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Evaluation of Parametric Limitations in Simulating Greenhouse Gas Fluxes from Irish Arable Soils Using Three Process-Based Models 认领 引用
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作者 Mohammad I. Khalil Mohamed Abdalla +2 位作者 Gary Lanigan Bruce Osborne Christoph Müller 《Agricultural Sciences》 2016年第8期503-520,共18页
Globally a large number of process-based models have been assessed for quantification of agricultural greenhouse gas (GHG) emissions. Modelling approaches minimize the presence of spatial variability of biogeochemical... Globally a large number of process-based models have been assessed for quantification of agricultural greenhouse gas (GHG) emissions. Modelling approaches minimize the presence of spatial variability of biogeochemical processes, leading to improved estimates of GHGs as well as identifying mitigation and policy options. The comparative performance of the three dynamic models (e.g., DNDC v9.4, DailyDayCent and ECOSSE v5+) with minimum numbers of common input parameters was evaluated against measured variables. Simulations were performed on conventionally-tilled spring barley crops receiving N fertilizer at 135 - 159 kg·N·ha-1·yr-1 and crop residues at 3 t·ha-1·yr-1. For surface soil nitrate (0 - 10 cm), the ECOSSE and DNDC simulated values showed significant correlations with measured values (R2 = 0.31 - 0.55, p 0.05). Only the ECOSSE-simulated N2O fluxes showed a significant relationship (R2 = 0.33, p 0.05) with values measured from fertilized fields, but not with unfertilized ones. The DNDC and DailyDayCent models significantly underestimated seasonal/annual N2O fluxes compared to ECOSSE, with emission factors (EFs), based on an 8-year average, were 0.09%, 0.31% and 0.52%, respectively. Predictions of ecosystem respiration by both DailyDayCent and DNDC showed reasonable agreement with Eddy Covariance data (R2 = 0.34 - 0.41, p 0.05). Compared to the measured value (3624 kg·C·ha-1·yr-1), the ECOSSE underestimated annual heterotrophic respiration by 7% but this was smaller than the DNDC (50%) and DailyDayCent (24%) estimates. All models simulated CH4 uptake we 展开更多
关键词 Greenhouse Gases Arable Lands Input Parameters Process-Based Models Ireland
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Integrating process-based and deep learning models for flood simulation in karst basins 认领 引用
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作者 Bin-quan Li Yi-jie Xia +3 位作者 Si-ji Tao Yun-yao Chen Jian-fei Zhao Zhong-min Liang 《Water Science and Engineering》 EI CAS CSCD 2026年第1期23-34,共12页
Flood process simulation in karst basins is challenging due to complex runoff generation and concentration mechanisms,often resulting in low accuracy.This study investigated two typical karst basins(the Maiweng and Li... Flood process simulation in karst basins is challenging due to complex runoff generation and concentration mechanisms,often resulting in low accuracy.This study investigated two typical karst basins(the Maiweng and Liudong river basins)in Guizhou Province,China,and developed two hydrological models for flood simulation:the karst-Xin'anjiang(Karst-XAJ)model,a modified Xin'anjiang(XAJ)hydrological model adapted for karst runoff characteristics,and the long short-term memory(LSTM)deep learning model.Their performances were compared,and their results were integrated using Bayesian model averaging(BMA).The Karst-XAJ model accurately simulated flood peak time and runoff depth but showed limited peak flow accuracy.The LSTM model performed well within a 2-h computational window,with accuracy declining for longer computational windows(3-4 h)yet maintaining a Nash-Sutcliffe model efficiency coefficient above 0.7.The BMA approach further enhanced simulation accuracy beyond individual models.Overall,both models effectively captured flood dynamics in karst basins,with the LSTM model achieving superior precision.This study offers a novel framework for simulating flood processes in karst regions with complex runoff processes. 展开更多
关键词 Karst basin Karst-Xin'anjiang model Long short-term memory neural network Bayesian model averaging Flood simulation
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Process-based nursing using explanation-simulation-practicecommunication-support model for pain management after liver cancer intervention 认领 引用
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作者 Ri-Hong Qian Yan Xu 《World Journal of Gastrointestinal Oncology》 SCIE 2026年第7期149-156,共8页
BACKGROUND Liver cancer is highly prevalent and fatal;transcatheter arterial chemoembolization is its main interventional therapy.Post-transcatheter arterial chemoembolization pain is common and affects recovery,deman... BACKGROUND Liver cancer is highly prevalent and fatal;transcatheter arterial chemoembolization is its main interventional therapy.Post-transcatheter arterial chemoembolization pain is common and affects recovery,demanding optimized nursing strategies.AIM To explore the application of process-based nursing using the Explain-Simulate-Practice-Communication-Support(ESPCS)model for pain management after interventional therapy for liver cancer.METHODS A total of 500 patients who underwent interventional therapy for liver cancer and were admitted to Ganzhou Fifth People’s Hospital between January 2022 and January 2025 were selected and divided into a control group(n=250,treated with routine nursing intervention)and an observation group(n=250,treated with process-based nursing intervention using the ESPCS model)using a random number table method.Both groups received the intervention until discharge.The Visual Analog Scale scores at 2 hours,6 hours,12 hours,and 24 hours after surgery,the scores of the Hospital Anxiety and Depression Scale(HADS),and the Functional Assessment of Cancer Therapy-General before and after intervention,and the incidence of complications were compared between the two groups.RESULTS At 2 hours,6 hours,12 hours,and 24 hours postoperatively,the Visual Analog Scale scores in the observation group were significantly lower than those in the control group(2 hours:4.18±0.85 vs 4.36±1.03,P=0.034;6 hours:3.31±0.67 vs 3.69±0.82,P<0.001;12 hours:2.89±0.58 vs 3.13±0.65,P<0.001;24 hours:1.82±0.69 vs 2.51±0.82,P<0.001).After intervention,HADS-Anxiety and HADS-Depression scores were significantly lower in the observation group than in the control group(HADS-Anxiety:7.15±1.57 vs 8.43±1.82;HADS-Depression:6.72±1.49 vs 7.26±1.76;both P<0.001).Functional Assessment of Cancer Therapy-General domain scores in the observation group were significantly higher than those in the control group,including physical well-being(26.25±3.01 vs 24.40±2.77),social/family well-being(18.33±2.65 vs 16.06±2.12),emotional well-being(28.35±3.43 vs 25.70±3.12),and functional well-being(18.45±3.03 vs 16.84±2.86)(all P<0.001).The incidence of complications was significantly lower in the observation group than in the control group(3.20%vs 7.20%,P=0.044).CONCLUSION Process-based nursing interventions based on the ESPCS model can effectively alleviate the degree of pain in patients after interventional therapy for liver cancer,improve their psychological state and quality of life,and reduce the incidence of complications. 展开更多
关键词 Liver cancer Interventional therapy Explain-Simulate-Practice-Communication-Support model Process-based nursing Pain management
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Ecosystem service models are indeed being validated:A response to Pereira et al.(2025) 认领 引用 被引量：1
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作者 James M.Bullock Danny A.P.Hooftman +1 位作者 John W.Redhead Simon Willcock 《Geography and Sustainability》 CSCD 2026年第1期247-248,共2页
In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation ... In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation is provided”and that“the validation step is largely overlooked”.This assertion may have been true several years ago,for example,when Ochoa and Urbina-Cardona(2017)made a similar observation.However,there has been much work on ES model validation over the last decade. 展开更多
关键词 evaluation mapping modeling es model ecosystem services validation
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AI and Deep Learning for Terahertz Ultra-Massive MIMO:From Model-Driven Approaches to Foundation Models 认领 引用 被引量：1
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作者 Wentao Yu Hengtao He +4 位作者 Shenghui Song Jun Zhang Linglong Dai Lizhong Zheng Khaled B.Letaief 《Engineering》 SCIE EI CSCD 2026年第1期14-33,共20页
This study explored the transformative potential of artificial intelligence(AI)in addressing the challenges posed by terahertz ultra-massive multiple-input multiple-output(UM-MIMO)systems.It begins by outlining the ch... This study explored the transformative potential of artificial intelligence(AI)in addressing the challenges posed by terahertz ultra-massive multiple-input multiple-output(UM-MIMO)systems.It begins by outlining the characteristics of terahertz UM-MIMO systems and identifies three primary challenges for transceiver design:computational complexity,modeling difficulty,and measurement limitations.The study posits that AI provides a promising solution to these challenges.Three systematic research roadmaps are proposed for developing AI algorithms tailored to terahertz UM-MIMO systems.The first roadmap,model-driven deep learning(DL),emphasizes the importance of leveraging available domain knowledge and advocates the adoption of AI only to enhance bottleneck modules within an established signal processing or optimization framework.Four essential steps are discussed:algorithmic frameworks,basis algorithms,loss function design,and neural architecture design.The second roadmap presents channel state information(CSI)foundation models,aimed at unifying the design of different transceiver modules by focusing on their shared foundation,that is,the wireless channel.The training of a single compact foundation model is proposed to estimate the score function of wireless channels,which serve as a versatile prior for designing a wide variety of transceiver modules.Four essential steps are outlined:general frameworks,conditioning,site-specific adaptation,and the joint design of CSI foundation models and model-driven DL.The third roadmap aims to explore potential directions for applying pretrained large language models(LLMs)to terahertz UM-MIMO systems.Several application scenarios are envisioned,including LLM-based estimation,optimization,search,network management,and protocol understanding.Finally,the study highlights open problems and future research directions. 展开更多
关键词 Terahertz communications Ultra-massive multiple-input multiple-output Model-driven deep learning Foundation models Large language models
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Evaluating the Shanghai Typhoon Model against State-of-the-Art Machine-Learning Weather Prediction Models:A Case Study for Typhoon Danas(2025) 认领 引用 被引量：1
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作者 Zeyi NIU Wei HUANG +5 位作者 Yuhua YANG Mengqi YANG Lin DENG Haibo WANG Hong LI Xu ZHANG 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2026年第4期744-750,共7页
This study traces the development of the Shanghai Typhoon Model(SHTM)from a traditional physics-based regional model toward a data-driven,machine-learning typhoon forecasting system.After upgrading its initial and bou... This study traces the development of the Shanghai Typhoon Model(SHTM)from a traditional physics-based regional model toward a data-driven,machine-learning typhoon forecasting system.After upgrading its initial and boundary conditions,SHTM now leverages large-scale constraints from machine-learning weather prediction(MLWP)models,resulting in an ML–physics hybrid framework.During Typhoon Danas(2025),the hybrid SHTM achieves substantially lower track errors than both the advanced ECMWF Integrated Forecasting System(IFS)and leading MLWP models such as PanGu and FuXi.Furthermore,the hybrid SHTM consistently maintains mean track errors below 200 km up to a forecast lead time of 108 hours,representing a significant advancement in forecast accuracy.In addition,this study highlights the technical roadmap for transitioning from a physics-based typhoon model to a fully data-driven ML typhoon forecast system.It also emphasizes that advances in the physical modeling framework provide a critical foundation for further improving the performance of future data-driven ML typhoon models. 展开更多
关键词 Shanghai Typhoon Model(SHTM) machine-learning weather prediction machine learning-physics hybrid model
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Data-driven computing ligament loading mechanisms:integration of the computational ligament mechanics models with deep learning 认领 引用 被引量：1
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作者 Datao Xu Huiyu Zhou +7 位作者 Yi Yuan Zanni Zhang Tianle Jie Zhifeng Zhou Zixiang Gao Liangliang Xiang Meizi Wang Yaodong Gu 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第5期628-672,共45页
Ankle injuries account for more than 25%of sports-related injuries.However,there is a lack of computational mechanics modeling and assessment tools for the ligament loading mechanism(LLM)caused by ankle injury.This st... Ankle injuries account for more than 25%of sports-related injuries.However,there is a lack of computational mechanics modeling and assessment tools for the ligament loading mechanism(LLM)caused by ankle injury.This study combines medical imaging data to construct the subject-specific ankle musculoskeletal model,which considers the subject's individualized characteristics and ligamentous attributes.Furthermore,we developed the structural constitutive model to restore the nonlinear short-term viscoelastic properties of the ligament-dense connective tissue,which can more realistically revert the LLM and reveal the mechanical properties of ankle injury.Based on the computational ligament mechanics(CLM)model,we developed a deep learning-based prediction model to predict LLM by CLM data-driven modeling.The modeling simulation results are highly consistent with the calculation results from the dual fluoroscopic imaging system,which demonstrated that the CLM model has high accuracy.The data-driven modeling performs exceptionally well in predicting ligament loading forces.The findings indicate that the constructed CLM data-driven model has the potential to enhance the accuracy and safety of ankle rehabilitation robots,while also providing personalized,dynamically adjusted rehabilitation training programs.The proposed comprehensive solutions would bring benefits to more patients with sports injuries and the general rehabilitation population,and promote the development and advancement of the research field of CLM and biomechanical variable prediction. 展开更多
关键词 Computational ligament mechanics Subject-specific musculoskeletal model Structural constitutive model Ankle ligament injury mechanisms Biomechanical variable prediction
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A decision framework for rural domestic sewage treatment models and process:Evidence from Inner Mongolia Autonomous Region,China 认领 引用 被引量：1
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作者 Ying Yan Pengyu Li +5 位作者 Zixuan Wang Yubo Tan Tianlong Zheng Jianguo Liu Xiaoxia Yang Junxin Liu 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2026年第1期302-311,共10页
Rural domestic sewage treatment is critical for environmental protection.This study defines the spatial pattern of villages from the perspective of rural sewage treatment and develops an integrated decision-making sys... Rural domestic sewage treatment is critical for environmental protection.This study defines the spatial pattern of villages from the perspective of rural sewage treatment and develops an integrated decision-making system to propose a sewage treatment mode and scheme suitable for local conditions.By considering the village spatial layout and terrain factors,a decision tree model of residential density and terrain type was constructed with accuracies of 76.47%and 96.00%,respectively.Combined with binary classification probability unit regression,an appropriate sewage treatment mode for the village was determined with 87.00%accuracy.The Analytic Hierarchy Process(AHP),combined with the Technique for Order Preference(TOPSIS)by Similarity to an Ideal Solution model,formed the basis for optimal treatment process selection under different emission standards.Verification was conducted in 542 villages across three counties of the Inner Mongolia Autonomous Region,focusing on the standard effluent effect(0.3773),low investment cost(0.3196),and high standard effluent effect(0.5115)to determine the best treatment process for the same emission standard under different needs.The annual environmental and carbon emission benefits of sewage treatment in these villages were estimated.This model matches village density,geographic feature,and social development level,and provides scientific support and a theoretical basis for rural sewage treatment decision-making. 展开更多
关键词 Rural domestic sewage Sewage treatment model Decision-making Environmental-economic benefits Inner Mongolia
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Amelioration of behavioral and neural deficits in animal models of neurodegenerative disease by nanoformulations of curcumin and quercetin 认领 引用 被引量：3
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作者 Bridget Martinez Philip V.Peplow 《Neural Regeneration Research》 SCIE CAS CSCD 2026年第8期3311-3322,共12页
Neurodegenerative diseases are increasing in prevalence due largely to aging populations worldwide and improved medical care for the elderly.Currently approved drugs can reduce some of the symptoms of neurodegenerativ... Neurodegenerative diseases are increasing in prevalence due largely to aging populations worldwide and improved medical care for the elderly.Currently approved drugs can reduce some of the symptoms of neurodegenerative diseases but cannot cure them.Inflammation is involved in the development and progression of neurodegenerative diseases,and oxidative stress is implicated in neurodegeneration associated with cognitive decline and age-related cognitive impairment.Polyphenols such as curcumin,quercetin,and resveratrol possess potent anti-inflammatory and antioxidant properties.Nanoformulations of curcumin and quercetin can optimize their pharmacological effects in the treatment of neurodegenerative diseases.Nanocarriers play a crucial role in delivering drugs across the blood-brain barrier,thereby lowering the risk of peripheral side effects.Various nanoforms have been developed to induce bioavailability and solubility of curcumin and quercetin,including nanoparticles and nanoemulsions.The studies reviewed included 17 using curcumin nanoformulations and seven with quercetin nanoformulations and were tested in widely used animal models of Alzheimer’s disease,Parkinson’s disease,Huntington’s disease,and multiple sclerosis.Many of the curcumin and quercetin nanoformulations brought about improvements in learning and memory in behavioral tests of Alzheimer’s disease models and were effective in reducing oxidative stress in the brain.Both nanocurcumin and nanoquercetin decreased the levels of inflammatory markers in the brain.Nanocurcumin formulations improved motor behavior,gait,and memory in Parkinson’s disease models and increased dopaminergic neurons in the striatum and substantia nigra.Furthermore,nanocurcumin improved locomotor activity,memory,and learning,and the number of dendrites of medium spiny neurons in Huntington’s disease models.Nanocurcumin formulations decreased oxidative stress and inflammation in a model of demyelination.Several important limitations were identified in the studies reviewed and these need to be considered in future studies.Also,clinical trials could be performed using the currently available nanoforms of curcumin and quercetin. 展开更多
关键词 animal models behavioral deficits curcumin inflammation nanoformulations neural deficits neurodegeneration oxidative stress quercetin
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Landslide susceptibility assessment integrating deep transfer learning and physical models in the Baihetan reservoir area,China 认领 引用 被引量：1
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作者 Ming Peng Yue Wang +5 位作者 Chenyi Ma Haojie Wang Shaoqiang Meng Zhenming Shi Weijiang Chu Jianrong Xu 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2026年第6期4382-4401,共20页
Reservoir landslides pose significant risks to hydropower projects,potentially leading to catastrophic disasters that threaten downstream lives and properties.Landslide susceptibility assessments are critical for effe... Reservoir landslides pose significant risks to hydropower projects,potentially leading to catastrophic disasters that threaten downstream lives and properties.Landslide susceptibility assessments are critical for effective regional disaster prevention and mitigation.However,the complexity,model uninterpretability,and data scarcity related to reservoir landslides,particularly when adapting models across diverse geographic regions,present significant challenges.This study proposes an interpretable Deep Transfer Learning model coupled with multi-source data and Physical methods(DTLP).The model is trained on multi-source data from the Three Gorges Reservoir Area(TGRA)and Lower Jinsha River Basin(LJRB),tested in Baihetan Reservoir Area(BHT),addressing the issues of limited data and cross-regional generalization.The physical method captures the effect of dynamic water level changes on slope stability.SHAP values are used to interpret the model,providing clear insights into its internal mechanisms.Results demonstrate that DTLP outperforms TrAdaBoost in data-scarce regions,achieving higher accuracy(AUC=0.953,Accuracy=0.941)with better feature generalization and susceptibility zone identification.Incorporating dynamic water level changes into the physical model enhances identification of high-susceptibility areas and reduces misclassifications.SHAP analysis indicates that elevation,lithology,and distance to river significantly influence the model decisions.Using TGRA as the source domain further validates the superiority of DTLP framework.However,due to the initial discrepancies between TGRA and the target domain,the transferability is constrained to some extent,resulting in models trained on LJRB data outperforming those trained on TGRA data. 展开更多
关键词 Landslide susceptibility assessment Deep transfer learning Reservoir landslides Infiniteslope model SHAP values
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Human cerebral organoids:Complex,versatile,and human-relevant models of neural development and brain diseases 认领 引用 被引量：4
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作者 Raquel Coronel Rosa González-Sastre +8 位作者 Patricia Mateos-Martínez Laura Maeso Elena Llorente-Beneyto Sabela Martín-Benito Viviana S.Costa Gagosian Leonardo Foti Ma Carmen González-Caballero Victoria López-Alonso Isabel Liste 《Neural Regeneration Research》 SCIE CAS CSCD 2026年第3期837-854,共18页
The brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cereb... The brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cerebral organoids have emerged as valuable tools offering a more complex,versatile,and human-relevant system than traditional animal models,which are often unable to replicate the intricate architecture and functionality of the human brain.Since human cerebral organoids are a state-of-the-art model for the study of neurodevelopment and different pathologies affecting the brain,this field is currently under constant development,and work in this area is abundant.In this review,we give a complete overview of human cerebral organoids technology,starting from the different types of protocols that exist to generate different human cerebral organoids.We continue with the use of brain organoids for the study of brain pathologies,highlighting neurodevelopmental,psychiatric,neurodegenerative,brain tumor,and infectious diseases.Because of the potential value of human cerebral organoids,we describe their use in transplantation,drug screening,and toxicology assays.We also discuss the technologies available to study cell diversity and physiological characteristics of organoids.Finally,we summarize the limitations that currently exist in the field,such as the development of vasculature and microglia,and highlight some of the novel approaches being pursued through bioengineering. 展开更多
关键词 assembloids bioengineering challenges disease modeling drug screening and toxicology human brain organoids human pluripotent stem cells neurodegenerative diseases neurodevelopment vascularization
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Correction models of Reynolds number effects for through-flow method in axial compressors 认领 引用 被引量：1
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作者 Xiaochen WANG Chunwei GU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第1期78-94,共17页
Aerodynamic performances of axial compressors are significantly affected by variation of Reynolds number in aero-engines.In the design and analysis of compressors,previous correction methods for cascades and stages ha... Aerodynamic performances of axial compressors are significantly affected by variation of Reynolds number in aero-engines.In the design and analysis of compressors,previous correction methods for cascades and stages have difficulties in predicting comprehensively Reynolds number effects on airfoils,matching and characteristics curves.This study proposes Re-correction models for loss,deviation angle and endwall blockage based on classical theories and cascade tests,and loss and deviation models show good agreement in test data of NACA65 and C4 cascades.Throughflow method considering Reynolds number effects is developed by integrating the correction models into a verified Streamline Curvature(SLC)tool.A three-stage axial compressor is investigated through SLC and CFD methods from design Reynolds number(Red=2106)to low Re=4104,and the numerical methods are validated with test data of characteristic curves and spanwise distributions at Red.With Re reduction,SLC method with correction models well predicts variation in overall performances compared with CFD calculations and Wassell's model.Streamwise and spanwise matching such as total pressure and loss distributions in SLC predictions are basically consistent with those in CFD results at near-stall points under design and low Reynolds numbers.SLC and CFD methods share similar detections of stall risks in the third stage(Stg3),and their analyses of diffusion processes deviate to some extent due to different predictions in separated endwall flow.The correction models can be adopted to consider Reynolds number effects in through-flow design and analysis of axial compressors. 展开更多
关键词 Axial compressor Reynolds number effects Correction model Through-flow method Aerodynamic performance
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Analysis-Oriented Stress–Strain Models for Ultra-High-Performance Concrete Confined with Fiber-Reinforced Polymer 认领 引用 被引量：1
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作者 Shishun Zhang Junjie Wang +1 位作者 Guan Lin Xuefei Nie 《Engineering》 SCIE EI CSCD 2026年第6期265-281,共17页
The use of fiber-reinforced polymer(FRP)jackets or tubes as confining devices can significantly improve the compressive performance of ultra-high-performance concrete(UHPC).For FRP-confined UHPC,an analysis-oriented s... The use of fiber-reinforced polymer(FRP)jackets or tubes as confining devices can significantly improve the compressive performance of ultra-high-performance concrete(UHPC).For FRP-confined UHPC,an analysis-oriented stress–strain model is essential for a comprehensive understanding of its compressive behavior and the development of design models.Although several analysis-oriented stress–strain models have been developed for FRP-confined normal-strength concrete(NSC),such models for FRP-confined UHPC are still lacking.In this study,an experiment is conducted to investigate the failure mechanism of UHPC confined with FRP under concentric compression,and the stress–strain behavior of the FRP-confined UHPC is analyzed using the stress–strain models of actively-confined UHPC.Results showed that the stress-path-independency assumption,which has been proven to apply to FRP-confined NSC,was inapplicable to FRP-confined UHPC.By modifying the confining pressure to consider the influence of stress-path dependency,an analysis-oriented model was proposed.The proposed model was verified using a collected test database.The results show that the proposed model accurately predicted the stress–strain behavior of FRP-confined UHPC. 展开更多
关键词 Ultra-high-performance concrete(UHPC) Fiber-reinforced polymer(FRP) Confinement mechanism Stress-path dependency Stress–strain model
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A Bayesian-based framework for quantifying model-inherent uncertainties in soil constitutive models 认领 引用
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作者 Haibin Xiong Shaoheng Dai +3 位作者 Feng Shan Xuzhen He Sheng Zhang Daichao Sheng 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2026年第6期4867-4881,共15页
Quantifying uncertainty in soil constitutive models is both challenging and essential for improving predictive reliability.While the Bayesian approach offers an effective framework for this purpose,previous studies ha... Quantifying uncertainty in soil constitutive models is both challenging and essential for improving predictive reliability.While the Bayesian approach offers an effective framework for this purpose,previous studies have primarily focused on uncertainties in input parameters of standard“ideal”constitutive models.However,models such as the Mohr-Coulomb,Cam-Clay,and Modified Cam-Clay are based on simplified assumptions that do not fully capture real soil behaviour,making it impossible for them to match real-world data perfectly.This study introduces a novel Bayesian-based framework that transforms deterministic models into probabilistic ones,allowing for the quantification of model-inherent uncertainty.A modified maximum a posteriori(MAP)estimator is employed,incorporating a penalty term into the negative log-likelihood to form a new loss function,which enhances bias estimates and model reliability.Using this method,three assumptions about the model bias term are evaluated against triaxial test data from Karlsruhe sand and White clay.The results demonstrate that non-constant assumptions about the bias term significantly enhance model performance.Among the models tested,the probabilistic Modified Cam-Clay model with a nonlinear bias assumption exhibits the best performance.Conversely,the probabilistic Mohr-Coulomb model reveals certain limitations,including overpredicted peak deviatoric stress and overfitted volumetric strain,underscoring the need for further refinements. 展开更多
关键词 Uncertainty quantification Maximum a posteriori(MAP) Probabilistic models Model bias Constitutive models
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Reply to Bullock et al.(2026)on ecosystem service models are indeed being validated 认领 引用
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作者 Paulo Pereira Miguel Inacio +1 位作者 Damia Barcelo Wenwu Zhao 《Geography and Sustainability》 CSCD 2026年第2期294-295,共2页
First and foremost,we are very happy that the topic of model vali-dation raised in Pereira et al.(2025)promoted a scientific discussion on this essential issue.Indeed,the question of model validation was raised by Och... First and foremost,we are very happy that the topic of model vali-dation raised in Pereira et al.(2025)promoted a scientific discussion on this essential issue.Indeed,the question of model validation was raised by Ochoa and Urbina-Cardona(2017)and by other scholars,such as Boerema et al.(2017). 展开更多
关键词 model validation issue model validation ecosystem service models scientific discussion
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Incorporating temperature-adapted growing periods enhances simulation of crop yield sensitivity to temperature in global gridded crop models 认领 引用
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作者 Xiaobo Wang Shaoqiang Wang +6 位作者 Christian Folberth Rastislav Skalsky Juraj Balkovic Florian Kraxner Xia Li Jinyuan Liu Bangyou Zheng 《Geography and Sustainability》 CSCD 2026年第2期205-215,共11页
Global Gridded Crop Models(GGCMs)have been widely used to simulate the impacts of global warming on crop production,but their accuracy in capturing the real-world temperature sensitivity of crop yields remains unclear... Global Gridded Crop Models(GGCMs)have been widely used to simulate the impacts of global warming on crop production,but their accuracy in capturing the real-world temperature sensitivity of crop yields remains unclear.Here,we evaluated the performance of eight GGCM emulators(incorporating versus not incorporating cultivar adaptation of crop growing periods at 0.5°×0.5°resolution)in modelling yield sensitivities to 1 K temperature increase(ST)and optimized their ensembles against statistically-inferred STfor maize,rice,and wheat using a Bayesian Model Averaging approach.Our results suggest that multi-GGCM ensembles assuming a fixed crop growing period(i.e.,a gradually temperature-adapted crop cultivar)show higher goodness-of-fit to statistically inferred STthan those assuming a temperature-sensitive growing period for the crops in major food-producing countries.When setting a temperature-adapted growing period instead of a temperature-sensitive growing period in the GGCM ensembles,the R 2 between GGCM-simulated and statistically-inferred STincreased from 0.63 to 0.81 for maize,0.28 to 0.52 for rice,and 0.40 to 0.85 for wheat,meanwhile the RMSE was reduced for all three crops across their respective top 20 producing countries.The crop models may exaggerate historical responses of crop growing periods to climate warming,resulting in an overestimation of yield STfor maize and an underestimation of yield STfor rice and wheat in major food-producing countries.The study highlights the importance of adopting dynamic phenological parameters in GGCM simulations to reflect crop cycle adaptation under global warming. 展开更多
关键词 Crop model GGCM Climate change Temperature sensitivity Growing period Model ensemble
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A Metaheuristic Football Optimization Algorithm Integrated with Large Language Models for Automated Seismic Time-Series Modeling 认领 引用
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作者 Amal H.Alharbi Marwa M.Eid +2 位作者 Nima Khodadadi Ebrahim A.Mattar Sayed Elkenawy 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第5期947-987,共41页
Seismic time series forecasting remains challenging due to the nonlinearity,non-stationarity,and noise of earthquake data,and because deep learning models are sensitive to preprocessing and hyperparameter settings.Alt... Seismic time series forecasting remains challenging due to the nonlinearity,non-stationarity,and noise of earthquake data,and because deep learning models are sensitive to preprocessing and hyperparameter settings.Although recent studies have improved neural architectures and optimization techniques,preprocessing is often treated as a fixed or manually designed stage,with limited integration into model optimization.To address this,this paper proposes an integrated,data-driven modelling framework that combines guided preprocessing with systematic hyperparameter optimization for seismic prediction,specifically forecasting earthquake magnitude from seismic catalog time-series data,with experiments conducted on Canadian seismic records.The method uses a Large Language Model to guide data preparation and feature engineering,rather than fully automate them,and applies deep learning-based forecasting with the N-HITS architecture,optimized via metaheuristic-assisted feature selection and hyperparameter tuning.The Football Optimization Algorithm(FbOA),employed as a metaheuristic optimization strategy in this study,is evaluated and compared with several well-known optimizers under identical conditions.The results show significant performance gains,with FbOA achieving superior accuracy,robustness,and convergence compared to baseline and competing methods.Notably,error metrics are reduced(MSE 3.10×10-7,RMSE 5.57×103),with high performance indicators(r=0.982,R2=0.979,NSE=0.981,WI=0.985).These results highlight the value of integrating guided preprocessing with optimization and demonstrate a scalable framework for high-precision time-series prediction in geophysical and related domains. 展开更多
关键词 Seismic time-series forecasting large language models metaheuristic algorithms football optimization algorithm earthquake modeling
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Research advances in animal models of high-altitude qi-deficiency and blood-stasis pattern 认领 引用
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作者 Zhixing Wang Xin Shen +3 位作者 Baoying Shen Lijun Huang Jie Huang Chengcai Lai 《Journal of Traditional Chinese Medical Sciences》 CAS CSCD 2026年第1期19-26,共8页
This study summarizes the theoretical basis,modeling strategies,pathological mechanisms,and therapeutic advances related to high-altitude qi-deficiency and blood-stasis pattern.Traditional concepts such as“qi drives ... This study summarizes the theoretical basis,modeling strategies,pathological mechanisms,and therapeutic advances related to high-altitude qi-deficiency and blood-stasis pattern.Traditional concepts such as“qi drives blood”and“deficiency leads to stasis”closely align with modern evidence demonstrating that hypoxia disrupts energy metabolism,impairs microcirculation,and amplifies inflammation and oxidative stress.Current animal models commonly use hypobaric hypoxia combined with fatigue loading,dietary restriction,ice-water stimulation,or adrenaline injection to mimic the combined effects of qi deficiency,blood stasis,and hypoxic injury.These composite approaches reproduce systemic abnormalities,including reduced arterial oxygen partial pressure,increased blood viscosity,impaired cardiac and pulmonary function,microcirculatory obstruction,and mitochondrial dysfunction.Enhanced inflammatory signaling,oxidative stress,and disturbances in metabolic and epigenetic networks further characterize the pattern.The findings indicate that its pathogenesis arises from multi-system,multi-target interactions rather than a single pathway.Representative herbal formulas,such as Buyang Huanwu decoction,Xuefu Zhuyu decoction,and prescriptions rich in Astragalus membranaceus(Fisch.)Bunge(A.membranaceus,Huang qi)or Salvia miltiorrhiza Bunge(S.miltiorrhiza,Dan Shen)have demonstrated the ability to improve energy metabolism,attenuate endothelial injury,enhance microcirculation,and suppress inflammation through network-level regulation.Future research should focus on standardizing exposure parameters,developing quantitative syndrome evaluation systems,and integrating multi-omics,systems biology and artificial intelligence to improve model reproducibility and mechanistic precision.These efforts may help establish objective criteria for high-altitude qi-deficiency and blood-stasis pattern and support the development of targeted therapeutic strategies. 展开更多
关键词 High-altitude qi-deficiency and blood-stasis pattern Animal model Hypobaric hypoxia Model establishment Evaluation system
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Advances and perspectives in animal models of human hepatitis A virus 认领 引用
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作者 Jian Li Pei-Yu Jiang +1 位作者 Hui Zhao Cheng-Feng Qin 《Animal Models and Experimental Medicine》 CAS CSCD 2026年第6期1180-1187,共8页
Hepatitis A virus(HAV)is an important pathogen that has continuously posed a threat to global public health for over 5000 years.The development of accessible and reliable small animal models,especially murine models,i... Hepatitis A virus(HAV)is an important pathogen that has continuously posed a threat to global public health for over 5000 years.The development of accessible and reliable small animal models,especially murine models,is essential for elucidating HAV pathogenesis and advancing preventive and therapeutic strategies.The first mouse model for HAV infection was established using human-liver chimeric mice,which supported robust viral replication and high viral loads.Later,an Ifnar1-/-mice model was established with a specific mouse-adapted strain,recapitulating key clinical features of human hepatitis A.Recently,to overcome limitations associated with the difficulty in obtaining and amplifying stocks of HAV for animal models,our laboratory established a novel hepatitis A mouse model using lipid nanoparticle-encapsulated viral genomic RNA(LNP-vRNA).This approach provides a new strategy for modeling infections of hard-to-culture RNA viruses.In this review,we systematically summarize and compare these mouse models,respectively highlighting their advantages and limitations,and offer guidance for their application in future HAV research. 展开更多
关键词 animal models hepatitis A virus LNP-vRNA based mouse model
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A comprehensive analysis and improvement of classical nonconformal contact force models for revolute joints with clearance 认领 引用
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作者 Fushou Liu Wenguang Pan Dongping Jin 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第4期56-68,共13页
Revolute joints are widely used in various engineering fields such as deployable space structures and robotics.Currently,various theoretical models have been applied to evaluate the normal contact force of the revolut... Revolute joints are widely used in various engineering fields such as deployable space structures and robotics.Currently,various theoretical models have been applied to evaluate the normal contact force of the revolute joints;however,the results obtained by these models often exhibit significant discrepancies,and there is a lack of explanation for the reasons behind these discrepancies.This study explores the underlying theories of three classical non-conformal contact force models for revolute joints,namely the ESDU-78035 model,the Radzimovsky model,and the Dubowsky-Freudenstein model.The theoretical differences among these classical models are analyzed,and their deficiencies are discovered,and then an improved non-conformal normal contact force model is presented.To validate the accuracy of the presented model,three-dimensional refined finite element models employing surface-to-surface contact elements are constructed to simulate the normal contact of the revolute joint with different clearance sizes and different contact lengths.A comprehensive comparison is carried out between the semi-contact-width,contact pressure,and load-deformation curves obtained from the theoretical models and the finite element model.The results indicate that the presented contact force model outperforms the three classical contact force models in terms of accuracy.The differences between the ideal contact model and the real revolute joint are also investigated,and a sub-model modeling method is presented for the real revolute joint based on the ideal contact force model. 展开更多
关键词 Revolute joint Clearance Normal contact force model Non-conformal contact Three-dimensional finite element model
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