This article presents a parameterized configuration modeling approach to develop a 6 degrees of freedom （DOF） rigid-body model for air-breathing hypersonic vehicle （AHV）. The modeling process involves the paramete...This article presents a parameterized configuration modeling approach to develop a 6 degrees of freedom （DOF） rigid-body model for air-breathing hypersonic vehicle （AHV）. The modeling process involves the parameterized configuration design, inviscous hypersonic aerodynamic force calculation and scramjet engine modeling. The parameters are designed for airframe-propulsion integration configuration, the aerodynamic force calculation is based on engineering experimental methods, and the engine model is acquired from gas dynamics and quasi-one dimensional combustor calculations. Multivariate fitting is used to obtain analytical equations for aerodynamic force and thrust. Furthermore, the fitting accuracy is evaluated by relative error （RE）. Trim results show that the model can be applied to the investigation of control method for AHV during the cruise phase. The modeling process integrates several disciplines such as configuration design, aerodynamic calculation, scramjet modeling and control method. Therefore the modeling method makes it possible to conduct AHV aerodynamics/propulsion/control integration design.展开更多
Since the subsystems of aerodynamics,propulsion,structure and so on in hypersonic vehicles involve characteristics of nonlinearity,strong coupling and uncertainty,and typical hypersonic vehicles adopt slender-body and...Since the subsystems of aerodynamics,propulsion,structure and so on in hypersonic vehicles involve characteristics of nonlinearity,strong coupling and uncertainty,and typical hypersonic vehicles adopt slender-body and wave-rider layout with widely-used lightweight materials,the accuracy of the modeling with a conventional rigid-body assumption is challenged.Therefore,a nonlinear mathematical longitudinal model of a hypersonic vehicle is established with its geometry provided to estimate aerodynamic force and thrust using hypersonic aerodynamics and quasi-one-dimensional flow with heat added and capture vehicle aeroelasticity using a single free-free Bernoulli-Euler beam model.Then the static and dynamic properties of the rigid and rigid-aeroelasticity coupling model are compared via theoretical analysis and numerical simulation under the given flight condition.Finally,a LQR controller for rigid model is designed and the comparable results are obtained to explain the aerolasticity influence on the control effect.The simulation results show that the aeroelasticity mode of slender-body hypersonic vehicles affects short period mode significantly and it cannot be simply neglected.展开更多
Delivering energy flexibility at the district scale entails coordinating control actions across many buildings to shape aggregate demand;this coordination depends on training and deploying control policies and optimiz...Delivering energy flexibility at the district scale entails coordinating control actions across many buildings to shape aggregate demand;this coordination depends on training and deploying control policies and optimization routines,which in turn require predictive models that can be queried efficiently over large building clusters.However,conventional physics-based simulators are computationally prohibitive for large-scale control training,and simple data-driven surrogates often lack the generalization needed for heterogeneous clusters.This paper introduces ScaleONet,a deep operator network framework designed for scalable,control-oriented modeling of building-cluster thermal dynamics.ScaleONet leverages the DeepONet paradigm to decouple and share learning across buildings:an LSTM-based branch network encodes outdoor climate and individual HVAC control signals,while a multilayer perceptron(MLP)-based trunk network embeds prediction timestamps,enabling fast predictions for growing clusters with negligible extra cost for each additional building or timestep.To the authors’knowledge,this is the first operator-learning method tailored to indoor air temperature forecasting in heterogeneous building clusters.Validation on thirty Belgian buildings(GenkNet)simulated in Dymola shows that,although a non-operator-learning LSTM baseline slightly outperforms ScaleONet for single-building cases,its error grows monotonically with cluster size.In contrast,ScaleONet’s median per-building-per-day RMSE decreases from 0.59°C at three buildings to 0.53°C at ten and 0.47°C at thirty,compared to 0.95°C for the LSTM at thirty buildings-a 51%reduction in prediction error.Error analysis across envelope heat-loss coefficients(UAbuilding)further reveals that while the LSTM’s RMSE increases for high-𝑈𝐴structures,ScaleONet maintains uniformly low error.With millisecond-scale inference(approximately 4 ms per sample for thirty buildings),ScaleONet is well suited for large-scale reinforcement learning,receding-horizon optimization,and real-time model predictive control.展开更多
This paper proposes a robust control-oriented identification method for errors-in-variables(EIV)systems in output feedbacks using frequency-response(FR)experimental data.An important relation between such a closed-loo...This paper proposes a robust control-oriented identification method for errors-in-variables(EIV)systems in output feedbacks using frequency-response(FR)experimental data.An important relation between such a closed-loop EIV system and its coprime factor(CF)uncertainty description is first derived,based on which the FR measurements suitable for plant CF identification are able to be generated.Different factorizations of a given controller in the closed-loop system can be made best use to adjust right coprime factors(RCFs)of the plant so as to realize an improvement on the signal-to-noise ratio of identification experimental data.Subsequently,a nominal RCF model is estimated by linear matrix inequalities from the applicable FR measurements and its associated worst-case errors are quantified from a priori and a posteriori information on the underlying system.A resulting RCF perturbation model set can then be described by the nominal RCF model and its worst-case error bounds.Such a model set capable of being stabilized by the given controller is ready for its robust stabilizing controller redesign and robust performance analysis.Finally,a numerical simulation is given to show the efficacy of the proposed identification method.展开更多
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
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
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
Activation pruning reduces neural network complexity by eliminating low-importance neuron activations,yet identifying the critical pruning threshold—beyond which accuracy rapidly deteriorates—remains computationally...Activation pruning reduces neural network complexity by eliminating low-importance neuron activations,yet identifying the critical pruning threshold—beyond which accuracy rapidly deteriorates—remains computationally expensive and typically requires exhaustive search.We introduce a thermodynamics-inspired framework that treats activation distributions as energy-filtered physical systems and employs the free energy of activations as a principled evaluation metric.Phase-transition-like phenomena in the free-energy profile—such as extrema,inflection points,and curvature changes—yield reliable estimates of the critical pruning threshold,providing a theoretically grounded means of predicting sharp accuracy degradation.To further enhance efficiency,we propose a renormalized free energy technique that approximates full-evaluation free energy using only the activation distribution of the unpruned network.This eliminates repeated forward passes,dramatically reducing computational overhead and achieving speedups of up to 550×for MLPs.Extensive experiments across diverse vision architectures(MLP,CNN,ResNet,MobileNet,Vision Transformer)and text models(LSTM,BERT,ELECTRA,T5,GPT-2)on multiple datasets validate the generality,robustness,and computational efficiency of our approach.Overall,this work establishes a theoretically grounded and practically effective framework for activation pruning,bridging the gap between analytical understanding and efficient deployment of sparse neural networks.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
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
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
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
This review highlights advances in inner ear organoids(IEOs)as a novel platform for drug screening and disease modeling,particularly for hearing loss.IEOs,derived from embryonic stem cells,induced pluripotent stem cel...This review highlights advances in inner ear organoids(IEOs)as a novel platform for drug screening and disease modeling,particularly for hearing loss.IEOs,derived from embryonic stem cells,induced pluripotent stem cells,or tissue-specific progenitors,provide a physiologically relevant alternative to traditional animal models.Significant progress has been made in utilizing various cell sources,extracellular matrix materials such as Matrigel and hydrogels,and methods for controlling microenvironments through biochemical and biophysical signals.Applications of IEOs in drug screening,disease modeling,and personalized medicine enable exploration of hearing loss mechanisms and therapeutic testing.However,challenges remain,including the incomplete maturation of cochlear cells and difficulty replicating in vivo environments.Future research should focus on optimizing IEO generation,incorporating microfluidic technologies,and advancing high-throughput screening to enhance drug discovery and clinical translation.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
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
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
Soft robotic manipulators represent a rapidly evolving field characterized by inherent compliance,adaptability,and safe interactions within unstructured environments.Over the past decade(2015-2025),significant advance...Soft robotic manipulators represent a rapidly evolving field characterized by inherent compliance,adaptability,and safe interactions within unstructured environments.Over the past decade(2015-2025),significant advancements have trans-formed their capabilities through novel designs inspired by biological systems,advanced modeling frameworks,sophisti-cated control strategies,and integration into diverse real-world applications.Recent innovations in multifunctional mate-rials and emerging actuation technologies have markedly expanded manipulator performance,reliability,and dexterity.Concurrently,developments in modeling have progressed from simplified geometric methods toward highly accurate physics-based and hybrid data-driven approaches,substantially improving real-time prediction and controllability.Coupled with these developments,adaptive and robust control strategies-including learning-based techniques-have enabled unprec-edented autonomy and precision in challenging application domains such as Minimally Invasive Surgery(MIS),precision agriculture,deep-sea exploration,disaster recovery,and space missions.Despite these remarkable strides,key challenges remain,notably regarding scalability,long-term material durability,robust integrated sensing,and standardized evaluation procedures.This review comprehensively synthesizes recent advances,critically evaluates state-of-the-art methodologies,and systematically identifies existing gaps to provide a clear roadmap and targeted research directions,guiding future developments toward the broader adoption and optimal utilization of soft robotic manipulators.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
基金Aeronautical Science Foundation of China (2008ZA51002)
文摘This article presents a parameterized configuration modeling approach to develop a 6 degrees of freedom （DOF） rigid-body model for air-breathing hypersonic vehicle （AHV）. The modeling process involves the parameterized configuration design, inviscous hypersonic aerodynamic force calculation and scramjet engine modeling. The parameters are designed for airframe-propulsion integration configuration, the aerodynamic force calculation is based on engineering experimental methods, and the engine model is acquired from gas dynamics and quasi-one dimensional combustor calculations. Multivariate fitting is used to obtain analytical equations for aerodynamic force and thrust. Furthermore, the fitting accuracy is evaluated by relative error （RE）. Trim results show that the model can be applied to the investigation of control method for AHV during the cruise phase. The modeling process integrates several disciplines such as configuration design, aerodynamic calculation, scramjet modeling and control method. Therefore the modeling method makes it possible to conduct AHV aerodynamics/propulsion/control integration design.
文摘Since the subsystems of aerodynamics,propulsion,structure and so on in hypersonic vehicles involve characteristics of nonlinearity,strong coupling and uncertainty,and typical hypersonic vehicles adopt slender-body and wave-rider layout with widely-used lightweight materials,the accuracy of the modeling with a conventional rigid-body assumption is challenged.Therefore,a nonlinear mathematical longitudinal model of a hypersonic vehicle is established with its geometry provided to estimate aerodynamic force and thrust using hypersonic aerodynamics and quasi-one-dimensional flow with heat added and capture vehicle aeroelasticity using a single free-free Bernoulli-Euler beam model.Then the static and dynamic properties of the rigid and rigid-aeroelasticity coupling model are compared via theoretical analysis and numerical simulation under the given flight condition.Finally,a LQR controller for rigid model is designed and the comparable results are obtained to explain the aerolasticity influence on the control effect.The simulation results show that the aeroelasticity mode of slender-body hypersonic vehicles affects short period mode significantly and it cannot be simply neglected.
基金supported by KU Leuven,Belgium through the TECHPED-C2 project(C24M/21/021)which investigates tech-nically feasible and effective solutions for Positive Energy Districts.Additional support was provided by the National University of Singa-pore,Singapore through the Start-Up Grant(A-0009876-00-00)the Ministry of Education,Singapore,under the Academic Research Fund Tier 1(A-8003235-00-00).
文摘Delivering energy flexibility at the district scale entails coordinating control actions across many buildings to shape aggregate demand;this coordination depends on training and deploying control policies and optimization routines,which in turn require predictive models that can be queried efficiently over large building clusters.However,conventional physics-based simulators are computationally prohibitive for large-scale control training,and simple data-driven surrogates often lack the generalization needed for heterogeneous clusters.This paper introduces ScaleONet,a deep operator network framework designed for scalable,control-oriented modeling of building-cluster thermal dynamics.ScaleONet leverages the DeepONet paradigm to decouple and share learning across buildings:an LSTM-based branch network encodes outdoor climate and individual HVAC control signals,while a multilayer perceptron(MLP)-based trunk network embeds prediction timestamps,enabling fast predictions for growing clusters with negligible extra cost for each additional building or timestep.To the authors’knowledge,this is the first operator-learning method tailored to indoor air temperature forecasting in heterogeneous building clusters.Validation on thirty Belgian buildings(GenkNet)simulated in Dymola shows that,although a non-operator-learning LSTM baseline slightly outperforms ScaleONet for single-building cases,its error grows monotonically with cluster size.In contrast,ScaleONet’s median per-building-per-day RMSE decreases from 0.59°C at three buildings to 0.53°C at ten and 0.47°C at thirty,compared to 0.95°C for the LSTM at thirty buildings-a 51%reduction in prediction error.Error analysis across envelope heat-loss coefficients(UAbuilding)further reveals that while the LSTM’s RMSE increases for high-𝑈𝐴structures,ScaleONet maintains uniformly low error.With millisecond-scale inference(approximately 4 ms per sample for thirty buildings),ScaleONet is well suited for large-scale reinforcement learning,receding-horizon optimization,and real-time model predictive control.
文摘This paper proposes a robust control-oriented identification method for errors-in-variables(EIV)systems in output feedbacks using frequency-response(FR)experimental data.An important relation between such a closed-loop EIV system and its coprime factor(CF)uncertainty description is first derived,based on which the FR measurements suitable for plant CF identification are able to be generated.Different factorizations of a given controller in the closed-loop system can be made best use to adjust right coprime factors(RCFs)of the plant so as to realize an improvement on the signal-to-noise ratio of identification experimental data.Subsequently,a nominal RCF model is estimated by linear matrix inequalities from the applicable FR measurements and its associated worst-case errors are quantified from a priori and a posteriori information on the underlying system.A resulting RCF perturbation model set can then be described by the nominal RCF model and its worst-case error bounds.Such a model set capable of being stabilized by the given controller is ready for its robust stabilizing controller redesign and robust performance analysis.Finally,a numerical simulation is given to show the efficacy of the proposed identification method.
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 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output of a research project implemented as part of the Basic Research Program at HSE University。
文摘Activation pruning reduces neural network complexity by eliminating low-importance neuron activations,yet identifying the critical pruning threshold—beyond which accuracy rapidly deteriorates—remains computationally expensive and typically requires exhaustive search.We introduce a thermodynamics-inspired framework that treats activation distributions as energy-filtered physical systems and employs the free energy of activations as a principled evaluation metric.Phase-transition-like phenomena in the free-energy profile—such as extrema,inflection points,and curvature changes—yield reliable estimates of the critical pruning threshold,providing a theoretically grounded means of predicting sharp accuracy degradation.To further enhance efficiency,we propose a renormalized free energy technique that approximates full-evaluation free energy using only the activation distribution of the unpruned network.This eliminates repeated forward passes,dramatically reducing computational overhead and achieving speedups of up to 550×for MLPs.Extensive experiments across diverse vision architectures(MLP,CNN,ResNet,MobileNet,Vision Transformer)and text models(LSTM,BERT,ELECTRA,T5,GPT-2)on multiple datasets validate the generality,robustness,and computational efficiency of our approach.Overall,this work establishes a theoretically grounded and practically effective framework for activation pruning,bridging the gap between analytical understanding and efficient deployment of sparse neural networks.
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.
基金supported by the National Natural Science Foundation of China(82222017 and 82271183)Hubei Province’s Key Research and Development Program(2022BCA046)the Start-up Research Fund of Southeast University(RF1028623028).
文摘This review highlights advances in inner ear organoids(IEOs)as a novel platform for drug screening and disease modeling,particularly for hearing loss.IEOs,derived from embryonic stem cells,induced pluripotent stem cells,or tissue-specific progenitors,provide a physiologically relevant alternative to traditional animal models.Significant progress has been made in utilizing various cell sources,extracellular matrix materials such as Matrigel and hydrogels,and methods for controlling microenvironments through biochemical and biophysical signals.Applications of IEOs in drug screening,disease modeling,and personalized medicine enable exploration of hearing loss mechanisms and therapeutic testing.However,challenges remain,including the incomplete maturation of cochlear cells and difficulty replicating in vivo environments.Future research should focus on optimizing IEO generation,incorporating microfluidic technologies,and advancing high-throughput screening to enhance drug discovery and clinical translation.
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Open access funding provided by The Science,Technology&Innovation Funding Authority(STDF)in cooperation with The Egyptian Knowledge Bank(EKB).
文摘Soft robotic manipulators represent a rapidly evolving field characterized by inherent compliance,adaptability,and safe interactions within unstructured environments.Over the past decade(2015-2025),significant advancements have trans-formed their capabilities through novel designs inspired by biological systems,advanced modeling frameworks,sophisti-cated control strategies,and integration into diverse real-world applications.Recent innovations in multifunctional mate-rials and emerging actuation technologies have markedly expanded manipulator performance,reliability,and dexterity.Concurrently,developments in modeling have progressed from simplified geometric methods toward highly accurate physics-based and hybrid data-driven approaches,substantially improving real-time prediction and controllability.Coupled with these developments,adaptive and robust control strategies-including learning-based techniques-have enabled unprec-edented autonomy and precision in challenging application domains such as Minimally Invasive Surgery(MIS),precision agriculture,deep-sea exploration,disaster recovery,and space missions.Despite these remarkable strides,key challenges remain,notably regarding scalability,long-term material durability,robust integrated sensing,and standardized evaluation procedures.This review comprehensively synthesizes recent advances,critically evaluates state-of-the-art methodologies,and systematically identifies existing gaps to provide a clear roadmap and targeted research directions,guiding future developments toward the broader adoption and optimal utilization of soft robotic manipulators.
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.
