Bone repair remains an important target in tissue engineering,making the development of bioactive scaffolds for effective bone defect repair a critical objective.In this study,β-tricalcium phosphate(β-TCP)scaffolds ...Bone repair remains an important target in tissue engineering,making the development of bioactive scaffolds for effective bone defect repair a critical objective.In this study,β-tricalcium phosphate(β-TCP)scaffolds incorporated with processed pyritum decoction(PPD)were fabricated using three-dimensional(3D)printing-assisted freeze-casting.The produced composite scaffolds were evaluated for their mechanical strength,physicochemical properties,biocompatibility,in vitro proangiogenic activity,and in vivo efficacy in repairing rabbit femoral defects.They not only demonstrated excellent physicochemical properties,enhanced mechanical strength,and good biosafety but also significantly promoted the proliferation,migration,and aggregation of pro-angiogenic human umbilical vein endothelial cells(HUVECs).In vivo studies revealed that all scaffold groups facilitated osteogenesis at the bone defect site,with theβ-TCP scaffolds loaded with PPD markedly enhancing the expression of neurogenic locus Notch homolog protein 1(Notch1),vascular endothelial growth factor(VEGF),bone morphogenetic protein-2(BMP-2),and osteopontin(OPN).Overall,the scaffolds developed in this study exhibited strong angiogenic and osteogenic capabilities both in vitro and in vivo.The incorporation of PPD notably promoted the angiogenic-osteogenic coupling,thereby accelerating bone repair,which suggests that PPD is a promising material for bone repair and that the PPD/β-TCP scaffolds hold great potential as a bone graft alternative.展开更多
The heterogeneity of unconventional reservoir rock tremendously affects its hydrofracturing behavior. A visual representation and accurate characterization of the three-dimensional （3D） growth and distribution of hy...The heterogeneity of unconventional reservoir rock tremendously affects its hydrofracturing behavior. A visual representation and accurate characterization of the three-dimensional （3D） growth and distribution of hydrofracturing cracks within heterogeneous rocks is of particular use to the design and implementation of hydrofracturing stimulation of unconventional reservoirs. However, because of the difficulties involved in visually representing and quantitatively characterizing a 3D hydrofracturing crack-network, this issue remains a challenge. In this paper, a novel method is proposed for physically visualizing and quantitatively characterizing the 3D hydrofracturing crack-network distributed through a heterogeneous structure based on a natural glutenite sample. This method incorporates X-ray microfocus computed tomography （μCT）, 3D printing models and hydrofracturing triaxial tests to represent visually the heterogeneous structure, and the 3D crack growth and distribution within a transparent rock model during hydrofracturing. The coupled effects of material heterogeneity and confining geostress on the 3D crack initiation and propagation were analyzed. The results indicate that the breakdown pressure of a heterogeneous rock model is significantly affected by material heterogeneity and confining geostress. The measured breakdown pressures of heterogeneous models are apparently different from those predicted by traditional theories. This study helps to elucidate the quantitative visualization and characterization of the mechanism and influencing factors that determine the hydrofracturing crack initiation and propagation in heterogeneous reservoir rocks.展开更多
[Significance]In alignment with the national germplasm security strategy,current research efforts are accelerating the adoption of precision breeding in sheep.Within the whole-genome selection,accurate phenotyping of ...[Significance]In alignment with the national germplasm security strategy,current research efforts are accelerating the adoption of precision breeding in sheep.Within the whole-genome selection,accurate phenotyping of body morphometrics is critical for assessing growth performance and breeding value.Traditional manual measurements are inefficient,prone to human error,and may cause stress to sheep,limiting their suitability for precision sheep management.By summarizing the applications of sheep body size measurement technologies and analyzing their development directions,this paper provides theoretical references and practical guidance for the research and application of non contact sheep body size measurement.[Progress]This review synthesizes progress across three principal methodological paradigms:two-dimensional(2D)image-based techniques,three-dimensional(3D)point cloud-based approaches,and integrated 2D-3D fusion systems.2D methods,employing either handcrafted geometric features or deep learning-based keypoint detector algorithms,are cost-effective and operationally simple but sensitive to variation in imaging conditions and unable to capture critical circumference metrics.3D point-cloud approaches enable precise reconstruction of full animal morphology,supporting comprehensive body-size acquisition with higher accuracy,yet face challenges including high hardware costs,complex data workflows,and sensitivity to posture variability.Hybrid 2D-3D fusion systems combine semantic richness from RGB imagery with geometric completeness from point clouds.Having been effectively validated in other livestock specise,e.g.,cattle and pigs,these fusion systems have demonstrated excellent performance,providing important technical references and practical insights for sheep body size measurement.[Conclusions and Prospects]Firstly,future research should focus on constructing large-scale,high-quality datasets for sheep body size measurement that encompass diverse breeds,growth stages,and environmental conditions,thereby enhancing model robustness and generalization.Secondly,the development of lightweight artificial intelligence models is essential.Techniques such as model compression,quantization,and algorithmic optimization can substantially reduce computational complexity and storage requirements,facilitating deployment in resource-constrained environments.Thirdly,the 3D point cloud processing pipeline should be streamlined to improve the efficiency of data acquisition,filtering,registration,and segmentation,while promoting the integration of low-cost,high-resilience vision systems into practical farming scenarios.Fourthly,specific emphasis should be placed on improving the accuracy of curved-dimensional measurements,such as chest circumference,abdominal circumference,and shank circumference,through advances in pose standardization,refined 3D segmentation strategies,and multimodal data fusion.Finally,the cross-fertilization of sheep body size measurement technologies with analogous methods for other livestock species offers a promising pathway for mutual learning and collaborative innovation,accelerating the industrialization of automated sheep morphometric systems and supporting the development of intelligent,data-driven pasture management practices.展开更多
Internal structural defects in engineering rock masses vary in size,exhibit complex shapes,and are unevenly distributed.Dominant fractures within a rock mass often play a critical to its mechanical behavior,directly a...Internal structural defects in engineering rock masses vary in size,exhibit complex shapes,and are unevenly distributed.Dominant fractures within a rock mass often play a critical to its mechanical behavior,directly affecting the macromechanical properties and failure modes.These fractures affect the instability and failure of the surrounding rock,significantlyimpacting the overall stability of engineering structures.Herein,sand-powder three-dimensional(3D)printing technology was used to prepare rock-like specimens with internal fracture networks.Triaxial compression testing,post-failure fracture mapping,and fractal dimension analysis of the fracture surfaces were conducted to investigate the effects of dominant fracture angles on the strength and deformation of rocks with internal fracture networks under triaxial stress.The results indicate that the dominant fracture angle has a pronounced effect on the mechanical behavior of rock.With increasing angle,both compressive strength and elastic modulus exhibit an initial decline followed by an increase.Moreover,higher confiningpressure significantlyimproves the compressive strength of fractured rock.This enhancement weakens as the confiningpressure further increases.Moreover,with increasing confiningpressure,the differences between the maximum and minimum values of elastic moduli and lateral strain ratios in fractured rock gradually decrease.Thus,the impact of the dominant fracture angle on rock mass deformation decreases with increasing confiningpressure.This research elucidates the effects of dominant fracture angles on the mechanical and failure properties of complex fractured rock masses and the influenceof the confiningpressure on these relationships.It provides valuable theoretical insights and practical guidance for stability analyses in engineering rock masses.展开更多
Online three-dimensional(3D)path planning in dynamic environments is a fundamental problem for achieving autonomous navigation of unmanned aerial vehicles(UAVs).However,existing methods struggle to model traversable d...Online three-dimensional(3D)path planning in dynamic environments is a fundamental problem for achieving autonomous navigation of unmanned aerial vehicles(UAVs).However,existing methods struggle to model traversable dynamic gaps,resulting in conservative and suboptimal trajectories.To address these challenges,this paper proposes a hierarchical reinforcement learning(RL)framework that integrates global path guidance,local trajectory generation,predictive safety evaluation,and neural network-based decision-making.Specifically,the global planner provides long-term navigation guidance,and the local module then utilizes an improved 3D dynamic window approach(DWA)to generate dynamically feasible candidate trajectories.To enhance safety in dense dynamic scenarios,the algorithm introduces a predictive axis-aligned bounding box(AABB)strategy to model the future occupancy of obstacles,combined with convex hull verification for efficient trajectory safety assessment.Furthermore,a double deep Q-network(DDQN)is employed with structured feature encoding,enabling the neural network to reliably select the optimal trajectory from the candidate set,thereby improving robustness and generalization.Comparative experiments conducted in a high-fidelity simulation environment show that the algorithm outperforms existing algorithms,reducing the average number of collisions to 0.2 while shortening the average task completion time by approximately 15%,and achieving a success rate of 97%.展开更多
Currently,there are a limited number of dynamic models available for braided composite plates with large overall motions,despite the incorporation of three-dimensional(3D)braided composites into rotating blade compone...Currently,there are a limited number of dynamic models available for braided composite plates with large overall motions,despite the incorporation of three-dimensional(3D)braided composites into rotating blade components.In this paper,a dynamic model of 3D 4-directional braided composite thin plates considering braiding directions is established.Based on Kirchhoff's plate assumptions,the displacement variables of the plate are expressed.By incorporating the braiding directions into the constitutive equation of the braided composites,the dynamic model of the plate considering braiding directions is obtained.The effects of the speeds,braiding directions,and braided angles on the responses of the plate with fixed-axis rotation and translational motion,respectively,are investigated.This paper presents a dynamic theory for calculating the deformation of 3D braided composite structures undergoing both translational and rotational motions.It also provides a simulation method for investigating the dynamic behavior of non-isotropic material plates in various applications.展开更多
It is of great importance to obtain precise trace data,as traces are frequently the sole visible and measurable parameter in most outcrops.The manual recognition and detection of traces on high-resolution three-dimens...It is of great importance to obtain precise trace data,as traces are frequently the sole visible and measurable parameter in most outcrops.The manual recognition and detection of traces on high-resolution three-dimensional(3D)models are relatively straightforward but time-consuming.One potential solution to enhance this process is to use machine learning algorithms to detect the 3D traces.In this study,a unique pixel-wise texture mapper algorithm generates a dense point cloud representation of an outcrop with the precise resolution of the original textured 3D model.A virtual digital image rendering was then employed to capture virtual images of selected regions.This technique helps to overcome limitations caused by the surface morphology of the rock mass,such as restricted access,lighting conditions,and shading effects.After AI-powered trace detection on two-dimensional(2D)images,a 3D data structuring technique was applied to the selected trace pixels.In the 3D data structuring,the trace data were structured through 2D thinning,3D reprojection,clustering,segmentation,and segment linking.Finally,the linked segments were exported as 3D polylines,with each polyline in the output corresponding to a trace.The efficacy of the proposed method was assessed using a 3D model of a real-world case study,which was used to compare the results of artificial intelligence(AI)-aided and human intelligence trace detection.Rosette diagrams,which visualize the distribution of trace orientations,confirmed the high similarity between the automatically and manually generated trace maps.In conclusion,the proposed semi-automatic method was easy to use,fast,and accurate in detecting the dominant jointing system of the rock mass.展开更多
Liposarcoma is one of the most common soft tissue sarcomas,however,its occurrence rate is still rare compared to other cancers.Due to its rarity,in vitro experiments are an essential approach to elucidate liposarcoma ...Liposarcoma is one of the most common soft tissue sarcomas,however,its occurrence rate is still rare compared to other cancers.Due to its rarity,in vitro experiments are an essential approach to elucidate liposarcoma pathobiology.Conventional cell culture-based research(2D cell culture)is still playing a pivotal role,while several shortcomings have been recently under discussion.In vivo,mouse models are usually adopted for pre-clinical analyses with expectations to overcome the issues of 2D cell culture.However,they do not fully recapitulate human dedifferentiated liposarcoma(DDLPS)characteristics.Therefore,three-dimensional(3D)culture systems have been the recent research focus in the cell biology field with the expectation to overcome at the same time the disadvantages of 2D cell culture and in vivo animal models and fill in the gap between them.Given the liposarcoma rarity,we believe that 3D cell culture techniques,including 3D cell cultures/co-cultures,and Patient-Derived tumor Organoids(PDOs),represent a promising approach to facilitate liposarcoma investigation and elucidate its molecular mechanisms and effective therapy development.In this review,we first provide a general overview of 3D cell cultures compared to 2D cell cultures.We then focus on one of the recent 3D cell culture applications,Patient-Derived Organoids(PDOs),summarizing and discussing several PDO methodologies.Finally,we discuss the current and future applications of PDOs to sarcoma,particularly in the field of liposarcoma.展开更多
Observing plants across time and diverse scenes is critical in uncovering plant growth patterns.Classic methods often struggle to observe or measure plants against complex backgrounds and at different growth stages.Th...Observing plants across time and diverse scenes is critical in uncovering plant growth patterns.Classic methods often struggle to observe or measure plants against complex backgrounds and at different growth stages.This highlights the need for a universal approach capable of providing realistic plant visualizations across time and scene.Here,we introduce PlantGaussian,an approach for generating realistic three-dimensional(3D)visualization for plants across time and scenes.It marks one of the first applications of 3D Gaussian splatting techniques in plant science,achieving high-quality visualization across species and growth stages.By integrating the Segment Anything Model(SAM)and tracking algorithms,PlantGaussian overcomes the limitations of classic Gaussian reconstruction techniques in complex planting environments.A new mesh partitioning technique is employed to convert Gaussian rendering results into measurable plant meshes,offering a methodology for accurate 3D plant morphology phenotyping.To support this approach,PlantGaussian dataset is developed,which includes images of four crop species captured under multiple conditions and growth stages.Using only plant image sequences as input,it computes high-fidelity plant visualization models and 3D meshes for 3D plant morphological phenotyping.Visualization results indicate that most plant models achieve a Peak Signal-to-Noise Ratio(PSNR)exceeding 25,outperforming all models including the original 3D Gaussian Splatting and enhanced NeRF.The mesh results indicate an average relative error of 4%between the calculated values and the true measurements.As a generic 3D digital plant model,PlantGaussian will support expansion of plant phenotype databases,ecological research,and remote expert consultations.展开更多
The development of digital twins for geotechnical structures necessitates the real-time updates of threedimensional(3D)virtual models(e.g.numerical finite element method(FEM)model)to accurately predict time-varying ge...The development of digital twins for geotechnical structures necessitates the real-time updates of threedimensional(3D)virtual models(e.g.numerical finite element method(FEM)model)to accurately predict time-varying geotechnical responses(e.g.consolidation settlement)in a 3D spatial domain.However,traditional 3D numerical model updating approaches are computationally prohibitive and therefore difficult to update the 3D responses in real time.To address these challenges,this study proposes a novel machine learning framework called sparse dictionary learning(T-3D-SDL)for real-time updating of time-varying 3D geotechnical responses.In T-3D-SDL,a concerned dataset(e.g.time-varying 3D settlement)is approximated as a linear superposition of dictionary atoms generated from 3D random FEM analyses.Field monitoring data are then used to identify non-trivial atoms and estimate their weights within a Bayesian framework for model updating and prediction.The proposed approach enables the real-time update of temporally varying settlements with a high 3D spatial resolution and quantified uncertainty as field monitoring data evolve.The proposed approach is illustrated using an embankment construction project.The results show that the proposed approach effectively improves settlement predictions along temporal and 3D spatial dimensions,with minimal latency(e.g.within minutes),as monitoring data appear.In addition,the proposed approach requires only a reasonably small number of 3D FEM model evaluations,avoids the use of widely adopted yet often criticized surrogate models,and effectively addresses the limitations(e.g.computational inefficiency)of existing 3D model updating approaches.展开更多
We theoretically investigate the extended Bose-Hubbard model using a three-dimensional cubic lattice.In the framework of the dynamical Gutzwiller mean-field theory,we identify a checkerboard supersolid phase.By consid...We theoretically investigate the extended Bose-Hubbard model using a three-dimensional cubic lattice.In the framework of the dynamical Gutzwiller mean-field theory,we identify a checkerboard supersolid phase.By considering the repulsive interactions between next-nearest-neighbor lattice sites,we further discover an exotic type of supersolid state,whose site occupancies show a stereoscopically arrayed and staggered distribution rather than checkerboard ordering.Intriguingly,if the physical observations of two neighboring layers were superimposed,they would give rise to a checkerboard configuration.This novel structure is convincingly induced by the simultaneous existence of nearest-neighbor and nextnearest-neighbor interactions.We also identify arrayed stripes in the ground state,as well as arrayed holes in the pattern of occupancies.展开更多
Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results ca...Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results cannot be fed back to users timely.To address this issue,we proposed a human-machine interaction(HMI)method for discontinuity mapping.Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments.For this,a regular cube was selected to illustrate the workflows:(1)point cloud was acquired using remote sensing;(2)the HMI method was employed to select reference points and angle thresholds to detect group discontinuity;(3)individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm;and(4)the orientation of each discontinuity was measured based on a plane fitting algorithm.The method was applied to a well-studied highway road cut and a complex natural slope.The consistency of the computational results with field measurements demonstrates its good accuracy,and the average error in the dip direction and dip angle for both cases was less than 3.Finally,the computational time of the proposed method was compared with two other popular algorithms,and the reduction in computational time by tens of times proves its high computational efficiency.This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.展开更多
3D model classification has emerged as a significant research focus in computer vision.However,traditional convolutional neural networks(CNNs)often struggle to capture global dependencies across both height and width ...3D model classification has emerged as a significant research focus in computer vision.However,traditional convolutional neural networks(CNNs)often struggle to capture global dependencies across both height and width dimensions simultaneously,leading to limited feature representation capabilities when handling complex visual tasks.To address this challenge,we propose a novel 3D model classification network named ViT-GE(Vision Transformer with Global and Efficient Attention),which integrates Global Grouped Coordinate Attention(GGCA)and Efficient Channel Attention(ECA)mechanisms.Specifically,the Vision Transformer(ViT)is employed to extract comprehensive global features from multi-view inputs using its self-attention mechanism,effectively capturing 3D shape characteristics.To further enhance spatial feature modeling,the GGCA module introduces a grouping strategy and global context interactions.Concurrently,the ECA module strengthens inter-channel information flow,enabling the network to adaptively emphasize key features and improve feature fusion.Finally,a voting mechanism is adopted to enhance classification accuracy,robustness,and stability.Experimental results on the ModelNet10 dataset demonstrate that our method achieves a classification accuracy of 93.50%,validating its effectiveness and superior performance.展开更多
The introduction of path planning and visual navigation in vascular interventional surgery can provide an intuitive reference and guidance for doctors.In this study,based on the preprocessing results of vessel skeleto...The introduction of path planning and visual navigation in vascular interventional surgery can provide an intuitive reference and guidance for doctors.In this study,based on the preprocessing results of vessel skeleton extraction and stenosis diagnosis in X-ray coronary angiography images,clustering is used to determine the connectivity of the intersection points,and then the improved Dijkstra algorithm is used to automatically plan the surgical path.On this basis,the intermediate point is introduced to piecewise correct the path and improve the accuracy of the system.Finally,the epipolar constrained inverse projection transformation is used to reconstruct the coronary artery 3D model,and the optimal path is marked to achieve a multi-angle 3D visual navigation.Clinical experimental results show that compared with the traditional Dijkstra algorithm,the improved method can reduce the need for intermediate points,which improves computational efficiency,and the average error of manual calibration path is reduced to 4%of that before overall optimization.The results of 3D reconstruction and reprojection further qualitatively and quantitatively verify the effectiveness of the whole scheme.展开更多
This paper proposes an attitude control strategy for a flexible satellite equipped with an orthogonal cluster of three-dimensional(3D)magnetically suspended wheels(MSWs).The mathematical model for the satellite incorp...This paper proposes an attitude control strategy for a flexible satellite equipped with an orthogonal cluster of three-dimensional(3D)magnetically suspended wheels(MSWs).The mathematical model for the satellite incorporating flexible appendages and an orthogonal cluster of magnetically suspended reaction wheel actuators is initially developed.After that,an adaptive attitude controller is designed with a switching surface of variable structure,an adaptive law for estimating inertia matrix uncertainty,and a fuzzy disturbance observer for estimating disturbance torques.Additionally,a Moore-Penrose-based steering law is proposed to derive the tilt angle commands of the orthogonal configuration of the 3D MSW to follow the designed control signal.Finally,numerical simulations are presented to validate the effectiveness of the proposed control strategy.展开更多
Background:Traditional imaging approaches to keratoconus(KCN)have thus far failed to produce a standardized approach for diagnosis.While many diagnostic modalities and metrics exist,none have proven robust enough to b...Background:Traditional imaging approaches to keratoconus(KCN)have thus far failed to produce a standardized approach for diagnosis.While many diagnostic modalities and metrics exist,none have proven robust enough to be considered a gold standard.This study aims to introduce novel metrics to differentiate between KCN and healthy corneas using three-dimensional(3D)measurements of surface area and volume.Methods:This retrospective observational study examined KCN patients along with healthy control patients between the ages of 20 and 79 years old at the University of Maryland,Baltimore.The selected patients underwent a nine-line raster scan anterior segment optical coherence tomography(AS-OCT).ImageJ was used to determine the central 6 mm of each image and each corneal image was then divided into six 1 mm segments.Free-D software was then used to render the nine different images into a 3D model to calculate corneal surface area and volume.A two-tailed Mann-Whitney test was used to assess statistical significance when comparing these subsets.Results:Thirty-three eyes with KCN,along with 33 healthy control,were enrolled.There were statistically significant differences between the healthy and KCN groups in the metric of anterior corneal surface area(13.927 vs.13.991 mm^(2),P=0.046),posterior corneal surface area(14.045 vs.14.173 mm^(2),P<0.001),and volume(8.430 vs.7.773 mm3,P<0.001)within the central 6 mm.Conclusions:3D corneal models derived from AS-OCT can be used to measure anterior corneal surface area,posterior corneal surface area,and corneal volume.All three parameters are statistically different between corneas with KCN and healthy corneas.Further study and application of these parameters may yield new methodologies for the detection of KCN.展开更多
The gravity inversion is to restore genetic density distribution of the underground target to be explored for explaining the internal structure and distribution of the Earth.In this paper,we propose a new 3D gravity i...The gravity inversion is to restore genetic density distribution of the underground target to be explored for explaining the internal structure and distribution of the Earth.In this paper,we propose a new 3D gravity inversion method based on 3D U-Net++.Compared with two-dimensional gravity inversion,three-dimensional(3D)gravity inversion can more precisely describe the density distribution of underground space.However,conventional 3D gravity inversion method input is two-dimensional,the input and output of the network proposed in our method are three-dimensional.In the training stage,we design a large number of diversifi ed simulation model-data pairs by using the random walk method to improve the generalization ability of the network.In the test phase,we verify the network performance by using the model-data pairs generated by the simulation.To further illustrate the eff ectiveness of the algorithm,we apply the method to the inversion of the San Nicolas mining area,and the inversion results are basically consistent with the borehole measurement results.Moreover,the results of the 3D U-Net++inversion and the 3D U-Net inversion are compared.The density models of the 3D U-Net++inversion have higher resolution,more concentrated inversion results,and a clearer boundary of the density model.展开更多
Adhesions between different cells and extracellular matrix have been studied extensively in vitro, but little is known about their functions in testicular tissue counterparts. Spermatogonia and their companion somatic...Adhesions between different cells and extracellular matrix have been studied extensively in vitro, but little is known about their functions in testicular tissue counterparts. Spermatogonia and their companion somatic cells maintain a close association throughout spermatogenesis and this association is necessary for normal spermatogenesis. In order to keep the relative integrity of the testicular tissues, and to detect the development in vitro, culture testicular tissues in a three- dimensional （3D） agarose matrix was examined. Testicular tissues isolated from 6.5 d postpartum （dpp） mouse were cultured on the top of the matrix for 26 d with a medium height up to 4/5 of the 3D agarose matrix. The results showed that in this 3D culture environment, each type of testicular cells kept the same structure, localization and function as in vivo and might be more biologically relevant to living organisms. After culture, germ cell marker VASA and meiosis markers DAZL and SCP3 showed typical positive analysed by immunofluorescence staining and RT-PCR. It demonstrated that this 3D culture system was able to maintain the number of germ cells and promote the meiosis initiation of male germ cells.展开更多
An improved three-dimensional （3-D） experimental visualization methodology is presented tor evaluating the fracture mechanisms of ferritic stainless steels by in-situ tensile testing with an environmental scanning e...An improved three-dimensional （3-D） experimental visualization methodology is presented tor evaluating the fracture mechanisms of ferritic stainless steels by in-situ tensile testing with an environmental scanning electron microscope （ESEM）. The samples were machined with a radial notched shape and a sloped surface. Both planar surface deformation and sloping surface deformation-induced microvoids were observed during dynamic tension experiments, where a greater amount of information could be obtained from the sloping surface. The results showed that microvoids formed at the grain boundaries of highly elongated large grains. The microvoids nucleated in the severely deformed regions grew nearly parallel to the tensile axis, predominantly along the grain boundaries. The microvoids nucleated at the interface of particles and the matrix did not propagate due to the high plasticity of the matrix. The large microvoids propagated and showed a zigzag shape along the grain boundaries,seemingly a consequence of the fracture of the slip bands caused by dislocation pile-ups. The final failure took place due to the reduction of the load-beating area.展开更多
Upon the conservation of mass, momentum and energy, volume fraction and surface penetrative rate were employed to modify the conservative equations to simulate the effect of blockages on fluid flows and heat transfer....Upon the conservation of mass, momentum and energy, volume fraction and surface penetrative rate were employed to modify the conservative equations to simulate the effect of blockages on fluid flows and heat transfer. These equations were solved numerically with the finite differential method and the primitive variable approach. This method uses staggered grid and pressure correction schemes. A computer code FASTOR3D integrated the aforementioned algorithm. The preliminary results have been compared with conventional benchmark solutions. With auxiliary software DV, the numerical results were visualized in colorful images to demonstrate the variation of flow patterns and temperature profiles during the transient process. The results of the simulation code for the fluid flows and heat transfer in the sodium pool of a fast breeder reactor are acceptable.展开更多
基金supported by the National Science Foundation of China(Nos.81373970,81773902,81973484,and 32171402)the National College Students Innovation and Entrepreneurship Training Program(No.201810315019)+4 种基金the Postgraduate Research and Practice Innovation Program of Jiangsu Province(Nos.SJCX21_0712 and KYCX23_2052)the Scientific Research Project of Jiangsu Provincial Association of Traditional Chinese Medicine(No.XYLD2024013)the Youth Scientific Research Project of Jiangyin Municipal Health Commission(No.Q202402)the Natural Science Foundation Project of Nanjing University of Chinese Medicine(No.XZR2024173)the Jiangyin Science and Technology Innovation Special Fund Project(No.JY0603A011014230032PB),China.
文摘Bone repair remains an important target in tissue engineering,making the development of bioactive scaffolds for effective bone defect repair a critical objective.In this study,β-tricalcium phosphate(β-TCP)scaffolds incorporated with processed pyritum decoction(PPD)were fabricated using three-dimensional(3D)printing-assisted freeze-casting.The produced composite scaffolds were evaluated for their mechanical strength,physicochemical properties,biocompatibility,in vitro proangiogenic activity,and in vivo efficacy in repairing rabbit femoral defects.They not only demonstrated excellent physicochemical properties,enhanced mechanical strength,and good biosafety but also significantly promoted the proliferation,migration,and aggregation of pro-angiogenic human umbilical vein endothelial cells(HUVECs).In vivo studies revealed that all scaffold groups facilitated osteogenesis at the bone defect site,with theβ-TCP scaffolds loaded with PPD markedly enhancing the expression of neurogenic locus Notch homolog protein 1(Notch1),vascular endothelial growth factor(VEGF),bone morphogenetic protein-2(BMP-2),and osteopontin(OPN).Overall,the scaffolds developed in this study exhibited strong angiogenic and osteogenic capabilities both in vitro and in vivo.The incorporation of PPD notably promoted the angiogenic-osteogenic coupling,thereby accelerating bone repair,which suggests that PPD is a promising material for bone repair and that the PPD/β-TCP scaffolds hold great potential as a bone graft alternative.
基金We gratefully acknowledge the financial support of the National Natural Science Foundation of China （Grants 51374213 and 51674251）, National Natural Science Fund for Distinguished Young Scholars of China （Grant 51125017）, Science Fund for Creative Research Groups of the National Natural Science Foundation of China （Grant 51421003）, Fund for Innovative Research and Development Group Program of Jiangsu Province （Grant 2014-27）, and the Priority Academic Program Development of Jiangsu Higher Education Institutions （Grant PAPD 2014）.
文摘The heterogeneity of unconventional reservoir rock tremendously affects its hydrofracturing behavior. A visual representation and accurate characterization of the three-dimensional （3D） growth and distribution of hydrofracturing cracks within heterogeneous rocks is of particular use to the design and implementation of hydrofracturing stimulation of unconventional reservoirs. However, because of the difficulties involved in visually representing and quantitatively characterizing a 3D hydrofracturing crack-network, this issue remains a challenge. In this paper, a novel method is proposed for physically visualizing and quantitatively characterizing the 3D hydrofracturing crack-network distributed through a heterogeneous structure based on a natural glutenite sample. This method incorporates X-ray microfocus computed tomography （μCT）, 3D printing models and hydrofracturing triaxial tests to represent visually the heterogeneous structure, and the 3D crack growth and distribution within a transparent rock model during hydrofracturing. The coupled effects of material heterogeneity and confining geostress on the 3D crack initiation and propagation were analyzed. The results indicate that the breakdown pressure of a heterogeneous rock model is significantly affected by material heterogeneity and confining geostress. The measured breakdown pressures of heterogeneous models are apparently different from those predicted by traditional theories. This study helps to elucidate the quantitative visualization and characterization of the mechanism and influencing factors that determine the hydrofracturing crack initiation and propagation in heterogeneous reservoir rocks.
文摘[Significance]In alignment with the national germplasm security strategy,current research efforts are accelerating the adoption of precision breeding in sheep.Within the whole-genome selection,accurate phenotyping of body morphometrics is critical for assessing growth performance and breeding value.Traditional manual measurements are inefficient,prone to human error,and may cause stress to sheep,limiting their suitability for precision sheep management.By summarizing the applications of sheep body size measurement technologies and analyzing their development directions,this paper provides theoretical references and practical guidance for the research and application of non contact sheep body size measurement.[Progress]This review synthesizes progress across three principal methodological paradigms:two-dimensional(2D)image-based techniques,three-dimensional(3D)point cloud-based approaches,and integrated 2D-3D fusion systems.2D methods,employing either handcrafted geometric features or deep learning-based keypoint detector algorithms,are cost-effective and operationally simple but sensitive to variation in imaging conditions and unable to capture critical circumference metrics.3D point-cloud approaches enable precise reconstruction of full animal morphology,supporting comprehensive body-size acquisition with higher accuracy,yet face challenges including high hardware costs,complex data workflows,and sensitivity to posture variability.Hybrid 2D-3D fusion systems combine semantic richness from RGB imagery with geometric completeness from point clouds.Having been effectively validated in other livestock specise,e.g.,cattle and pigs,these fusion systems have demonstrated excellent performance,providing important technical references and practical insights for sheep body size measurement.[Conclusions and Prospects]Firstly,future research should focus on constructing large-scale,high-quality datasets for sheep body size measurement that encompass diverse breeds,growth stages,and environmental conditions,thereby enhancing model robustness and generalization.Secondly,the development of lightweight artificial intelligence models is essential.Techniques such as model compression,quantization,and algorithmic optimization can substantially reduce computational complexity and storage requirements,facilitating deployment in resource-constrained environments.Thirdly,the 3D point cloud processing pipeline should be streamlined to improve the efficiency of data acquisition,filtering,registration,and segmentation,while promoting the integration of low-cost,high-resilience vision systems into practical farming scenarios.Fourthly,specific emphasis should be placed on improving the accuracy of curved-dimensional measurements,such as chest circumference,abdominal circumference,and shank circumference,through advances in pose standardization,refined 3D segmentation strategies,and multimodal data fusion.Finally,the cross-fertilization of sheep body size measurement technologies with analogous methods for other livestock species offers a promising pathway for mutual learning and collaborative innovation,accelerating the industrialization of automated sheep morphometric systems and supporting the development of intelligent,data-driven pasture management practices.
基金supported by the National Key Research and Development Program Young Scientist Project(Grant No.2024YFC2911000)the National Natural Science Foundation of China(Grant No.52474103)the Major Basic Research Project of the Natural Science Foundation of Shandong Province(Grant No.ZR2024ZD22).
文摘Internal structural defects in engineering rock masses vary in size,exhibit complex shapes,and are unevenly distributed.Dominant fractures within a rock mass often play a critical to its mechanical behavior,directly affecting the macromechanical properties and failure modes.These fractures affect the instability and failure of the surrounding rock,significantlyimpacting the overall stability of engineering structures.Herein,sand-powder three-dimensional(3D)printing technology was used to prepare rock-like specimens with internal fracture networks.Triaxial compression testing,post-failure fracture mapping,and fractal dimension analysis of the fracture surfaces were conducted to investigate the effects of dominant fracture angles on the strength and deformation of rocks with internal fracture networks under triaxial stress.The results indicate that the dominant fracture angle has a pronounced effect on the mechanical behavior of rock.With increasing angle,both compressive strength and elastic modulus exhibit an initial decline followed by an increase.Moreover,higher confiningpressure significantlyimproves the compressive strength of fractured rock.This enhancement weakens as the confiningpressure further increases.Moreover,with increasing confiningpressure,the differences between the maximum and minimum values of elastic moduli and lateral strain ratios in fractured rock gradually decrease.Thus,the impact of the dominant fracture angle on rock mass deformation decreases with increasing confiningpressure.This research elucidates the effects of dominant fracture angles on the mechanical and failure properties of complex fractured rock masses and the influenceof the confiningpressure on these relationships.It provides valuable theoretical insights and practical guidance for stability analyses in engineering rock masses.
基金supported by the Postgraduate Research&Practice Innovation Program of Nanjing University of Aeronautics and Astronautics(NUAA)(No.xcxjh20251502)。
文摘Online three-dimensional(3D)path planning in dynamic environments is a fundamental problem for achieving autonomous navigation of unmanned aerial vehicles(UAVs).However,existing methods struggle to model traversable dynamic gaps,resulting in conservative and suboptimal trajectories.To address these challenges,this paper proposes a hierarchical reinforcement learning(RL)framework that integrates global path guidance,local trajectory generation,predictive safety evaluation,and neural network-based decision-making.Specifically,the global planner provides long-term navigation guidance,and the local module then utilizes an improved 3D dynamic window approach(DWA)to generate dynamically feasible candidate trajectories.To enhance safety in dense dynamic scenarios,the algorithm introduces a predictive axis-aligned bounding box(AABB)strategy to model the future occupancy of obstacles,combined with convex hull verification for efficient trajectory safety assessment.Furthermore,a double deep Q-network(DDQN)is employed with structured feature encoding,enabling the neural network to reliably select the optimal trajectory from the candidate set,thereby improving robustness and generalization.Comparative experiments conducted in a high-fidelity simulation environment show that the algorithm outperforms existing algorithms,reducing the average number of collisions to 0.2 while shortening the average task completion time by approximately 15%,and achieving a success rate of 97%.
基金Project supported by the National Natural Science Foundation of China(Nos.12372071 and 12372070)the Aeronautical Science Fund of China(No.2022Z055052001)the Foundation of China Scholarship Council(No.202306830079)。
文摘Currently,there are a limited number of dynamic models available for braided composite plates with large overall motions,despite the incorporation of three-dimensional(3D)braided composites into rotating blade components.In this paper,a dynamic model of 3D 4-directional braided composite thin plates considering braiding directions is established.Based on Kirchhoff's plate assumptions,the displacement variables of the plate are expressed.By incorporating the braiding directions into the constitutive equation of the braided composites,the dynamic model of the plate considering braiding directions is obtained.The effects of the speeds,braiding directions,and braided angles on the responses of the plate with fixed-axis rotation and translational motion,respectively,are investigated.This paper presents a dynamic theory for calculating the deformation of 3D braided composite structures undergoing both translational and rotational motions.It also provides a simulation method for investigating the dynamic behavior of non-isotropic material plates in various applications.
基金supported by grants from the Human Resources Development program (Grant No.20204010600250)the Training Program of CCUS for the Green Growth (Grant No.20214000000500)by the Korea Institute of Energy Technology Evaluation and Planning (KETEP)funded by the Ministry of Trade,Industry,and Energy of the Korean Government (MOTIE).
文摘It is of great importance to obtain precise trace data,as traces are frequently the sole visible and measurable parameter in most outcrops.The manual recognition and detection of traces on high-resolution three-dimensional(3D)models are relatively straightforward but time-consuming.One potential solution to enhance this process is to use machine learning algorithms to detect the 3D traces.In this study,a unique pixel-wise texture mapper algorithm generates a dense point cloud representation of an outcrop with the precise resolution of the original textured 3D model.A virtual digital image rendering was then employed to capture virtual images of selected regions.This technique helps to overcome limitations caused by the surface morphology of the rock mass,such as restricted access,lighting conditions,and shading effects.After AI-powered trace detection on two-dimensional(2D)images,a 3D data structuring technique was applied to the selected trace pixels.In the 3D data structuring,the trace data were structured through 2D thinning,3D reprojection,clustering,segmentation,and segment linking.Finally,the linked segments were exported as 3D polylines,with each polyline in the output corresponding to a trace.The efficacy of the proposed method was assessed using a 3D model of a real-world case study,which was used to compare the results of artificial intelligence(AI)-aided and human intelligence trace detection.Rosette diagrams,which visualize the distribution of trace orientations,confirmed the high similarity between the automatically and manually generated trace maps.In conclusion,the proposed semi-automatic method was easy to use,fast,and accurate in detecting the dominant jointing system of the rock mass.
文摘Liposarcoma is one of the most common soft tissue sarcomas,however,its occurrence rate is still rare compared to other cancers.Due to its rarity,in vitro experiments are an essential approach to elucidate liposarcoma pathobiology.Conventional cell culture-based research(2D cell culture)is still playing a pivotal role,while several shortcomings have been recently under discussion.In vivo,mouse models are usually adopted for pre-clinical analyses with expectations to overcome the issues of 2D cell culture.However,they do not fully recapitulate human dedifferentiated liposarcoma(DDLPS)characteristics.Therefore,three-dimensional(3D)culture systems have been the recent research focus in the cell biology field with the expectation to overcome at the same time the disadvantages of 2D cell culture and in vivo animal models and fill in the gap between them.Given the liposarcoma rarity,we believe that 3D cell culture techniques,including 3D cell cultures/co-cultures,and Patient-Derived tumor Organoids(PDOs),represent a promising approach to facilitate liposarcoma investigation and elucidate its molecular mechanisms and effective therapy development.In this review,we first provide a general overview of 3D cell cultures compared to 2D cell cultures.We then focus on one of the recent 3D cell culture applications,Patient-Derived Organoids(PDOs),summarizing and discussing several PDO methodologies.Finally,we discuss the current and future applications of PDOs to sarcoma,particularly in the field of liposarcoma.
基金supported by the Central Government’s Guidance Fund for Local Science and Technology Development(2024ZY-CGZY-19)。
文摘Observing plants across time and diverse scenes is critical in uncovering plant growth patterns.Classic methods often struggle to observe or measure plants against complex backgrounds and at different growth stages.This highlights the need for a universal approach capable of providing realistic plant visualizations across time and scene.Here,we introduce PlantGaussian,an approach for generating realistic three-dimensional(3D)visualization for plants across time and scenes.It marks one of the first applications of 3D Gaussian splatting techniques in plant science,achieving high-quality visualization across species and growth stages.By integrating the Segment Anything Model(SAM)and tracking algorithms,PlantGaussian overcomes the limitations of classic Gaussian reconstruction techniques in complex planting environments.A new mesh partitioning technique is employed to convert Gaussian rendering results into measurable plant meshes,offering a methodology for accurate 3D plant morphology phenotyping.To support this approach,PlantGaussian dataset is developed,which includes images of four crop species captured under multiple conditions and growth stages.Using only plant image sequences as input,it computes high-fidelity plant visualization models and 3D meshes for 3D plant morphological phenotyping.Visualization results indicate that most plant models achieve a Peak Signal-to-Noise Ratio(PSNR)exceeding 25,outperforming all models including the original 3D Gaussian Splatting and enhanced NeRF.The mesh results indicate an average relative error of 4%between the calculated values and the true measurements.As a generic 3D digital plant model,PlantGaussian will support expansion of plant phenotype databases,ecological research,and remote expert consultations.
基金supported by a grant from the Research Grant Council of Hong Kong Special Administrative Region(Project No.11207724).
文摘The development of digital twins for geotechnical structures necessitates the real-time updates of threedimensional(3D)virtual models(e.g.numerical finite element method(FEM)model)to accurately predict time-varying geotechnical responses(e.g.consolidation settlement)in a 3D spatial domain.However,traditional 3D numerical model updating approaches are computationally prohibitive and therefore difficult to update the 3D responses in real time.To address these challenges,this study proposes a novel machine learning framework called sparse dictionary learning(T-3D-SDL)for real-time updating of time-varying 3D geotechnical responses.In T-3D-SDL,a concerned dataset(e.g.time-varying 3D settlement)is approximated as a linear superposition of dictionary atoms generated from 3D random FEM analyses.Field monitoring data are then used to identify non-trivial atoms and estimate their weights within a Bayesian framework for model updating and prediction.The proposed approach enables the real-time update of temporally varying settlements with a high 3D spatial resolution and quantified uncertainty as field monitoring data evolve.The proposed approach is illustrated using an embankment construction project.The results show that the proposed approach effectively improves settlement predictions along temporal and 3D spatial dimensions,with minimal latency(e.g.within minutes),as monitoring data appear.In addition,the proposed approach requires only a reasonably small number of 3D FEM model evaluations,avoids the use of widely adopted yet often criticized surrogate models,and effectively addresses the limitations(e.g.computational inefficiency)of existing 3D model updating approaches.
基金supported by the Hainan Provincial Natural Science Foundation of China(Grant No.525QN342)the Scientific Research Foundation of Hainan Tropical Ocean University(Grant No.RHDRC202301).
文摘We theoretically investigate the extended Bose-Hubbard model using a three-dimensional cubic lattice.In the framework of the dynamical Gutzwiller mean-field theory,we identify a checkerboard supersolid phase.By considering the repulsive interactions between next-nearest-neighbor lattice sites,we further discover an exotic type of supersolid state,whose site occupancies show a stereoscopically arrayed and staggered distribution rather than checkerboard ordering.Intriguingly,if the physical observations of two neighboring layers were superimposed,they would give rise to a checkerboard configuration.This novel structure is convincingly induced by the simultaneous existence of nearest-neighbor and nextnearest-neighbor interactions.We also identify arrayed stripes in the ground state,as well as arrayed holes in the pattern of occupancies.
基金supported by the National Key R&D Program of China(No.2023YFC3081200)the National Natural Science Foundation of China(No.42077264)the Scientific Research Project of PowerChina Huadong Engineering Corporation Limited(HDEC-2022-0301).
文摘Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results cannot be fed back to users timely.To address this issue,we proposed a human-machine interaction(HMI)method for discontinuity mapping.Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments.For this,a regular cube was selected to illustrate the workflows:(1)point cloud was acquired using remote sensing;(2)the HMI method was employed to select reference points and angle thresholds to detect group discontinuity;(3)individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm;and(4)the orientation of each discontinuity was measured based on a plane fitting algorithm.The method was applied to a well-studied highway road cut and a complex natural slope.The consistency of the computational results with field measurements demonstrates its good accuracy,and the average error in the dip direction and dip angle for both cases was less than 3.Finally,the computational time of the proposed method was compared with two other popular algorithms,and the reduction in computational time by tens of times proves its high computational efficiency.This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.
基金funded by the project supported by the Heilongjiang Provincial Natural Science Foundation of China(Grant Number LH2022F030).
文摘3D model classification has emerged as a significant research focus in computer vision.However,traditional convolutional neural networks(CNNs)often struggle to capture global dependencies across both height and width dimensions simultaneously,leading to limited feature representation capabilities when handling complex visual tasks.To address this challenge,we propose a novel 3D model classification network named ViT-GE(Vision Transformer with Global and Efficient Attention),which integrates Global Grouped Coordinate Attention(GGCA)and Efficient Channel Attention(ECA)mechanisms.Specifically,the Vision Transformer(ViT)is employed to extract comprehensive global features from multi-view inputs using its self-attention mechanism,effectively capturing 3D shape characteristics.To further enhance spatial feature modeling,the GGCA module introduces a grouping strategy and global context interactions.Concurrently,the ECA module strengthens inter-channel information flow,enabling the network to adaptively emphasize key features and improve feature fusion.Finally,a voting mechanism is adopted to enhance classification accuracy,robustness,and stability.Experimental results on the ModelNet10 dataset demonstrate that our method achieves a classification accuracy of 93.50%,validating its effectiveness and superior performance.
基金the National Natural Science Foundation of China(No.61973210)the Interdisciplinary Program of Shanghai Jiao Tong University(Nos.YG2019ZDA17 and ZH2018QNB23)+1 种基金the Shanghai Advanced Technology Joint Research Fund(No.USCAST2020-7)the Shenzhen Science and Technology Commission Key Technology Project(No.JSGG20200701095003006)。
文摘The introduction of path planning and visual navigation in vascular interventional surgery can provide an intuitive reference and guidance for doctors.In this study,based on the preprocessing results of vessel skeleton extraction and stenosis diagnosis in X-ray coronary angiography images,clustering is used to determine the connectivity of the intersection points,and then the improved Dijkstra algorithm is used to automatically plan the surgical path.On this basis,the intermediate point is introduced to piecewise correct the path and improve the accuracy of the system.Finally,the epipolar constrained inverse projection transformation is used to reconstruct the coronary artery 3D model,and the optimal path is marked to achieve a multi-angle 3D visual navigation.Clinical experimental results show that compared with the traditional Dijkstra algorithm,the improved method can reduce the need for intermediate points,which improves computational efficiency,and the average error of manual calibration path is reduced to 4%of that before overall optimization.The results of 3D reconstruction and reprojection further qualitatively and quantitatively verify the effectiveness of the whole scheme.
基金Project supported by the National Natural Science Foundation of China(Nos.W2433004 and 12472015)the Research Fund of the State Key Laboratory of Mechanics and Control of Mechanical Structures(Nanjing University of Aeronautics and Astronautics)(No.MCMS-I-0122K01).
文摘This paper proposes an attitude control strategy for a flexible satellite equipped with an orthogonal cluster of three-dimensional(3D)magnetically suspended wheels(MSWs).The mathematical model for the satellite incorporating flexible appendages and an orthogonal cluster of magnetically suspended reaction wheel actuators is initially developed.After that,an adaptive attitude controller is designed with a switching surface of variable structure,an adaptive law for estimating inertia matrix uncertainty,and a fuzzy disturbance observer for estimating disturbance torques.Additionally,a Moore-Penrose-based steering law is proposed to derive the tilt angle commands of the orthogonal configuration of the 3D MSW to follow the designed control signal.Finally,numerical simulations are presented to validate the effectiveness of the proposed control strategy.
文摘Background:Traditional imaging approaches to keratoconus(KCN)have thus far failed to produce a standardized approach for diagnosis.While many diagnostic modalities and metrics exist,none have proven robust enough to be considered a gold standard.This study aims to introduce novel metrics to differentiate between KCN and healthy corneas using three-dimensional(3D)measurements of surface area and volume.Methods:This retrospective observational study examined KCN patients along with healthy control patients between the ages of 20 and 79 years old at the University of Maryland,Baltimore.The selected patients underwent a nine-line raster scan anterior segment optical coherence tomography(AS-OCT).ImageJ was used to determine the central 6 mm of each image and each corneal image was then divided into six 1 mm segments.Free-D software was then used to render the nine different images into a 3D model to calculate corneal surface area and volume.A two-tailed Mann-Whitney test was used to assess statistical significance when comparing these subsets.Results:Thirty-three eyes with KCN,along with 33 healthy control,were enrolled.There were statistically significant differences between the healthy and KCN groups in the metric of anterior corneal surface area(13.927 vs.13.991 mm^(2),P=0.046),posterior corneal surface area(14.045 vs.14.173 mm^(2),P<0.001),and volume(8.430 vs.7.773 mm3,P<0.001)within the central 6 mm.Conclusions:3D corneal models derived from AS-OCT can be used to measure anterior corneal surface area,posterior corneal surface area,and corneal volume.All three parameters are statistically different between corneas with KCN and healthy corneas.Further study and application of these parameters may yield new methodologies for the detection of KCN.
基金supported by the Key Laboratory of Geological Survey and Evaluation of Ministry of Education (China University of Geosciences)(No. GLAB2020ZR13)
文摘The gravity inversion is to restore genetic density distribution of the underground target to be explored for explaining the internal structure and distribution of the Earth.In this paper,we propose a new 3D gravity inversion method based on 3D U-Net++.Compared with two-dimensional gravity inversion,three-dimensional(3D)gravity inversion can more precisely describe the density distribution of underground space.However,conventional 3D gravity inversion method input is two-dimensional,the input and output of the network proposed in our method are three-dimensional.In the training stage,we design a large number of diversifi ed simulation model-data pairs by using the random walk method to improve the generalization ability of the network.In the test phase,we verify the network performance by using the model-data pairs generated by the simulation.To further illustrate the eff ectiveness of the algorithm,we apply the method to the inversion of the San Nicolas mining area,and the inversion results are basically consistent with the borehole measurement results.Moreover,the results of the 3D U-Net++inversion and the 3D U-Net inversion are compared.The density models of the 3D U-Net++inversion have higher resolution,more concentrated inversion results,and a clearer boundary of the density model.
基金supported by the National Natural Science Foundation of China(31272518)the program for the New Century Excellent Talents of Ministry of Education of China(NCET-09-0654)+1 种基金the Doctoral Fund of Ministry of Education of P.R.China(RFDP,20120204110030)the Fundamental Research Funds for the Central Universities,China(QN2011012)
文摘Adhesions between different cells and extracellular matrix have been studied extensively in vitro, but little is known about their functions in testicular tissue counterparts. Spermatogonia and their companion somatic cells maintain a close association throughout spermatogenesis and this association is necessary for normal spermatogenesis. In order to keep the relative integrity of the testicular tissues, and to detect the development in vitro, culture testicular tissues in a three- dimensional （3D） agarose matrix was examined. Testicular tissues isolated from 6.5 d postpartum （dpp） mouse were cultured on the top of the matrix for 26 d with a medium height up to 4/5 of the 3D agarose matrix. The results showed that in this 3D culture environment, each type of testicular cells kept the same structure, localization and function as in vivo and might be more biologically relevant to living organisms. After culture, germ cell marker VASA and meiosis markers DAZL and SCP3 showed typical positive analysed by immunofluorescence staining and RT-PCR. It demonstrated that this 3D culture system was able to maintain the number of germ cells and promote the meiosis initiation of male germ cells.
文摘An improved three-dimensional （3-D） experimental visualization methodology is presented tor evaluating the fracture mechanisms of ferritic stainless steels by in-situ tensile testing with an environmental scanning electron microscope （ESEM）. The samples were machined with a radial notched shape and a sloped surface. Both planar surface deformation and sloping surface deformation-induced microvoids were observed during dynamic tension experiments, where a greater amount of information could be obtained from the sloping surface. The results showed that microvoids formed at the grain boundaries of highly elongated large grains. The microvoids nucleated in the severely deformed regions grew nearly parallel to the tensile axis, predominantly along the grain boundaries. The microvoids nucleated at the interface of particles and the matrix did not propagate due to the high plasticity of the matrix. The large microvoids propagated and showed a zigzag shape along the grain boundaries,seemingly a consequence of the fracture of the slip bands caused by dislocation pile-ups. The final failure took place due to the reduction of the load-beating area.
文摘Upon the conservation of mass, momentum and energy, volume fraction and surface penetrative rate were employed to modify the conservative equations to simulate the effect of blockages on fluid flows and heat transfer. These equations were solved numerically with the finite differential method and the primitive variable approach. This method uses staggered grid and pressure correction schemes. A computer code FASTOR3D integrated the aforementioned algorithm. The preliminary results have been compared with conventional benchmark solutions. With auxiliary software DV, the numerical results were visualized in colorful images to demonstrate the variation of flow patterns and temperature profiles during the transient process. The results of the simulation code for the fluid flows and heat transfer in the sodium pool of a fast breeder reactor are acceptable.
