In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and cha...In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.展开更多
(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbi...(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbitrary-elevation one-cylinder model.The derived results include a closed-form expression for the space-time correlation function and some quasi-closed-form ones for the space-Doppler power spectrum density,the level crossing rate,and the average fading duration,which are shown to be the generalizations of those previously obtained from the two-dimensional(2-D)one-ring model and the 3-D low-elevation one-cylinder model for terrestrial mobile-to-mobile channels.The close agreements between the theoretical results and the simulations as well as the measurements validate the utility of the derived channel statistics.Based on the derived expressions,the impacts of some parameters on the channel characteristics are investigated in an effective,efficient,and explicable way,which leads to a general guideline on the manual parameter estimation from the measurement description.展开更多
Mount Kandil is situated in the eastern sector of the EAHP(Eastern Anatolian High Plateau),to the south of the Lesser Caucasus.The mountain lies at the westernmost end of the Aras Mountains,which extends approximately...Mount Kandil is situated in the eastern sector of the EAHP(Eastern Anatolian High Plateau),to the south of the Lesser Caucasus.The mountain lies at the westernmost end of the Aras Mountains,which extends approximately 80 km along a NW-SE axis.With a summit reaching~3214 m(a.s.l.),Mount Kandil is a stratovolcano that,like many other peaks within the EAHP and the Lesser Caucasus,experienced significant environmental changes during Late Pleistocene.Among these,glacial processes stand out as the most profound,having distinctly shaped the mountains geomorphic landscape.This study presents,for the first time,a comprehensive analysis of the glacial morphology of Mount Kandil based on multiple datasets.Field-based morphological observations indicate that an area of approximately 32.62 km^(2)has been sculpted by glacial activity.Within six glaciated regions on Mount Kandil,25 cirques and 6 glacial valleys have been identified.In addition,moraines in various locations exhibit characteristic morphologies.Furthermore,valley glaciers are inferred to have descended to altitudes as low as~2000 m.The paleoequilibrium line(p ELA)was estimated to use AABR method within GIS,yielding a mean pELA of~2730 m.Ice thickness modelling indicates that the thickness of glaciers in the Kandil Mountain valleys reaches up to~350 m.Due to its orographic extension,Mount Kandil is exposed to humid northwest winds and receives substantial frontal precipitation(~686 mm annually).The compiled geomorphic,cartographic and morphometric parameters suggest that the glaciation dynamics of Mount Kandil—situated between the Southeastern Taurus and the Lesser Caucasus—closely resemble those observed in the Lesser Caucasus.This indicates that glaciation was primarily governed by northern atmospheric systems with additional influences from southerly or westerly winds.The integrated data also underscores the role of multiple atmospheric systems in controlling the glaciation regime around the Lesser Caucasus.Additionally,findings on regional pELA question the common belief that pELA increases eastward in EAHP.展开更多
The intracontinental subduction of a>200-km-long section of the Tajik-Tarim lithosphere beneath the Pamir Mountains is proposed to explain nearly 30 km of shortening in the Tajik fold-thrust belt and the Pamir upli...The intracontinental subduction of a>200-km-long section of the Tajik-Tarim lithosphere beneath the Pamir Mountains is proposed to explain nearly 30 km of shortening in the Tajik fold-thrust belt and the Pamir uplift.Seismic imaging revealed that the upper slab was scraped and that the lower slab had subducted to a depth of>150 km.These features constitute the tectonic complexity of the Pamirs,as well as the thermal subduction mechanism involved,which remains poorly understood.Hence,in this study,high-resolution three-dimensional(3D)kinematic modeling is applied to investigate the thermal structure and geometry of the subducting slab beneath the Pamirs.The modeled slab configuration reveals distinct along-strike variations,with a steeply dipping slab beneath the southern Pamirs,a more gently inclined slab beneath the northern Pamirs,and apparent upper slab termination at shallow depths beneath the Pamirs.The thermal field reveals a cold slab core after delamination,with temperatures ranging from 400℃to 800℃,enveloped by a hotter mantle reaching~1400℃.The occurrence of intermediate-depth earthquakes aligns primarily with colder slab regions,particularly near the slab tear-off below the southwestern Pamirs,indicating a strong correlation between slab temperature and seismicity.In contrast,the northern Pamirs exhibit reduced seismicity at depth,which is likely associated with thermal weakening and delamination.The central Pamirs show a significant thermal anomaly caused by a concave slab,where the coldest crust does not descend deeply,further suggesting crustal detachment or mechanical failure.The lateral asymmetry in slab temperature possibly explains the mechanism of lateral tearing and differential slab-mantle coupling.展开更多
Kinetic impact is the most practical planetary-defense technique,with momentum-transfer efficiency central to deflection design.We present a Monte Carlo photometric framework that couples ejecta sampling,dynamical evo...Kinetic impact is the most practical planetary-defense technique,with momentum-transfer efficiency central to deflection design.We present a Monte Carlo photometric framework that couples ejecta sampling,dynamical evolution,and image synthesis to compare directly with HST,LICIACube,ground-based and Lucy observations of the DART impact.Decomposing ejecta into(1)a highvelocity(~1600 m/s)plume exhibiting Na/K resonance,(2)a low-velocity(~1 m/s)conical component shaped by binary gravity and solar radiation pressure,and(3)meter-scale boulders,we quantify each component’s mass and momentum.Fitting photometric decay curves and morphological evolution yields size-velocity distributions and,via scaling laws,estimates of Dimorphos’bulk density,cratering parameters,and cohesive strength that agree with dynamical constraints.Photometric ejecta modeling therefore provides a robust route to constrain momentum enhancement and target properties,improving predictive capability for kinetic-deflection missions.展开更多
Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical si...Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%.展开更多
To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework ba...To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.展开更多
With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration wi...With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration within urban spaces and serve as testbeds for exploring smart city planning and governance models.Information models facilitate the effective integration of technology into space.Building Information Modeling(BIM)and City Information Modeling(CIM)have been widely used in urban construction.However,the existing information models have limitations in the application of the park,so it is necessary to develop an information model suitable for the park.This paper first traces the evolution of park smart transformation,reviews the global landscape of smart park development,and identifies key trends and persistent challenges.Addressing the particularities of parks,the concept of Park Information Modeling(PIM)is proposed.PIM leverages smart technologies such as artificial intelligence,digital twins,and collaborative sensing to help form a‘space-technology-system’smart structure,enabling systematic management of diverse park spaces,addressing the deficiency in park-level information models,and aiming to achieve scale articulation between BIM and CIM.Finally,through a detailed top-level design application case study of the Nanjing Smart Education Park in China,this paper illustrates the translation process of the PIM concept into practice,showcasing its potential to provide smart management tools for park managers and enhance services for park stakeholders,although further empirical validation is required.展开更多
Huperzine A(HupA) is a highly selective, reversible acetylcholinesterase(AChE) inhibitor that exhibits neuroprotective effects and is clinically used to manage benign memory decline.However, the specific relationship ...Huperzine A(HupA) is a highly selective, reversible acetylcholinesterase(AChE) inhibitor that exhibits neuroprotective effects and is clinically used to manage benign memory decline.However, the specific relationship between the pharmacokinetic(PK) profile of HupA and cerebral acetylcholine(ACh) dynamics remains poorly characterized. Here, we characterize the PK-pharmacodynamic(PD) properties of HupA in rats under both physiological and pathological conditions. Following a single intramuscular injection, HupA exhibits a short halflife but rapid brain penetration, while multiple dosing significantly enhances its brain exposure. In a middle cerebral artery occlusion(MCAO) rat model, HupA demonstrates increased brain distribution. Furthermore, HupA elevates ACh concentrations across multiple brain regions, concurrently modulating several monoamine neurotransmitters. Using a minimal physiologically based pharmacokinetic-pharmacodynamic(mPBPK-PD) modeling approach,cerebral ACh dynamics were accurately predicted based on the pharmacokinetics of HupA in systemic circulation. The developed mPBPK-PD model exhibits robust predictive performance and holds potential for guiding the optimization of clinical dosing regimens and improving the therapeutic efficacy of HupA.展开更多
Glassy polymers are widely used in biomedical applications in a solvent environment,yet their long-term performance is governed by the competing effects of physical aging and solvent-induced plasticization.Here,we dev...Glassy polymers are widely used in biomedical applications in a solvent environment,yet their long-term performance is governed by the competing effects of physical aging and solvent-induced plasticization.Here,we develop a constitutive model that explicitly couples the solvent concentration,structural relaxation,and mechanical response.This framework is built on a multiplicative decomposition of deformation and an Eyring-type flow rule,with structural evolution described by an effective temperature.A generalized shift factor is introduced to quantify how the solvent concentration and effective temperature jointly affect the relaxation time,thereby integrating physical aging and plasticization.The model is subsequently applied to methacrylate(MA)-based copolymer networks immersed in phosphate-buffered saline for up to nine months.Simulations accurately capture key experimental features,including the strong softening of highly swellable networks,the partial recovery due to aging,and the mitigating role of hydrophobic crosslinking in reducing solvent uptake.While the current single-mode description cannot reproduce the full relaxation spectrum,it establishes an efficient framework for predicting the long-term mechanical performance under coupled environmental and mechanical loading.This study provides a constitutive description of solvent-swollen glassy polymers,offering mechanistic insight into the interplay between plasticization and aging.Beyond biomedical MA networks,this framework establishes a foundation for predicting the long-term performance of polymer glasses under coupled aqueous environmental and mechanical loading.展开更多
Xylogenesis,the process through which wood cells are formed,results in the long-term storage of carbon in woody biomass,making it a key component of the global carbon cycle.Understanding how environmental drivers infl...Xylogenesis,the process through which wood cells are formed,results in the long-term storage of carbon in woody biomass,making it a key component of the global carbon cycle.Understanding how environmental drivers influence xylogenesis during the growing season is therefore of great interest.However,studying shortterm drivers of wood production using xylogenetic data is complicated by the usual sampling scheme and the influence of eccentric growth,i.e.,heterogeneous growth around the stem.In this study,we improve xylogenesis research by introducing a statistical approach that explicitly considers seasonal phenology,short-term growth rates,and growth eccentricity.To this end,we developed Bayesian models of xylogenesis and compared them with a conventional method based on the use of Gompertz functions.Our results show that eccentricity generated high temporal autocorrelation between successive samples,and that explicitly taking it into account improved both the representativeness of phenology and intra-ring variability.We observed consistent short-term patterns in the model residuals,suggesting the influence of an unaccounted-for environmental variable on cell production.The proposed models offer several advantages over traditional methods,including robust confidence intervals around predictions,consistency with phenology,and reduced sensitivity to extreme observations at the end of the growing season,often linked to eccentric growth.These models also provide a benchmark for mechanistic testing of short-term drivers of wood formation.展开更多
In deep coal mining,surrounding rock is subjected to both high in-situ stress and intense mining disturbances,leading to significant time-dependent behavior.Accurately capturing this behavior is essential for predicti...In deep coal mining,surrounding rock is subjected to both high in-situ stress and intense mining disturbances,leading to significant time-dependent behavior.Accurately capturing this behavior is essential for predicting long-term roadway stability,necessitating the development of a reliable constitutive creep model and numerical simulation approach.In this study,creep experiments were conducted on pre-damaged rock with varying initial damage levels to investigate the time-dependent mechanical properties.Based on the experimental results,an accelerated-creep criterion was proposed,and an elastic-viscoplastic creep damage model(EVPCD)was established that simultaneously considers the effects of time-dependent damage and instantaneous damage caused by stress disturbances on rock creep behavior.Subsequently,the effectiveness of the proposed creep model was verified using experimental data,and the secondary development of the EVPCD model was completed based on the FLAC3D platform.Following this,a long-term stability analysis method of deep surrounding rock that accounts for excavation-and mining-induced disturbances was proposed.Using the main roadway of Xutuan Coal Mine as a case study,numerical simulations were carried out to investigate the time-dependent deformation and failure characteristics of the surrounding rock following excavation and mining disturbance.Combined with on-site monitoring of the surrounding rock damage areas,the results indicate that the EVPCD outperforms the CVISC and Nishihara models in predicting the time-dependent behavior of deep surrounding rock.展开更多
A lupuslike condition induced by intraperitoneal administration of pristane(2,6,10,14 tetramethylpentadecane)in mice is widely used as a model of systemic lupus erythematosus(SLE).Due to their phylogenetic distance fr...A lupuslike condition induced by intraperitoneal administration of pristane(2,6,10,14 tetramethylpentadecane)in mice is widely used as a model of systemic lupus erythematosus(SLE).Due to their phylogenetic distance from humans,murine models are not always suitable tool for studying the specific activity of therapeutic agents and the pathogenesis of SLE.In order to overcome speciesspecific limitations of murine models,this approach was tested in nonhuman primates-cynomolgus monkeys(Macaca fascicularis).Two intraperitoneal injections at a dose of 3.5 mL/kg,administered at weeks 1 and 23,recapitulated SLE features,including:production of antinuclear autoantibodies(ANA),membranoproliferative glomerulonephritis with immune complex(IC)deposition in the glomeruli.However,from week 27 five of eight pristanetreated monkeys developed progressive respiratory failure.Two of these died at week 28 and the remaining were euthanized at week 32.The histology of the monkey lungs suggested exogenous lipoid pneumonia.Thus,while pristane induced serological autoimmunity and characteristic renal manifestations in Macaca fascicularis,the consequent lipoid pneumonia limited the observation period and prevented comprehensive evaluation of SLE manifestations beyond 32 weeks.展开更多
In this study,copper extraction from low-grade oxide-sulfide ores was investigated using a leaching method combined with response surface methodology(RSM)to optimize operational conditions and assess leaching kinetics...In this study,copper extraction from low-grade oxide-sulfide ores was investigated using a leaching method combined with response surface methodology(RSM)to optimize operational conditions and assess leaching kinetics.Given copper's extensive industrial applications,sustainable recovery from low-grade ores is critical.Five key parameters-acid concentration,leaching time,particle size,temperature,and solids percentage-were identified as major influences on copper recovery.The results revealed that leaching time and solids percentage,along with interactions between temperature-time and temperature-solids percentage,had the most significant effects.Optimal conditions for 80% copper recovery while minimizing iron recovery below 3% included an acid concentration of 1.21 mol L^(-1),a leaching time of 108 min,a particle size of 438μm,a temperature of 45℃,and a solids percentage of 18.2%.Leaching kinetics were analyzed using shrinking core models,with the Dickinson model best describing the process,showing an activation energy of 32.63 kJ mol^(-1),indicative of mixed diffusion and chemical reaction control.The final kinetic model effectively predicted the influence of key parameters.These findings highlight the importance of optimizing process variables and selecting suitable kinetic models to enhance extraction efficiency,reduce costs,and improve sustainability in copper recovery.展开更多
Background Multibreed genomic prediction(MBGP)is crucial for improving prediction accuracy for breeds with small populations,for which limited data are often available.Recent studies have demonstrated that partitionin...Background Multibreed genomic prediction(MBGP)is crucial for improving prediction accuracy for breeds with small populations,for which limited data are often available.Recent studies have demonstrated that partitioning the genome into nonoverlapping blocks to model heterogeneous genetic(co)variance in multitrait models can achieve higher joint prediction accuracy.However,the block partitioning method,a key factor influencing model performance,has not been extensively explored.Results We introduce mbBayesABLD,a novel Bayesian MBGP model that partitions each chromosome into nonoverlapping blocks on the basis of linkage disequilibrium(LD)patterns.In this model,marker effects within each block are assumed to follow normal distributions with block-specific parameters.We employ simulated data as well as empirical datasets from pigs and beans to assess genomic prediction accuracy across different models using cross-validation.The results demonstrate that mbBayesABLD significantly outperforms conventional MBGP models,such as GBLUP and BayesR.For the meat marbling score trait in pigs,compared with GBLUP,which does not account for heterogeneous genetic(co)variance,mbBayesABLD improves the prediction accuracy for the small-population breed Landrace by 15.6%.Furthermore,our findings indicate that a moderate level of similarity in LD patterns between breeds(with an average correlation of 0.6)is sufficient to improve the prediction accuracy of the target breed.Conclusions This study presents a novel LD block-based approach for multibreed genomic prediction.Our work provides a practical tool for livestock breeding programs and offers new insights into leveraging genetic diversity across breeds for improved genomic prediction.展开更多
As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods ge...As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.展开更多
Proton Exchange Membrane Water Electrolyzers(PEMWE)are efficient and sustainable hydrogen production devices.This article analyzes their static and dynamic electrical models integrated with degradation mechanisms.Stat...Proton Exchange Membrane Water Electrolyzers(PEMWE)are efficient and sustainable hydrogen production devices.This article analyzes their static and dynamic electrical models integrated with degradation mechanisms.Static models reveal steady-state behavior,while dynamic models capture transient responses to input variations.The developed modeling approach combines the activation and diffusion phenomena,resulting in a novel PEMWE model that closely reflects real-world conditions and enables fast simulations.The electrical model is integrated with the aging model through two key ratios,surface degradation ratio and membrane degradation ratio,which characterize degradation mechanisms affecting electrode and membrane performance.The linear model using second-order Taylor approximation enables the development of a diagnosis approach that can contribute to estimating the remaining useful life of PEMWEs.By associating aging models with electrical models through the proposed ratios,a deeper understanding is achieved regarding how degra-dation phenomena evolve and influence electrolyzer efficiency and durability.The integrated framework enables predictive maintenance strategies,making it valuable for industrial hydrogen production applications.展开更多
Hydrocarbon production from shale has attracted much attention in the recent years. When applied to this prolific and hydrocarbon rich resource plays, our understanding of the complexities of the flow mechanism（sorpt...Hydrocarbon production from shale has attracted much attention in the recent years. When applied to this prolific and hydrocarbon rich resource plays, our understanding of the complexities of the flow mechanism（sorption process and flow behavior in complex fracture systems- induced or natural） leaves much to be desired. In this paper, we present and discuss a novel approach to modeling, history matching of hydrocarbon production from a Marcellus shale asset in southwestern Pennsylvania using advanced data mining, pattern recognition and machine learning technologies. In this new approach instead of imposing our understanding of the flow mechanism, the impact of multi-stage hydraulic fractures, and the production process on the reservoir model, we allow the production history, well log, completion and hydraulic fracturing data to guide our model and determine its behavior. The uniqueness of this technology is that it incorporates the so-called ＂hard data＂ directly into the reservoir model, so that the model can be used to optimize the hydraulic fracture process. The ＂hard data＂ refers to field measurements during the hydraulic fracturing process such as fluid and proppant type and amount, injection pressure and rate as well as proppant concentration. This novel approach contrasts with the current industry focus on the use of ＂soft data＂（non-measured, interpretive data such as frac length, width,height and conductivity） in the reservoir models. The study focuses on a Marcellus shale asset that includes 135 wells with multiple pads, different landing targets, well length and reservoir properties. The full field history matching process was successfully completed using this data driven approach thus capturing the production behavior with acceptable accuracy for individual wells and for the entire asset.展开更多
Earth’s internal core and crustal magnetic fields,as measured by geomagnetic satellites like MSS-1(Macao Science Satellite-1)and Swarm,are vital for understanding core dynamics and tectonic evolution.To model these i...Earth’s internal core and crustal magnetic fields,as measured by geomagnetic satellites like MSS-1(Macao Science Satellite-1)and Swarm,are vital for understanding core dynamics and tectonic evolution.To model these internal magnetic fields accurately,data selection based on specific criteria is often employed to minimize the influence of rapidly changing current systems in the ionosphere and magnetosphere.However,the quantitative impact of various data selection criteria on internal geomagnetic field modeling is not well understood.This study aims to address this issue and provide a reference for constructing and applying geomagnetic field models.First,we collect the latest MSS-1 and Swarm satellite magnetic data and summarize widely used data selection criteria in geomagnetic field modeling.Second,we briefly describe the method to co-estimate the core,crustal,and large-scale magnetospheric fields using satellite magnetic data.Finally,we conduct a series of field modeling experiments with different data selection criteria to quantitatively estimate their influence.Our numerical experiments confirm that without selecting data from dark regions and geomagnetically quiet times,the resulting internal field differences at the Earth’s surface can range from tens to hundreds of nanotesla(nT).Additionally,we find that the uncertainties introduced into field models by different data selection criteria are significantly larger than the measurement accuracy of modern geomagnetic satellites.These uncertainties should be considered when utilizing constructed magnetic field models for scientific research and applications.展开更多
Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a vi...Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a viewpoint in DoDAF2.0,the operational viewpoint(OV)describes operational activities,nodes,and resource flows.The OV models are important for SoS architecture development.However,as the SoS complexity increases,constructing OV models with traditional methods exposes shortcomings,such as inefficient data collection and low modeling standards.Therefore,we propose an intelligent modeling method for five OV models,including operational resource flow OV-2,organizational relationships OV-4,operational activity hierarchy OV-5a,operational activities model OV-5b,and operational activity sequences OV-6c.The main idea of the method is to extract OV architecture data from text and generate interoperable OV models.First,we construct the OV meta model based on the DoDAF2.0 meta model(DM2).Second,OV architecture named entities is recognized from text based on the bidirectional long short-term memory and conditional random field(BiLSTM-CRF)model.And OV architecture relationships are collected with relationship extraction rules.Finally,we define the generation rules for OV models and develop an OV modeling tool.We use unmanned surface vehicles(USV)swarm target defense SoS architecture as a case to verify the feasibility and effectiveness of the intelligent modeling method.展开更多
基金the World Climate Research Programme(WCRP),Climate Variability and Predictability(CLIVAR),and Global Energy and Water Exchanges(GEWEX)for facilitating the coordination of African monsoon researchsupport from the Center for Earth System Modeling,Analysis,and Data at the Pennsylvania State Universitythe support of the Office of Science of the U.S.Department of Energy Biological and Environmental Research as part of the Regional&Global Model Analysis(RGMA)program area。
文摘In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.
基金supported in part by the National Key Research and Development Program of China(2021YFB2900501)in part by the Shaanxi Science and Technology Innovation Team(2023-CX-TD-03)+3 种基金in part by the Science and Technology Program of Shaanxi Province(2021GXLH-Z-038)in part by the Natural Science Foundation of Hunan Province(2023JJ40607 and 2023JJ50045)in part by the Scientific Research Foundation of Hunan Provincial Education Department(23B0713 and 24B0603)in part by the National Natural Science Foundation of China(62401371,62101275,and 62372070).
文摘(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbitrary-elevation one-cylinder model.The derived results include a closed-form expression for the space-time correlation function and some quasi-closed-form ones for the space-Doppler power spectrum density,the level crossing rate,and the average fading duration,which are shown to be the generalizations of those previously obtained from the two-dimensional(2-D)one-ring model and the 3-D low-elevation one-cylinder model for terrestrial mobile-to-mobile channels.The close agreements between the theoretical results and the simulations as well as the measurements validate the utility of the derived channel statistics.Based on the derived expressions,the impacts of some parameters on the channel characteristics are investigated in an effective,efficient,and explicable way,which leads to a general guideline on the manual parameter estimation from the measurement description.
基金supported by Van Yüzüncü Yıl University,Scientific Research Projects Coordination Unit(Project No:SDK-2025-11935)Van Yüzüncü Yıl University,Scientific Research Projects Coordination Unit for supporting the study。
文摘Mount Kandil is situated in the eastern sector of the EAHP(Eastern Anatolian High Plateau),to the south of the Lesser Caucasus.The mountain lies at the westernmost end of the Aras Mountains,which extends approximately 80 km along a NW-SE axis.With a summit reaching~3214 m(a.s.l.),Mount Kandil is a stratovolcano that,like many other peaks within the EAHP and the Lesser Caucasus,experienced significant environmental changes during Late Pleistocene.Among these,glacial processes stand out as the most profound,having distinctly shaped the mountains geomorphic landscape.This study presents,for the first time,a comprehensive analysis of the glacial morphology of Mount Kandil based on multiple datasets.Field-based morphological observations indicate that an area of approximately 32.62 km^(2)has been sculpted by glacial activity.Within six glaciated regions on Mount Kandil,25 cirques and 6 glacial valleys have been identified.In addition,moraines in various locations exhibit characteristic morphologies.Furthermore,valley glaciers are inferred to have descended to altitudes as low as~2000 m.The paleoequilibrium line(p ELA)was estimated to use AABR method within GIS,yielding a mean pELA of~2730 m.Ice thickness modelling indicates that the thickness of glaciers in the Kandil Mountain valleys reaches up to~350 m.Due to its orographic extension,Mount Kandil is exposed to humid northwest winds and receives substantial frontal precipitation(~686 mm annually).The compiled geomorphic,cartographic and morphometric parameters suggest that the glaciation dynamics of Mount Kandil—situated between the Southeastern Taurus and the Lesser Caucasus—closely resemble those observed in the Lesser Caucasus.This indicates that glaciation was primarily governed by northern atmospheric systems with additional influences from southerly or westerly winds.The integrated data also underscores the role of multiple atmospheric systems in controlling the glaciation regime around the Lesser Caucasus.Additionally,findings on regional pELA question the common belief that pELA increases eastward in EAHP.
基金the Chinese Academy of Sciences Pioneer Hundred Talents Program and the Second Tibetan Plateau Scientific Expedition and Research Program(Grant No.2019QZKK0708)supported by a MEXT(Ministry of Education,Culture,Sports,Science and Technology)KAKENHI(Grants-in-Aid for Scientific Research)grant(Grant No.21H05203)Kobe University Strategic International Collaborative Research Grant(Type B Fostering Joint Research).
文摘The intracontinental subduction of a>200-km-long section of the Tajik-Tarim lithosphere beneath the Pamir Mountains is proposed to explain nearly 30 km of shortening in the Tajik fold-thrust belt and the Pamir uplift.Seismic imaging revealed that the upper slab was scraped and that the lower slab had subducted to a depth of>150 km.These features constitute the tectonic complexity of the Pamirs,as well as the thermal subduction mechanism involved,which remains poorly understood.Hence,in this study,high-resolution three-dimensional(3D)kinematic modeling is applied to investigate the thermal structure and geometry of the subducting slab beneath the Pamirs.The modeled slab configuration reveals distinct along-strike variations,with a steeply dipping slab beneath the southern Pamirs,a more gently inclined slab beneath the northern Pamirs,and apparent upper slab termination at shallow depths beneath the Pamirs.The thermal field reveals a cold slab core after delamination,with temperatures ranging from 400℃to 800℃,enveloped by a hotter mantle reaching~1400℃.The occurrence of intermediate-depth earthquakes aligns primarily with colder slab regions,particularly near the slab tear-off below the southwestern Pamirs,indicating a strong correlation between slab temperature and seismicity.In contrast,the northern Pamirs exhibit reduced seismicity at depth,which is likely associated with thermal weakening and delamination.The central Pamirs show a significant thermal anomaly caused by a concave slab,where the coldest crust does not descend deeply,further suggesting crustal detachment or mechanical failure.The lateral asymmetry in slab temperature possibly explains the mechanism of lateral tearing and differential slab-mantle coupling.
基金supported by the National Natural Science Foundation of China(Grant No.12272018)the National Key Basic Research Project(2022JCJQZD20600).
文摘Kinetic impact is the most practical planetary-defense technique,with momentum-transfer efficiency central to deflection design.We present a Monte Carlo photometric framework that couples ejecta sampling,dynamical evolution,and image synthesis to compare directly with HST,LICIACube,ground-based and Lucy observations of the DART impact.Decomposing ejecta into(1)a highvelocity(~1600 m/s)plume exhibiting Na/K resonance,(2)a low-velocity(~1 m/s)conical component shaped by binary gravity and solar radiation pressure,and(3)meter-scale boulders,we quantify each component’s mass and momentum.Fitting photometric decay curves and morphological evolution yields size-velocity distributions and,via scaling laws,estimates of Dimorphos’bulk density,cratering parameters,and cohesive strength that agree with dynamical constraints.Photometric ejecta modeling therefore provides a robust route to constrain momentum enhancement and target properties,improving predictive capability for kinetic-deflection missions.
基金financially supported by the National Key Research and Development Program of China (2022YFB3706802)。
文摘Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%.
基金supported by the confidential research grant No.a8317。
文摘To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.
基金Under the auspices of National Natural Science Foundation of China(No.42330510)。
文摘With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration within urban spaces and serve as testbeds for exploring smart city planning and governance models.Information models facilitate the effective integration of technology into space.Building Information Modeling(BIM)and City Information Modeling(CIM)have been widely used in urban construction.However,the existing information models have limitations in the application of the park,so it is necessary to develop an information model suitable for the park.This paper first traces the evolution of park smart transformation,reviews the global landscape of smart park development,and identifies key trends and persistent challenges.Addressing the particularities of parks,the concept of Park Information Modeling(PIM)is proposed.PIM leverages smart technologies such as artificial intelligence,digital twins,and collaborative sensing to help form a‘space-technology-system’smart structure,enabling systematic management of diverse park spaces,addressing the deficiency in park-level information models,and aiming to achieve scale articulation between BIM and CIM.Finally,through a detailed top-level design application case study of the Nanjing Smart Education Park in China,this paper illustrates the translation process of the PIM concept into practice,showcasing its potential to provide smart management tools for park managers and enhance services for park stakeholders,although further empirical validation is required.
基金supported by the National Key Research and Development Program of China (No. 2024YFA1308200)the National Natural Science Foundation of China (Nos. 82274009 and81973556)。
文摘Huperzine A(HupA) is a highly selective, reversible acetylcholinesterase(AChE) inhibitor that exhibits neuroprotective effects and is clinically used to manage benign memory decline.However, the specific relationship between the pharmacokinetic(PK) profile of HupA and cerebral acetylcholine(ACh) dynamics remains poorly characterized. Here, we characterize the PK-pharmacodynamic(PD) properties of HupA in rats under both physiological and pathological conditions. Following a single intramuscular injection, HupA exhibits a short halflife but rapid brain penetration, while multiple dosing significantly enhances its brain exposure. In a middle cerebral artery occlusion(MCAO) rat model, HupA demonstrates increased brain distribution. Furthermore, HupA elevates ACh concentrations across multiple brain regions, concurrently modulating several monoamine neurotransmitters. Using a minimal physiologically based pharmacokinetic-pharmacodynamic(mPBPK-PD) modeling approach,cerebral ACh dynamics were accurately predicted based on the pharmacokinetics of HupA in systemic circulation. The developed mPBPK-PD model exhibits robust predictive performance and holds potential for guiding the optimization of clinical dosing regimens and improving the therapeutic efficacy of HupA.
基金the funding support from the Smart Medicine and Engineering Interdisciplinary Innovation Project of Ningbo University(No.ZHYG003)。
文摘Glassy polymers are widely used in biomedical applications in a solvent environment,yet their long-term performance is governed by the competing effects of physical aging and solvent-induced plasticization.Here,we develop a constitutive model that explicitly couples the solvent concentration,structural relaxation,and mechanical response.This framework is built on a multiplicative decomposition of deformation and an Eyring-type flow rule,with structural evolution described by an effective temperature.A generalized shift factor is introduced to quantify how the solvent concentration and effective temperature jointly affect the relaxation time,thereby integrating physical aging and plasticization.The model is subsequently applied to methacrylate(MA)-based copolymer networks immersed in phosphate-buffered saline for up to nine months.Simulations accurately capture key experimental features,including the strong softening of highly swellable networks,the partial recovery due to aging,and the mitigating role of hydrophobic crosslinking in reducing solvent uptake.While the current single-mode description cannot reproduce the full relaxation spectrum,it establishes an efficient framework for predicting the long-term mechanical performance under coupled environmental and mechanical loading.This study provides a constitutive description of solvent-swollen glassy polymers,offering mechanistic insight into the interplay between plasticization and aging.Beyond biomedical MA networks,this framework establishes a foundation for predicting the long-term performance of polymer glasses under coupled aqueous environmental and mechanical loading.
基金supported by the Discovery Grants program of the Natural Sciences and Engineering Research Council of Canada(No.RGPIN-2021-03553)the Canadian Research Chair in dendroecology and dendroclimatology(CRC-2021-00368)+3 种基金the Ministère des Ressources Naturelles et des Forèts(MRNF,Contract no.142332177-D)the Natural Sciences and Engineering Research Council of Canada(Alliance Grant No.ALLRP 557148-20,obtained in partnership with the MRNF and Resolute Forest Products)the Fonds de recherche du Qu ebec–Nature et technologies(Partnership Research Program on the Contribution of the Forestry Sector to Climate Change MitigationGrant No.2022-0FC-309064)。
文摘Xylogenesis,the process through which wood cells are formed,results in the long-term storage of carbon in woody biomass,making it a key component of the global carbon cycle.Understanding how environmental drivers influence xylogenesis during the growing season is therefore of great interest.However,studying shortterm drivers of wood production using xylogenetic data is complicated by the usual sampling scheme and the influence of eccentric growth,i.e.,heterogeneous growth around the stem.In this study,we improve xylogenesis research by introducing a statistical approach that explicitly considers seasonal phenology,short-term growth rates,and growth eccentricity.To this end,we developed Bayesian models of xylogenesis and compared them with a conventional method based on the use of Gompertz functions.Our results show that eccentricity generated high temporal autocorrelation between successive samples,and that explicitly taking it into account improved both the representativeness of phenology and intra-ring variability.We observed consistent short-term patterns in the model residuals,suggesting the influence of an unaccounted-for environmental variable on cell production.The proposed models offer several advantages over traditional methods,including robust confidence intervals around predictions,consistency with phenology,and reduced sensitivity to extreme observations at the end of the growing season,often linked to eccentric growth.These models also provide a benchmark for mechanistic testing of short-term drivers of wood formation.
基金funded by the National Natural Science Foundation of China(Nos.52004098,U24B2041,and 52274079)the Key Research and Development Program of Henan Province(No.251111320400)+1 种基金the Key Research Project Plan for Higher Education Institutions in Henan Province(Nos.24A570006 and 25A570002)the Scientific and Technological Research Project in Henan Province(No.242102320061).
文摘In deep coal mining,surrounding rock is subjected to both high in-situ stress and intense mining disturbances,leading to significant time-dependent behavior.Accurately capturing this behavior is essential for predicting long-term roadway stability,necessitating the development of a reliable constitutive creep model and numerical simulation approach.In this study,creep experiments were conducted on pre-damaged rock with varying initial damage levels to investigate the time-dependent mechanical properties.Based on the experimental results,an accelerated-creep criterion was proposed,and an elastic-viscoplastic creep damage model(EVPCD)was established that simultaneously considers the effects of time-dependent damage and instantaneous damage caused by stress disturbances on rock creep behavior.Subsequently,the effectiveness of the proposed creep model was verified using experimental data,and the secondary development of the EVPCD model was completed based on the FLAC3D platform.Following this,a long-term stability analysis method of deep surrounding rock that accounts for excavation-and mining-induced disturbances was proposed.Using the main roadway of Xutuan Coal Mine as a case study,numerical simulations were carried out to investigate the time-dependent deformation and failure characteristics of the surrounding rock following excavation and mining disturbance.Combined with on-site monitoring of the surrounding rock damage areas,the results indicate that the EVPCD outperforms the CVISC and Nishihara models in predicting the time-dependent behavior of deep surrounding rock.
文摘A lupuslike condition induced by intraperitoneal administration of pristane(2,6,10,14 tetramethylpentadecane)in mice is widely used as a model of systemic lupus erythematosus(SLE).Due to their phylogenetic distance from humans,murine models are not always suitable tool for studying the specific activity of therapeutic agents and the pathogenesis of SLE.In order to overcome speciesspecific limitations of murine models,this approach was tested in nonhuman primates-cynomolgus monkeys(Macaca fascicularis).Two intraperitoneal injections at a dose of 3.5 mL/kg,administered at weeks 1 and 23,recapitulated SLE features,including:production of antinuclear autoantibodies(ANA),membranoproliferative glomerulonephritis with immune complex(IC)deposition in the glomeruli.However,from week 27 five of eight pristanetreated monkeys developed progressive respiratory failure.Two of these died at week 28 and the remaining were euthanized at week 32.The histology of the monkey lungs suggested exogenous lipoid pneumonia.Thus,while pristane induced serological autoimmunity and characteristic renal manifestations in Macaca fascicularis,the consequent lipoid pneumonia limited the observation period and prevented comprehensive evaluation of SLE manifestations beyond 32 weeks.
基金Open Access funding enabled and organized by Projekt DEAL.
文摘In this study,copper extraction from low-grade oxide-sulfide ores was investigated using a leaching method combined with response surface methodology(RSM)to optimize operational conditions and assess leaching kinetics.Given copper's extensive industrial applications,sustainable recovery from low-grade ores is critical.Five key parameters-acid concentration,leaching time,particle size,temperature,and solids percentage-were identified as major influences on copper recovery.The results revealed that leaching time and solids percentage,along with interactions between temperature-time and temperature-solids percentage,had the most significant effects.Optimal conditions for 80% copper recovery while minimizing iron recovery below 3% included an acid concentration of 1.21 mol L^(-1),a leaching time of 108 min,a particle size of 438μm,a temperature of 45℃,and a solids percentage of 18.2%.Leaching kinetics were analyzed using shrinking core models,with the Dickinson model best describing the process,showing an activation energy of 32.63 kJ mol^(-1),indicative of mixed diffusion and chemical reaction control.The final kinetic model effectively predicted the influence of key parameters.These findings highlight the importance of optimizing process variables and selecting suitable kinetic models to enhance extraction efficiency,reduce costs,and improve sustainability in copper recovery.
基金supported by the Biological Breeding-Major Projects in National Science and Technology(No.2023ZD0404405)the Earmarked Fund for China Agriculture Research System(No.CARS-pig-35)+2 种基金the National Natural Science Foundation of China(No.3227284,32302708)the 2115 Talent Development Program of China Agricultural University,the Chinese Universities Scientific Fund(No.2023TC196)the Seed Industry Revitalization Action Project of Guangdong Province(No.2024-XPY-06-001)。
文摘Background Multibreed genomic prediction(MBGP)is crucial for improving prediction accuracy for breeds with small populations,for which limited data are often available.Recent studies have demonstrated that partitioning the genome into nonoverlapping blocks to model heterogeneous genetic(co)variance in multitrait models can achieve higher joint prediction accuracy.However,the block partitioning method,a key factor influencing model performance,has not been extensively explored.Results We introduce mbBayesABLD,a novel Bayesian MBGP model that partitions each chromosome into nonoverlapping blocks on the basis of linkage disequilibrium(LD)patterns.In this model,marker effects within each block are assumed to follow normal distributions with block-specific parameters.We employ simulated data as well as empirical datasets from pigs and beans to assess genomic prediction accuracy across different models using cross-validation.The results demonstrate that mbBayesABLD significantly outperforms conventional MBGP models,such as GBLUP and BayesR.For the meat marbling score trait in pigs,compared with GBLUP,which does not account for heterogeneous genetic(co)variance,mbBayesABLD improves the prediction accuracy for the small-population breed Landrace by 15.6%.Furthermore,our findings indicate that a moderate level of similarity in LD patterns between breeds(with an average correlation of 0.6)is sufficient to improve the prediction accuracy of the target breed.Conclusions This study presents a novel LD block-based approach for multibreed genomic prediction.Our work provides a practical tool for livestock breeding programs and offers new insights into leveraging genetic diversity across breeds for improved genomic prediction.
基金National Natural Science Foundation of China(Nos.42301473,42271424,42171397)Chinese Postdoctoral Innovation Talents Support Program(No.BX20230299)+2 种基金China Postdoctoral Science Foundation(No.2023M742884)Natural Science Foundation of Sichuan Province(Nos.24NSFSC2264,2025ZNSFSC0322)Key Research and Development Project of Sichuan Province(No.24ZDYF0633).
文摘As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.
文摘Proton Exchange Membrane Water Electrolyzers(PEMWE)are efficient and sustainable hydrogen production devices.This article analyzes their static and dynamic electrical models integrated with degradation mechanisms.Static models reveal steady-state behavior,while dynamic models capture transient responses to input variations.The developed modeling approach combines the activation and diffusion phenomena,resulting in a novel PEMWE model that closely reflects real-world conditions and enables fast simulations.The electrical model is integrated with the aging model through two key ratios,surface degradation ratio and membrane degradation ratio,which characterize degradation mechanisms affecting electrode and membrane performance.The linear model using second-order Taylor approximation enables the development of a diagnosis approach that can contribute to estimating the remaining useful life of PEMWEs.By associating aging models with electrical models through the proposed ratios,a deeper understanding is achieved regarding how degra-dation phenomena evolve and influence electrolyzer efficiency and durability.The integrated framework enables predictive maintenance strategies,making it valuable for industrial hydrogen production applications.
基金RPSEA and U.S.Department of Energy for partially funding this study
文摘Hydrocarbon production from shale has attracted much attention in the recent years. When applied to this prolific and hydrocarbon rich resource plays, our understanding of the complexities of the flow mechanism（sorption process and flow behavior in complex fracture systems- induced or natural） leaves much to be desired. In this paper, we present and discuss a novel approach to modeling, history matching of hydrocarbon production from a Marcellus shale asset in southwestern Pennsylvania using advanced data mining, pattern recognition and machine learning technologies. In this new approach instead of imposing our understanding of the flow mechanism, the impact of multi-stage hydraulic fractures, and the production process on the reservoir model, we allow the production history, well log, completion and hydraulic fracturing data to guide our model and determine its behavior. The uniqueness of this technology is that it incorporates the so-called ＂hard data＂ directly into the reservoir model, so that the model can be used to optimize the hydraulic fracture process. The ＂hard data＂ refers to field measurements during the hydraulic fracturing process such as fluid and proppant type and amount, injection pressure and rate as well as proppant concentration. This novel approach contrasts with the current industry focus on the use of ＂soft data＂（non-measured, interpretive data such as frac length, width,height and conductivity） in the reservoir models. The study focuses on a Marcellus shale asset that includes 135 wells with multiple pads, different landing targets, well length and reservoir properties. The full field history matching process was successfully completed using this data driven approach thus capturing the production behavior with acceptable accuracy for individual wells and for the entire asset.
基金supported by the National Natural Science Foundation of China(42250101)the Macao Foundation。
文摘Earth’s internal core and crustal magnetic fields,as measured by geomagnetic satellites like MSS-1(Macao Science Satellite-1)and Swarm,are vital for understanding core dynamics and tectonic evolution.To model these internal magnetic fields accurately,data selection based on specific criteria is often employed to minimize the influence of rapidly changing current systems in the ionosphere and magnetosphere.However,the quantitative impact of various data selection criteria on internal geomagnetic field modeling is not well understood.This study aims to address this issue and provide a reference for constructing and applying geomagnetic field models.First,we collect the latest MSS-1 and Swarm satellite magnetic data and summarize widely used data selection criteria in geomagnetic field modeling.Second,we briefly describe the method to co-estimate the core,crustal,and large-scale magnetospheric fields using satellite magnetic data.Finally,we conduct a series of field modeling experiments with different data selection criteria to quantitatively estimate their influence.Our numerical experiments confirm that without selecting data from dark regions and geomagnetically quiet times,the resulting internal field differences at the Earth’s surface can range from tens to hundreds of nanotesla(nT).Additionally,we find that the uncertainties introduced into field models by different data selection criteria are significantly larger than the measurement accuracy of modern geomagnetic satellites.These uncertainties should be considered when utilizing constructed magnetic field models for scientific research and applications.
基金National Natural Science Foundation of China(71690233,71971213,71901214)。
文摘Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a viewpoint in DoDAF2.0,the operational viewpoint(OV)describes operational activities,nodes,and resource flows.The OV models are important for SoS architecture development.However,as the SoS complexity increases,constructing OV models with traditional methods exposes shortcomings,such as inefficient data collection and low modeling standards.Therefore,we propose an intelligent modeling method for five OV models,including operational resource flow OV-2,organizational relationships OV-4,operational activity hierarchy OV-5a,operational activities model OV-5b,and operational activity sequences OV-6c.The main idea of the method is to extract OV architecture data from text and generate interoperable OV models.First,we construct the OV meta model based on the DoDAF2.0 meta model(DM2).Second,OV architecture named entities is recognized from text based on the bidirectional long short-term memory and conditional random field(BiLSTM-CRF)model.And OV architecture relationships are collected with relationship extraction rules.Finally,we define the generation rules for OV models and develop an OV modeling tool.We use unmanned surface vehicles(USV)swarm target defense SoS architecture as a case to verify the feasibility and effectiveness of the intelligent modeling method.
