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
AIM:To build a functional generalized estimating equation(GEE)model to detect glaucomatous visual field progression and compare the performance of the proposed method with that of commonly employed algorithms.METHODS:...AIM:To build a functional generalized estimating equation(GEE)model to detect glaucomatous visual field progression and compare the performance of the proposed method with that of commonly employed algorithms.METHODS:Totally 716 eyes of 716 patients with primary open angle glaucoma(POAG)with at least 5 reliable 24-2 test results and 2y of follow-up were selected.The functional GEE model was used to detect perimetric progression in the training dataset(501 eyes).In the testing dataset(215 eyes),progression was evaluated the functional GEE model,mean deviation(MD)and visual field index(VFI)rates of change,Advanced Glaucoma Intervention Study(AGIS)and Collaborative Initial Glaucoma Treatment Study(CIGTS)scores,and pointwise linear regression(PLR).RESULTS:The proposed method showed the highest proportion of eyes detected as progression(54.4%),followed by the VFI rate(34.4%),PLR(23.3%),and MD rate(21.4%).The CIGTS and AGIS scores had a lower proportion of eyes detected as progression(7.9%and 5.1%,respectively).The time to detection of progression was significantly shorter for the proposed method than that of other algorithms(adjusted P≤0.019).The VFI rate displayed moderate pairwise agreement with the proposed method(k=0.47).CONCLUSION:The functional GEE model shows the highest proportion of eyes detected as perimetric progression and the shortest time to detect perimetric progression in patients with POAG.展开更多
It is well known that coarse-grained super-elastic NiTi shape memory alloys(SMAs)exhibit localized rather than homogeneous martensite transformation(MT),which,however,can be strongly influenced by either internal size...It is well known that coarse-grained super-elastic NiTi shape memory alloys(SMAs)exhibit localized rather than homogeneous martensite transformation(MT),which,however,can be strongly influenced by either internal size(grain size,GS)or the external size(geometric size).The coupled effect of GS and geometric size on the functional properties has not been clearly understood yet.In this work,the super-elasticity,one-way,and stress-assisted two-way shape memory effects of the polycrystalline NiTi SMAs with different aspect ratios(length/width for the gauge section)and different GSs are investigated based on the phase field method.The coupled effect of the aspect ratio and GS on the functional properties is adequately revealed.The simulated results indicate that when the aspect ratio is lower than about 4:1,the stress biaxiality and stress heterogeneity in the gauge section of the sample become more and more obvious with decreasing the aspect ratio,which can significantly influence the microstructure evolution in the process involving external stress.Therefore,the corresponding functional property is strongly dependent on the aspect ratio.With decreasing the GS and the aspect ratio(to be lower than 4:1),both the aspect ratio and GS can affect the MT or martensite reorientation in each grain and the interaction among grains.Thus,due to the strong internal constraint(i.e.,the constraint of grain boundary)and the external constraint(i.e.,the constraint of geometric boundary),the capabilities of the functional properties of NiTi SMAs are gradually weakened and highly dependent on these two factors.展开更多
We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers...We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers based on the Lambert W function:a voltage-driven V-Lambert solver for high-fidelity I–V computation and a resistance-driven R-Lambert solver designed for seamless integration in a closed-loop PV emulator.Unlike Taylor-linearized explicit models,our proposed formulation retains the exponential nonlinearity of the PV equations.It employs a numerically stable analytical evaluation that eliminates the need for lookup tables and root-finding,all while maintaining limited computational costs and a small memory footprint.The R-Lambert model is integrated into a buck-converter emulator equipped with a discrete PI regulator,which generates current references directly from sensed operating points,thus supporting hardware-constrained implementation.Comprehensive numerical experiments conducted on six commercial modules from various technologies(mono,poly,and multicrystalline)demonstrate significant accuracy improvements under the IEC EN 50530 near-MPP criterion:the V-Lambert solver reduces the±10%Vmpp band error by up to 61 times compared to an explicit-model baseline.Dynamic simulations under varying irradiance,temperature,and load conditions achieve millisecond-scale settling with accurate trajectory tracking.Additionally,processor-in-the-loop experimental validation on an embedded microcontroller supports the simulation results.By unifying exact analytical modeling with embedded realization,this work advances computer modeling for PV emulation,MPPT benchmarking,and controller verification in integrated renewable energy systems.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
In rock engineering,natural cracks in rock masses subjected to external loads tend to initiate and propagate,leading to potential safety hazards.To investigate the effect of cracking behavior on the mechanical propert...In rock engineering,natural cracks in rock masses subjected to external loads tend to initiate and propagate,leading to potential safety hazards.To investigate the effect of cracking behavior on the mechanical properties of rocks,the cracking processes of pre-cracked rocks have been extensively studied using numerical modeling methods.The peridynamics(PD)exhibits advantages over other numerical methods due to the absence of the requirements for remeshing and external crack growth criterion.However,for modeling pre-cracked rock cracking processes under impact,current PD implementations lack generally applicable rock constitutive models and impact contact models,which leads to difficulties in determining rock material parameters and efficiently calculating impact loads.This paper proposes a non-ordinary state-based peridynamics(NOSBPD)modeling method integrating the Drucker-Prager(DP)plasticity model and an efficient contact model to address the above problems.In the proposed method,the Drucker-Prager plasticity model is integrated into the NOSBPD,thereby equipping NOSBPD with the capability to accurately characterize the nonlinear stress-strain relationship inherent in rocks.An efficient contact model between particles and meshes is designed to calculate the impact loads,which is essentially a coupling method of PD with the finite element method(FEM).The effectiveness of the proposed NOSBPD modeling method is verified by comparison with other numerical methods and experiments.Experimental results indicate that the proposed method can effectively and accurately predict the 3D cracking processes of pre-cracked cracks under impact loading,and the maximum principal stress is the key driver behind wing crack formation in pre-cracked rocks.展开更多
Background:Rats are often used to prepare skin defect models.However,the skin defect sizes of the models prepared by researchers are different,and the lack of consensus on the critical-size defect makes it difficult t...Background:Rats are often used to prepare skin defect models.However,the skin defect sizes of the models prepared by researchers are different,and the lack of consensus on the critical-size defect makes it difficult to compare their research results.Methods:The time for wound closure was evaluated and recorded through gross observation.The regression equation between the healing time and the diameter of skin defect was established,which can be used to predict the healing time for a certain skin defect size in rats.Histochemical and immunohistochemical staining was used to observe the regeneration and reconstruction of skin appendages,and the functional skin repair was quantitatively scored.Results:The critical-size defect of rats was determined based on the maximum capacity of structural skin repair,and the functional skin repair was quantitatively scored based on the regeneration and reconstruction of skin appendages.The allowable range of critical-size skin defect of SD rats lies between 45 and 50 mm in diameter.The concept of structural repair and the category of functional repair of injured skin are put forward.The regression equation between the structural skin healing time and defect diameters is established.Conclusion:The allowable range of skin critical-size defect of SD rats lies between 45 and 50 mm in diameter.The regression equation between the structural skin healing time and defect diameters can be used to predict the healing time for a certain skin defect size in rats.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
Industrial robot dynamics lay the foundation for high-precision and high-speed control, and accurate identification of dynamic parameters is essential for precise dynamic calculations. The choice of friction models is...Industrial robot dynamics lay the foundation for high-precision and high-speed control, and accurate identification of dynamic parameters is essential for precise dynamic calculations. The choice of friction models is a critical component in the identification of industrial robot dynamics. Traditional static friction models struggle to capture the hysteresis effects caused by robot joint elasticity and clearances, leading to large torque prediction errors when the joint velocity crosses zero. Due to the presence of hysteresis effects, the joint velocity crosses zero in the forward direction, and the reverse direction will have different friction patterns. Although the hysteresis effects can be modeled as an ordinary differential equation(ODE), it is difficult to determine the ODE structure that achieves both generalization and accuracy to describe the hysteresis effects of the friction model. To address this issue, we propose the neural hysteresis friction(NHF), which uses neural ODE to model the hysteresis effects in a data-driven manner, thereby mitigating the current inadequacies in the study of dynamic friction characteristics. The experiments on a real 6-axis industrial robot demonstrate that our proposed method can accurately model the friction dynamics during directional switching and outperform other modeling methods. Velocity tracking control experiments show that NHF can effectively reduce tracking errors when the velocity crosses zero.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
Slopes are likely to fail in areas with frequent rainfall and earthquakes.The deformation characteristics of unsaturated slopes subjected to post-rainfall earthquakes are investigated using centrifuge model tests and ...Slopes are likely to fail in areas with frequent rainfall and earthquakes.The deformation characteristics of unsaturated slopes subjected to post-rainfall earthquakes are investigated using centrifuge model tests and finite element analyses.Three tests of the slope deformation under earthquake and post-rainfall earthquakes are first studied using image analysis techniques.Then,based on an elastoplastic constitutive model,numerical simulations are carried out using the finite element method and compared with the centrifuge test results.Finally,a parametric study is performed to clarify the effects of antecedent rainfall on earthquake-induced slope deformation.The results show that slope deformation caused by post-rainfall earthquakes differs from that caused by earthquakes without antecedent rainfall.The seepage flow and soil strength of the slope are affected by previous rainfall conditions,such as intensity and duration,which directly influence the slope deformation caused by the subsequent earthquake.Soil displacement and strain become greater and the slip surface is more noticeable during the post-rainfall earthquake of higher intensity.In addition,the time interval between the rainfall and the earthquake has a considerable impact on the detailed characteristics of the slope deformation,and the significant deformation occurs at the time of lowest soil strength when seepage flow reaches the lower part of the slope.Moreover,the repeated intermittent rainfall greatly affects the subsequent earthquake-induced slope deformation,the main characteristics of which are closely related to the changes in saturation and strength of the slope.However,with the prolonged time gap between each round of rainfall,the earthquake-induced slope deformation becomes insignificant.展开更多
Hepatitis B Virus(HBV)infection and heavy alcohol consumption are the two primary pathogenic causes of liver cirrhosis.In this paper,we proposed a deterministic mathematical model and a logistic equation to investigat...Hepatitis B Virus(HBV)infection and heavy alcohol consumption are the two primary pathogenic causes of liver cirrhosis.In this paper,we proposed a deterministic mathematical model and a logistic equation to investigate the dynamics of liver cirrhosis progression as well as to explain the implications of variations in alcohol consumption on chronic hepatitis B patients,respectively.The intricate interactions between liver cirrhosis,recovery,and treatment dynamics are captured by the model.This study aims to show that alcohol consumption by Hepatitis B-infected individuals accelerates liver cirrhosis progression while treatment of acutely infected individuals reduces it.We proved that a unique solution of the proposed model exists,which is positive and bounded.Using the next-generation matrix approach,two basic reproductive numbers R_(A_(0))and R_(A_(max))are calculated to identify future recurrence.The equilibrium points are calculated,and both equilibria are proved locally and globally asymptotically stable when R_(0)is below and above one,respectively.It is shown that bifurcation exists at R_(0)=1 and a detailed proof for forward bifurcation is given.Furthermore,we performed the sensitivity analysis of the model parameters on R_(0).For the confirmation of analytical work,we performed numerical simulations,and the results indicate that the treatment and the inhibitory effects reduce the risk of developing liver cirrhosis in individuals,while heavy alcohol consumption accelerates markedly the liver cirrhosis progression in patients with chronic hepatitis B.展开更多
Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network lev...Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery.展开更多
The accuracy of genomic annotation is crucial for subsequent functional investigations;however,computational protocols used in high-throughput annotation of open reading frames(ORFs)can introduce inconsistencies.These...The accuracy of genomic annotation is crucial for subsequent functional investigations;however,computational protocols used in high-throughput annotation of open reading frames(ORFs)can introduce inconsistencies.These inconsistencies,which lead to non-uniform extension or truncation of sequence ends,pose challenges for downstream analyses.Existing strategies to rectify these inconsistencies are time-consuming and labor-intensive,lacking specific approaches.To address this gap,we developed to GC,a tool that integrates genomic annotation with RNA-seq datasets to rectify annotation inconsistencies.Using to GC,we achieved an accuracy of nearly 100%accuracy in correcting inconsistencies in published Phytophthora sojae ORFs.We applied this innovative pipeline to the GPCR-bigrams gene family,which was predicted to have 42 members in the P.sojae genome but lacked experimental validation.By employing to GC,we identified 32 GPCR-bigram ORFs with inconsistencies between previous annotations and to GC-corrected sequences.Notably,among these were 5 genes(GPCR-TKL9,GPCR-TKL15,GPCR-PDE3,GPCR-AC3,and GPCR-AC4)showed substantial inconsistencies.Experimental gene annotation confirmed the effectiveness of to GC,as sequences obtained through cloning matched those annotated by to GC.Importantly,we discovered two novel GPCRs(GPCR-AC3 and GPCR-AC4),which were previously mispredicted as a single gene.CRISPR/Cas9-mediated knockout experiments revealed the involvement of GPCR-AC4 but not GPCR-AC3 in oospore production,further confirming their status as two separate genes.In addition to P.sojae,the reliability of the to GC pipeline in Phytophthora capsici and Pythium ultimum further emphasizes the robustness of this pipeline.Our findings highlight the utility of to GC for reliable gene model correction,facilitating investigations into biological functions and offering potential applications in diverse species analyses.展开更多
Accurate fault modeling is essential for understanding earthquake rupture processes and improving seismic hazard assessment.We present a unified framework that integrates geodetic data with multidisciplinary constrain...Accurate fault modeling is essential for understanding earthquake rupture processes and improving seismic hazard assessment.We present a unified framework that integrates geodetic data with multidisciplinary constraints,including relocated aftershocks,geological observations,and geophysical information,to adaptively model fault geometry and slip in diverse scenarios such as multi-segment and multi-event ruptures.The framework combines adaptive fault construction with a scenario-driven Bayesian joint inversion approach.Fault geometries are first built from prior constraints,such as surface ruptures and aftershocks,and then refined through probabilistic inference when such data are inadequate.To enhance computational efficiency,we introduce a Sequential Monte Carlo Fukuda-Johnson(SMC-FJ)strategy.This separates nonlinear parameters-including geometry,data weights,and smoothing factors-from linear slip parameters,which are conditionally solved via constrained least squares.Geometry updates follow a hierarchical adjustment scheme based on point,line,and structural units,enabling flexibility across rupture complexities.Synthetic tests and four case studies,including the 2022 Menyuan,2023 Türkiye,2022 Luding,and 2019 Ridgecrest earthquakes,demonstrate robustness under various constraints.For the Menyuan earthquake,full Bayesian inversion confirms that the fault geometry constrained by relocated aftershocks is highly accurate and needs only minor adjustment to match the observed surface deformation.The results further show that gradual changes in fault strike and dip modulated rupture arrest and postseismic stress accumulation,highlighting the critical role of inherited geometric structure in controlling rupture termination and delayed seismic activation.展开更多
Amphibious vehicles are more prone to attitude instability compared to ships,making it crucial to develop effective methods for monitoring instability risks.However,large inclination events,which can lead to instabili...Amphibious vehicles are more prone to attitude instability compared to ships,making it crucial to develop effective methods for monitoring instability risks.However,large inclination events,which can lead to instability,occur frequently in both experimental and operational data.This infrequency causes events to be overlooked by existing prediction models,which lack the precision to accurately predict inclination attitudes in amphibious vehicles.To address this gap in predicting attitudes near extreme inclination points,this study introduces a novel loss function,termed generalized extreme value loss.Subsequently,a deep learning model for improved waterborne attitude prediction,termed iInformer,was developed using a Transformer-based approach.During the embedding phase,a text prototype is created based on the vehicle’s operation log data is constructed to help the model better understand the vehicle’s operating environment.Data segmentation techniques are used to highlight local data variation features.Furthermore,to mitigate issues related to poor convergence and slow training speeds caused by the extreme value loss function,a teacher forcing mechanism is integrated into the model,enhancing its convergence capabilities.Experimental results validate the effectiveness of the proposed method,demonstrating its ability to handle data imbalance challenges.Specifically,the model achieves over a 60%improvement in root mean square error under extreme value conditions,with significant improvements observed across additional metrics.展开更多
Accurate mechanical modeling is essential for robotic belt grinding(RBG), a process characterized by compliant contact mechanisms that make force prediction particularly challenging. However, existing mechanical model...Accurate mechanical modeling is essential for robotic belt grinding(RBG), a process characterized by compliant contact mechanisms that make force prediction particularly challenging. However, existing mechanical models predominantly focus on macroscale compliance while neglecting grain-scale compliant motion. Moreover, abrasive grains are typically idealized as regular shapes, overlooking the inherent stochasticity of real grain geometries. This study proposes a shapeequivalence method for modeling stochastic abrasive grains and develops a multiscale compliant force model for RBG. Specifically, an individual grain is represented as a polygonal pyramid with stochastic edges that is mathematically equivalent to a cone;this method unifies the treatment of grain geometries and streamlines the modeling process. The mathematical equivalence relationship for random grain shapes is further derived based on a grain-compliant contact model. By integrating grain geometric characteristics and progressive grain wear, an analytical mechanical model that captures both the static contact force and dynamic grinding force is established, thereby describing the transition from grain-workpiece compliant interaction to belt-workpiece elastic contact. Grinding experiments were conducted using abrasive belts with different grain shape distributions to validate the model. The results demonstrated reliable predictions of the tangential grinding force and its component characteristics. Additional analyses were performed to reveal how the tangential grinding force varies with wear time and grinding parameters.展开更多
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Supported by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute(KHIDI),funded by the Ministry of Health&Welfare,Republic of Korea(No.HR20C0026)the National Research Foundation of Korea(NRF)(No.RS-2023-00247504)the Patient-Centered Clinical Research Coordinating Center,funded by the Ministry of Health&Welfare,Republic of Korea(No.HC19C0276).
文摘AIM:To build a functional generalized estimating equation(GEE)model to detect glaucomatous visual field progression and compare the performance of the proposed method with that of commonly employed algorithms.METHODS:Totally 716 eyes of 716 patients with primary open angle glaucoma(POAG)with at least 5 reliable 24-2 test results and 2y of follow-up were selected.The functional GEE model was used to detect perimetric progression in the training dataset(501 eyes).In the testing dataset(215 eyes),progression was evaluated the functional GEE model,mean deviation(MD)and visual field index(VFI)rates of change,Advanced Glaucoma Intervention Study(AGIS)and Collaborative Initial Glaucoma Treatment Study(CIGTS)scores,and pointwise linear regression(PLR).RESULTS:The proposed method showed the highest proportion of eyes detected as progression(54.4%),followed by the VFI rate(34.4%),PLR(23.3%),and MD rate(21.4%).The CIGTS and AGIS scores had a lower proportion of eyes detected as progression(7.9%and 5.1%,respectively).The time to detection of progression was significantly shorter for the proposed method than that of other algorithms(adjusted P≤0.019).The VFI rate displayed moderate pairwise agreement with the proposed method(k=0.47).CONCLUSION:The functional GEE model shows the highest proportion of eyes detected as perimetric progression and the shortest time to detect perimetric progression in patients with POAG.
基金supported by the National Natural Science Foundation of China (Grant Nos.12202294 and 12022208)the Project funded by China Postdoctoral Science Foundation (Grant No.2022M712243)the Fundamental Research Funds for the Central Universities (Grant No.2023SCU12098).
文摘It is well known that coarse-grained super-elastic NiTi shape memory alloys(SMAs)exhibit localized rather than homogeneous martensite transformation(MT),which,however,can be strongly influenced by either internal size(grain size,GS)or the external size(geometric size).The coupled effect of GS and geometric size on the functional properties has not been clearly understood yet.In this work,the super-elasticity,one-way,and stress-assisted two-way shape memory effects of the polycrystalline NiTi SMAs with different aspect ratios(length/width for the gauge section)and different GSs are investigated based on the phase field method.The coupled effect of the aspect ratio and GS on the functional properties is adequately revealed.The simulated results indicate that when the aspect ratio is lower than about 4:1,the stress biaxiality and stress heterogeneity in the gauge section of the sample become more and more obvious with decreasing the aspect ratio,which can significantly influence the microstructure evolution in the process involving external stress.Therefore,the corresponding functional property is strongly dependent on the aspect ratio.With decreasing the GS and the aspect ratio(to be lower than 4:1),both the aspect ratio and GS can affect the MT or martensite reorientation in each grain and the interaction among grains.Thus,due to the strong internal constraint(i.e.,the constraint of grain boundary)and the external constraint(i.e.,the constraint of geometric boundary),the capabilities of the functional properties of NiTi SMAs are gradually weakened and highly dependent on these two factors.
基金funded by Scientific Research Deanship at University of Ha’il-Saudi Arabia through project number(RG-24014).
文摘We present a computer-modeling framework for photovoltaic(PV)source emulation that preserves the exact single-diode physics while enabling iteration-free,real-time evaluation.We derive two closed-form explicit solvers based on the Lambert W function:a voltage-driven V-Lambert solver for high-fidelity I–V computation and a resistance-driven R-Lambert solver designed for seamless integration in a closed-loop PV emulator.Unlike Taylor-linearized explicit models,our proposed formulation retains the exponential nonlinearity of the PV equations.It employs a numerically stable analytical evaluation that eliminates the need for lookup tables and root-finding,all while maintaining limited computational costs and a small memory footprint.The R-Lambert model is integrated into a buck-converter emulator equipped with a discrete PI regulator,which generates current references directly from sensed operating points,thus supporting hardware-constrained implementation.Comprehensive numerical experiments conducted on six commercial modules from various technologies(mono,poly,and multicrystalline)demonstrate significant accuracy improvements under the IEC EN 50530 near-MPP criterion:the V-Lambert solver reduces the±10%Vmpp band error by up to 61 times compared to an explicit-model baseline.Dynamic simulations under varying irradiance,temperature,and load conditions achieve millisecond-scale settling with accurate trajectory tracking.Additionally,processor-in-the-loop experimental validation on an embedded microcontroller supports the simulation results.By unifying exact analytical modeling with embedded realization,this work advances computer modeling for PV emulation,MPPT benchmarking,and controller verification in integrated renewable energy systems.
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support from the National Natural Science Foundation of China(Grant Nos.42277161 and 42230709).
文摘In rock engineering,natural cracks in rock masses subjected to external loads tend to initiate and propagate,leading to potential safety hazards.To investigate the effect of cracking behavior on the mechanical properties of rocks,the cracking processes of pre-cracked rocks have been extensively studied using numerical modeling methods.The peridynamics(PD)exhibits advantages over other numerical methods due to the absence of the requirements for remeshing and external crack growth criterion.However,for modeling pre-cracked rock cracking processes under impact,current PD implementations lack generally applicable rock constitutive models and impact contact models,which leads to difficulties in determining rock material parameters and efficiently calculating impact loads.This paper proposes a non-ordinary state-based peridynamics(NOSBPD)modeling method integrating the Drucker-Prager(DP)plasticity model and an efficient contact model to address the above problems.In the proposed method,the Drucker-Prager plasticity model is integrated into the NOSBPD,thereby equipping NOSBPD with the capability to accurately characterize the nonlinear stress-strain relationship inherent in rocks.An efficient contact model between particles and meshes is designed to calculate the impact loads,which is essentially a coupling method of PD with the finite element method(FEM).The effectiveness of the proposed NOSBPD modeling method is verified by comparison with other numerical methods and experiments.Experimental results indicate that the proposed method can effectively and accurately predict the 3D cracking processes of pre-cracked cracks under impact loading,and the maximum principal stress is the key driver behind wing crack formation in pre-cracked rocks.
基金National Key Research and Development Program of China,Grant/Award Number:2023YFC2410403。
文摘Background:Rats are often used to prepare skin defect models.However,the skin defect sizes of the models prepared by researchers are different,and the lack of consensus on the critical-size defect makes it difficult to compare their research results.Methods:The time for wound closure was evaluated and recorded through gross observation.The regression equation between the healing time and the diameter of skin defect was established,which can be used to predict the healing time for a certain skin defect size in rats.Histochemical and immunohistochemical staining was used to observe the regeneration and reconstruction of skin appendages,and the functional skin repair was quantitatively scored.Results:The critical-size defect of rats was determined based on the maximum capacity of structural skin repair,and the functional skin repair was quantitatively scored based on the regeneration and reconstruction of skin appendages.The allowable range of critical-size skin defect of SD rats lies between 45 and 50 mm in diameter.The concept of structural repair and the category of functional repair of injured skin are put forward.The regression equation between the structural skin healing time and defect diameters is established.Conclusion:The allowable range of skin critical-size defect of SD rats lies between 45 and 50 mm in diameter.The regression equation between the structural skin healing time and defect diameters can be used to predict the healing time for a certain skin defect size in rats.
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 National Natural Science Foundation of China (Grant No.52188102)。
文摘Industrial robot dynamics lay the foundation for high-precision and high-speed control, and accurate identification of dynamic parameters is essential for precise dynamic calculations. The choice of friction models is a critical component in the identification of industrial robot dynamics. Traditional static friction models struggle to capture the hysteresis effects caused by robot joint elasticity and clearances, leading to large torque prediction errors when the joint velocity crosses zero. Due to the presence of hysteresis effects, the joint velocity crosses zero in the forward direction, and the reverse direction will have different friction patterns. Although the hysteresis effects can be modeled as an ordinary differential equation(ODE), it is difficult to determine the ODE structure that achieves both generalization and accuracy to describe the hysteresis effects of the friction model. To address this issue, we propose the neural hysteresis friction(NHF), which uses neural ODE to model the hysteresis effects in a data-driven manner, thereby mitigating the current inadequacies in the study of dynamic friction characteristics. The experiments on a real 6-axis industrial robot demonstrate that our proposed method can accurately model the friction dynamics during directional switching and outperform other modeling methods. Velocity tracking control experiments show that NHF can effectively reduce tracking errors when the velocity crosses zero.
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 China Postdoctoral Science Foundation(CPSF)(Grant No.2024M762769)the Natural Science Basic Research Program of Shaanxi(Grant No.2024JC-YBQN-0333)the Postdoctoral Fellowship Program of CPSF(Grant No.GZC20232230).
文摘Slopes are likely to fail in areas with frequent rainfall and earthquakes.The deformation characteristics of unsaturated slopes subjected to post-rainfall earthquakes are investigated using centrifuge model tests and finite element analyses.Three tests of the slope deformation under earthquake and post-rainfall earthquakes are first studied using image analysis techniques.Then,based on an elastoplastic constitutive model,numerical simulations are carried out using the finite element method and compared with the centrifuge test results.Finally,a parametric study is performed to clarify the effects of antecedent rainfall on earthquake-induced slope deformation.The results show that slope deformation caused by post-rainfall earthquakes differs from that caused by earthquakes without antecedent rainfall.The seepage flow and soil strength of the slope are affected by previous rainfall conditions,such as intensity and duration,which directly influence the slope deformation caused by the subsequent earthquake.Soil displacement and strain become greater and the slip surface is more noticeable during the post-rainfall earthquake of higher intensity.In addition,the time interval between the rainfall and the earthquake has a considerable impact on the detailed characteristics of the slope deformation,and the significant deformation occurs at the time of lowest soil strength when seepage flow reaches the lower part of the slope.Moreover,the repeated intermittent rainfall greatly affects the subsequent earthquake-induced slope deformation,the main characteristics of which are closely related to the changes in saturation and strength of the slope.However,with the prolonged time gap between each round of rainfall,the earthquake-induced slope deformation becomes insignificant.
文摘Hepatitis B Virus(HBV)infection and heavy alcohol consumption are the two primary pathogenic causes of liver cirrhosis.In this paper,we proposed a deterministic mathematical model and a logistic equation to investigate the dynamics of liver cirrhosis progression as well as to explain the implications of variations in alcohol consumption on chronic hepatitis B patients,respectively.The intricate interactions between liver cirrhosis,recovery,and treatment dynamics are captured by the model.This study aims to show that alcohol consumption by Hepatitis B-infected individuals accelerates liver cirrhosis progression while treatment of acutely infected individuals reduces it.We proved that a unique solution of the proposed model exists,which is positive and bounded.Using the next-generation matrix approach,two basic reproductive numbers R_(A_(0))and R_(A_(max))are calculated to identify future recurrence.The equilibrium points are calculated,and both equilibria are proved locally and globally asymptotically stable when R_(0)is below and above one,respectively.It is shown that bifurcation exists at R_(0)=1 and a detailed proof for forward bifurcation is given.Furthermore,we performed the sensitivity analysis of the model parameters on R_(0).For the confirmation of analytical work,we performed numerical simulations,and the results indicate that the treatment and the inhibitory effects reduce the risk of developing liver cirrhosis in individuals,while heavy alcohol consumption accelerates markedly the liver cirrhosis progression in patients with chronic hepatitis B.
基金supported by the National Natural Science Foundation of China,Nos.81871836(to MZ),82172554(to XH),and 81802249(to XH),81902301(to JW)the National Key R&D Program of China,Nos.2018YFC2001600(to JX)and 2018YFC2001604(to JX)+3 种基金Shanghai Rising Star Program,No.19QA1409000(to MZ)Shanghai Municipal Commission of Health and Family Planning,No.2018YQ02(to MZ)Shanghai Youth Top Talent Development PlanShanghai“Rising Stars of Medical Talent”Youth Development Program,No.RY411.19.01.10(to XH)。
文摘Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery.
基金supported by the grants to Min Qiu and Ming Wang from the National Natural Science Foundation of China(32100160 and 32100044)the grants to Ming Wang from the Jiangsu“Innovative and Entrepreneurial Talent”Program,China(JSSCRC2021510)the grants to Yuanchao Wang from the Chinese Modern Agricultural Industry Technology System(CARS-004-PS14)。
文摘The accuracy of genomic annotation is crucial for subsequent functional investigations;however,computational protocols used in high-throughput annotation of open reading frames(ORFs)can introduce inconsistencies.These inconsistencies,which lead to non-uniform extension or truncation of sequence ends,pose challenges for downstream analyses.Existing strategies to rectify these inconsistencies are time-consuming and labor-intensive,lacking specific approaches.To address this gap,we developed to GC,a tool that integrates genomic annotation with RNA-seq datasets to rectify annotation inconsistencies.Using to GC,we achieved an accuracy of nearly 100%accuracy in correcting inconsistencies in published Phytophthora sojae ORFs.We applied this innovative pipeline to the GPCR-bigrams gene family,which was predicted to have 42 members in the P.sojae genome but lacked experimental validation.By employing to GC,we identified 32 GPCR-bigram ORFs with inconsistencies between previous annotations and to GC-corrected sequences.Notably,among these were 5 genes(GPCR-TKL9,GPCR-TKL15,GPCR-PDE3,GPCR-AC3,and GPCR-AC4)showed substantial inconsistencies.Experimental gene annotation confirmed the effectiveness of to GC,as sequences obtained through cloning matched those annotated by to GC.Importantly,we discovered two novel GPCRs(GPCR-AC3 and GPCR-AC4),which were previously mispredicted as a single gene.CRISPR/Cas9-mediated knockout experiments revealed the involvement of GPCR-AC4 but not GPCR-AC3 in oospore production,further confirming their status as two separate genes.In addition to P.sojae,the reliability of the to GC pipeline in Phytophthora capsici and Pythium ultimum further emphasizes the robustness of this pipeline.Our findings highlight the utility of to GC for reliable gene model correction,facilitating investigations into biological functions and offering potential applications in diverse species analyses.
基金supported by the National Natural Science Foundation of China(Grant Nos.42130101,42474002,42374003&42564002)the Jiangxi Provincial Natural Science Foundation(Grant No.20252BAC240262).
文摘Accurate fault modeling is essential for understanding earthquake rupture processes and improving seismic hazard assessment.We present a unified framework that integrates geodetic data with multidisciplinary constraints,including relocated aftershocks,geological observations,and geophysical information,to adaptively model fault geometry and slip in diverse scenarios such as multi-segment and multi-event ruptures.The framework combines adaptive fault construction with a scenario-driven Bayesian joint inversion approach.Fault geometries are first built from prior constraints,such as surface ruptures and aftershocks,and then refined through probabilistic inference when such data are inadequate.To enhance computational efficiency,we introduce a Sequential Monte Carlo Fukuda-Johnson(SMC-FJ)strategy.This separates nonlinear parameters-including geometry,data weights,and smoothing factors-from linear slip parameters,which are conditionally solved via constrained least squares.Geometry updates follow a hierarchical adjustment scheme based on point,line,and structural units,enabling flexibility across rupture complexities.Synthetic tests and four case studies,including the 2022 Menyuan,2023 Türkiye,2022 Luding,and 2019 Ridgecrest earthquakes,demonstrate robustness under various constraints.For the Menyuan earthquake,full Bayesian inversion confirms that the fault geometry constrained by relocated aftershocks is highly accurate and needs only minor adjustment to match the observed surface deformation.The results further show that gradual changes in fault strike and dip modulated rupture arrest and postseismic stress accumulation,highlighting the critical role of inherited geometric structure in controlling rupture termination and delayed seismic activation.
基金Supported by the National Defense Basic Scientific Research Program of China.
文摘Amphibious vehicles are more prone to attitude instability compared to ships,making it crucial to develop effective methods for monitoring instability risks.However,large inclination events,which can lead to instability,occur frequently in both experimental and operational data.This infrequency causes events to be overlooked by existing prediction models,which lack the precision to accurately predict inclination attitudes in amphibious vehicles.To address this gap in predicting attitudes near extreme inclination points,this study introduces a novel loss function,termed generalized extreme value loss.Subsequently,a deep learning model for improved waterborne attitude prediction,termed iInformer,was developed using a Transformer-based approach.During the embedding phase,a text prototype is created based on the vehicle’s operation log data is constructed to help the model better understand the vehicle’s operating environment.Data segmentation techniques are used to highlight local data variation features.Furthermore,to mitigate issues related to poor convergence and slow training speeds caused by the extreme value loss function,a teacher forcing mechanism is integrated into the model,enhancing its convergence capabilities.Experimental results validate the effectiveness of the proposed method,demonstrating its ability to handle data imbalance challenges.Specifically,the model achieves over a 60%improvement in root mean square error under extreme value conditions,with significant improvements observed across additional metrics.
基金supported by the National Natural Science Foundation of China (Grant Nos.52505554,52575571)the Postdoctoral Fellowship Program of CPSF (Grant No.GZB20250348)。
文摘Accurate mechanical modeling is essential for robotic belt grinding(RBG), a process characterized by compliant contact mechanisms that make force prediction particularly challenging. However, existing mechanical models predominantly focus on macroscale compliance while neglecting grain-scale compliant motion. Moreover, abrasive grains are typically idealized as regular shapes, overlooking the inherent stochasticity of real grain geometries. This study proposes a shapeequivalence method for modeling stochastic abrasive grains and develops a multiscale compliant force model for RBG. Specifically, an individual grain is represented as a polygonal pyramid with stochastic edges that is mathematically equivalent to a cone;this method unifies the treatment of grain geometries and streamlines the modeling process. The mathematical equivalence relationship for random grain shapes is further derived based on a grain-compliant contact model. By integrating grain geometric characteristics and progressive grain wear, an analytical mechanical model that captures both the static contact force and dynamic grinding force is established, thereby describing the transition from grain-workpiece compliant interaction to belt-workpiece elastic contact. Grinding experiments were conducted using abrasive belts with different grain shape distributions to validate the model. The results demonstrated reliable predictions of the tangential grinding force and its component characteristics. Additional analyses were performed to reveal how the tangential grinding force varies with wear time and grinding parameters.
