of 0.975 and maintaining prediction errors maintained within approximately 12%.The proposed empirical correlations and dynamic prediction model provide essential quantitative data support for safety-distance design and emergency-response decision-making for high-pressure natural gas pipelines.
基金support from the Central South University Fundamental Research Funds(Grant No.2025ZZTS0444)the Innovation-Driven Research Program(Grant No.2023 CXQD053)+2 种基金The authors acknowledge the National Natural Science Foundation of China(Grant No.52274310)The authors thank the financial support(Project No.H202111040350002)the provision of the hydroxide precursors from Ningbo Ronbay New Energy Technology Co.,Ltd.This work was supported in part by the High-Performance Computing Center of Central South University.The authors would also like to thank Jialin Wu from Shiyanjia Lab(www.shiyanjia.com)for the HTXRD analysis.
文摘Cation disordering is a common issue in Ni-rich cathodes that significantly degrades cycle life and compromises safety.The cubic rock-salt phase formation and the slow oxidation kinetics of Ni^(2+)during solid-state sintering are widely recognized as the principal causes of these structural defects.To solve this issue,a topotactic soft-chemical precursor engineering strategy is proposed for use in aqueous solution.By utilizing the layered structure of the precursor,this method allows for selective proton extraction and efficient Ni^(2+)oxidation,along with rapid Li+intercalation to form a layered lithiated intermediate.This intermediate crystallizes without further phase transitions during subsequent heat treatment,preventing structural defects caused by complex phase evolution and slow ion diffusion.The resulting cathode exhibits a long-range ordered layered structure and a uniform phase distribution,enabling efficient Li+insertion and extraction.Electrochemical tests reveal a high discharge capacity of 229.6 mAh g^(−1)and an initial coulombic efficiency of 95.77%at 0.1 C,greatly exceeding the performance of a conventionally synthesized cathode(210.3 mAh g^(−1),88.93%).Improved Li^(+)transport kinetics reduces phase-transition hysteresis and alleviates stress concentration,resulting in better cycling stability with a capacity retention of 85.3%after 300 cycles,compared to 61.5%for the conventional sample.This work presents a scalable and effective synthesis route for Ni-rich cathodes with reduced structural disorder and extended lifespan,providing valuable insights into how the regulation of intermediate phases influences electrochemical performance in high-performance Ni-rich cathodes.
基金supported by the National Natural Science Foundation Joint Fund,No.U22A20309(to PY)the Natural Science Foundation of LiaoningProvince,No.2023-MS-07(to HuL)the Unveiling Key Scientific and Technological Projects of Liaoning Province,No.2021JH1/10400051(to HuL).
文摘Some patients with systemic lupus erythematosus experience neuropsychiatric symptoms.Although magnetic resonance imaging can detect abnormal signals in the white matter of the brain,conventional methods often struggle to accurately capture microstructural changes.Various diffusion models have been used to study white matter in systemic lupus erythematosus;however,comparative analyses of their sensitivity and specificity for detecting microstructural changes remain insufficient.To address this,our team designed a diagnostic trial that used multimodal diffusion imaging techniques to observe white matter microstructural changes in patients with systemic lupus erythematosus who had neuropsychiatric symptoms,with an aim to identify key diagnostic biomarkers for these patients.Patients with active lupus who received treatment at the Department of Rheumatology and Immunology,The First Affiliated Hospital of China Medical University,from September 2023 to March 2024 were recruited.According to the standards of the American College of Rheumatology,patients with systemic lupus erythematosus who had neuropsychiatric symptoms were assigned to the systemic lupus erythematosus group,whereas those without neuropsychiatric symptoms were assigned to the non-systemic lupus erythematosus group.Additionally,healthy volunteers matched by region,sex,and age were recruited as controls.All three groups underwent the same diffusion magnetic resonance imaging examination protocol to compare differences in diffusion parameters.Advanced diffusion imaging models were able to sensitively detect microstructural changes in the white matter fibers of patients with systemic lupus erythematosus who had neuropsychiatric symptoms,with specific diffusion parameters showing significant abnormalities in key brain regions.In the left superior longitudinal fasciculus subregion and the right thalamic radiations of patients with systemic lupus erythematosus who had neuropsychiatric symptoms,we also identified abnormal diffusion characteristics that were clearly correlated with disease activity,suggesting that microstructural changes in these areas may reflect the dynamic process of neuroinflammatory damage.The present study addresses critical challenges in the diagnosis of systemic lupus erythematosus by identifying specific white matter imaging biomarkers and elucidating the association between microstructural damage and clinical manifestations.The main contributions of our study include:1)establishing axial regression probability parameters from mean apparent propagator magnetic resonance imaging as sensitive biomarkers for systemic lupus erythematosus,particularly in the third subregion of the left superior longitudinal fasciculus;2)demonstrating that multimodal diffusion imaging may be superior to conventional diffusion tensor imaging for detecting white matter microstructural abnormalities in patients with systemic lupus erythematosus;and 3)integrating tract-based spatial statistics with clinically relevant analyses to link imaging findings to pathological mechanisms.
文摘Inverse design of advanced materials represents a pivotal challenge in materials science.Leveraging the latent space of Variational Autoencoders(VAEs)for material optimization has emerged as a significant advancement in the field of material inverse design.However,VAEs are inherently prone to generating blurred images,posing challenges for precise inverse design and microstructure manufacturing.While increasing the dimensionality of the VAE latent space can mitigate reconstruction blurriness to some extent,it simultaneously imposes a substantial burden on target optimization due to an excessively high search space.To address these limitations,this study adopts a Variational Autoencoder guided Conditional Diffusion Generative Model(VAE-CDGM)framework integrated with Bayesian optimization to achieve the inverse design of composite materials with targeted mechanical properties.The VAE-CDGM model synergizes the strengths of VAEs and Denoising Diffusion Probabilistic Models(DDPM),enabling the generation of high-quality,sharp images while preserving a manipulable latent space.To accommodate varying dimensional requirements of the latent space,two optimization strategies are proposed.When the latent space dimensionality is excessively high,SHapley Additive exPlanations(SHAP)sensitivity analysis is employed to identify critical latent features for optimization within a reduced subspace.Conversely,direct optimization is performed in the low-dimensional latent space of VAE-CDGM when dimensionality is modest.The results demonstrate that both strategies accurately achieve the targeted design of composite materials while circumventing the blurred reconstruction flaws of VAEs,which offers a novel pathway for the precise design of advanced materials.
基金financially supported by the National Natural Science Foundation of China(No.5247401)the Research and Technology Development Project of the China National Petroleum Corporation(No.2021DJ5002(JT))。
文摘This study integrates experimental investigation with molecular dynamics simulations to elucidate the hydrogen transport mechanisms in polyetheretherketone(PEEK)and polytetrafluoroethylene(PTFE),offering fundamental insights into the barrier properties of high-performance polymeric materials.Experimental results demonstrate that PEEK exhibits superior hydrogen barrier performance compared to PTFE at both ambient and elevated temperatures.However,detailed molecular dynamics simulations uncover a distinctive,enthalpy-driven"high solubility-low diffusivity"transport mechanism:although PEEK displays higher hydrogen solubility due to its stronger thermodynamic affinity,its diffusion coefficient is markedly lower than that of PTFE.This mechanism remains operative across a broad operational temperature range(233 K to358 K),yet its influence on overall permeability is strongly temperature-dependent.At room and high temperatures,the exceptionally low diffusivity of PEEK governs the entire permeation process,establishing its effectiveness as a high-performance hydrogen barrier material.In contrast,under low-temperature conditions(e.g.,233 K),the general suppression of diffusion allows the high solubility of PEEK to dominate,resulting in greater overall permeability than PTFE and giving rise to a performance“reversal”phenomenon.This distinct transport behavior originates from the strong non-covalent interactions between hydrogen molecules and the aromatic rings as well as polar functional groups present in the amorphous regions of PEEK,which simultaneously enhance solubility and impose significant kinetic energy barriers.The"structure-mechanism"correlation framework established in this work provides a robust theoretical foundation for the rational design of next-generation hydrogen barrier materials tailored to specific operational temperature requirements.
基金supported by the National Natural Science Foundation of China(Grant No.72161034).
文摘Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.
基金Supported by the Faculty of Medicine,Prince of Songkla University.Wainipitapong S has received grants from the Faculty of Medicine,Prince of Songkla University。
文摘AIM:To investigate the clinical characteristics and treatment outcomes,including visual function and overall survival(OS)of patients with ocular adnexal diffuse large B-cell lymphoma(OA-DLBCL).METHODS:This retrospective cohort study enrolled 29 patients diagnosed with OA-DLBCL based on histopathological biopsy between 2006 and 2023.Patients were stratified into two subgroups:primary OA-DLBCL(no prior history of lymphoma)and secondary OA-DLBCL(history of DLBCL at non-ocular adnexal sites).OS was defined as the time interval from OA-DLBCL diagnosis to death from any cause.Survival analysis was performed using the Kaplan–Meier method,and prognostic factors affecting OS were identified using multivariate Cox proportional hazards regression with a stepwise selection approach.RESULTS:The cohort included 24 patients with primary OA-DLBCL(13 males,11 females;mean age:61.36±18.29y)and 5 patients with secondary OA-DLBCL(2 males,3 females;mean age:50.94±18.17y).Among the primary OA-DLBCL subgroup,12 patients(50%)presented with advanced disease(Ann Arbor stage IIIE–IV),and 16 patients(66%)were classified as T4 disease according to the tumor-node-metastasis(TNM)staging system.The mean final visual acuity was 1.72±1.10 in the primary group and 0.90±1.18 in the secondary group.The 5-year OS rate for the entire cohort was 27.7%.Multivariate analysis identified five factors significantly associated with poor survival outcomes:epiphora[adjusted hazard ratio(aHR),36.95],atherosclerotic cardiovascular disease(aHR,10.08),human immunodeficiency virus(HIV)infection(aHR,12.47),M1 stage(aHR,6.99),and secondary OA-DLBCL(aHR,6.03;all P<0.05).The median OS was 1.68y for primary OA-DLBCL and 1.12y for secondary OA-DLBCL.CONCLUSION:A substantial proportion of patients with primary OA-DLBCL present with advanced-stage disease at diagnosis.Epiphora,atherosclerotic cardiovascular disease,HIV infection,M1 stage,and secondary OA-DLBCL are independent prognostic factors for poor survival outcomes.These findings emphasize the urgent need for optimized therapeutic strategies and early screening protocols to improve the management of OA-DLBCL,particularly in developing countries.
基金Supported by the National Key Research and Development Program of China(No.2023YFC3008200)the Independent Research Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(No.SML2022SP505)。
文摘Physics-informed neural networks(PINNs),as a novel artificial intelligence method for solving partial differential equations,are applicable to solve both forward and inverse problems.This study evaluates the performance of PINNs in solving the temperature diffusion equation of the seawater across six scenarios,including forward and inverse problems under three different boundary conditions.Results demonstrate that PINNs achieved consistently higher accuracy with the Dirichlet and Neumann boundary conditions compared to the Robin boundary condition for both forward and inverse problems.Inaccurate weighting of terms in the loss function can reduce model accuracy.Additionally,the sensitivity of model performance to the positioning of sampling points varied between different boundary conditions.In particular,the model under the Dirichlet boundary condition exhibited superior robustness to variations in point positions during the solutions of inverse problems.In contrast,for the Neumann and Robin boundary conditions,accuracy declines when points were sampled from identical positions or at the same time.Subsequently,the Argo observations were used to reconstruct the vertical diffusion of seawater temperature in the north-central Pacific for the applicability of PINNs in the real ocean.The PINNs successfully captured the vertical diffusion characteristics of seawater temperature,reflected the seasonal changes of vertical temperature under different topographic conditions,and revealed the influence of topography on the temperature diffusion coefficient.The PINNs were proved effective in solving the temperature diffusion equation of seawater with limited data,providing a promising technique for simulating or predicting ocean phenomena using sparse observations.
