With respect to oceanic fluid dynamics,certain models have appeared,e.g.,an extended time-dependent(3+1)-dimensional shallow water wave equation in an ocean or a river,which we investigate in this paper.Using symbolic...With respect to oceanic fluid dynamics,certain models have appeared,e.g.,an extended time-dependent(3+1)-dimensional shallow water wave equation in an ocean or a river,which we investigate in this paper.Using symbolic computation,we find out,on one hand,a set of bilinear auto-Backlund transformations,which could connect certain solutions of that equation with other solutions of that equation itself,and on the other hand,a set of similarity reductions,which could go from that equation to a known ordinary differential equation.The results in this paper depend on all the oceanic variable coefficients in that equation.展开更多
This paper proposes a novel cargo loading algorithm applicable to automated conveyor-type loading systems.The algorithm offers improvements in computational efficiency and robustness by utilizing the concept of discre...This paper proposes a novel cargo loading algorithm applicable to automated conveyor-type loading systems.The algorithm offers improvements in computational efficiency and robustness by utilizing the concept of discrete derivatives and introducing logistics-related constraints.Optional consideration of the rotation of the cargoes was made to further enhance the optimality of the solutions,if possible to be physically implemented.Evaluation metrics were developed for accurate evaluation and enhancement of the algorithm’s ability to efficiently utilize the loading space and provide a high level of dynamic stability.Experimental results demonstrate the extensive robustness of the proposed algorithm to the diversity of cargoes present in Business-to-Consumer environments.This study contributes practical advancements in both cargo loading optimization and automation of the logistics industry,with potential applications in last-mile delivery services,warehousing,and supply chain management.展开更多
Lie symmetry analysis is applied to a(3+1)-dimensional combined potential Kadomtsev-Petviashvili equation with B-type Kadomtsev-Petviashvili equation(pKP-BKP equation)and the corresponding similarity reduction equatio...Lie symmetry analysis is applied to a(3+1)-dimensional combined potential Kadomtsev-Petviashvili equation with B-type Kadomtsev-Petviashvili equation(pKP-BKP equation)and the corresponding similarity reduction equations are obtained with the different infinitesimal generators.Invariant solutions with arbitrary functions and constants for the(3+1)-dimensional pKP-BKP equation,including the lump solution,the periodic-lump solution,the two-kink solution,the breather solution and the lump-two-kink solution,have been studied analytically and graphically.展开更多
To better understand the biological structure of bigeye tuna(Thunnus obesus),albacore tuna(Thunnus alalunga),and longtail tuna(Thunnus tonggol),computed tomography(CT)was used to scan their bodies,and the data are pro...To better understand the biological structure of bigeye tuna(Thunnus obesus),albacore tuna(Thunnus alalunga),and longtail tuna(Thunnus tonggol),computed tomography(CT)was used to scan their bodies,and the data are processed by Mimics software.The skeleton,swim bladder,and muscle of the three tuna species are reconstructed in three dimensions.The surface area and volume of the corresponding parts are measured.The results show that the surface areas of the skeleton of longtail tuna,bigeye tuna,albacore tuna accounted for 28.18%,37.34%,33.45%of their whole body surface areas respectively;the surface areas of swim bladder accounted for 0,2.06%,2.72% of their whole body surface area respectively;and the surface areas of muscle accounted for 71.82%,60.6%,63.83%of their whole body surface areas respectively.And the volumes of skeleton accounted for 28.18%,8.05%,3.84%,the volumes of swim bladder accounted for 0,3.44%,0.92%,and the volumes of muscle accounted for 94.84%,88.51%,95.24%of their body volumes respectively.The swim bladder of the longtail tuna has degenerated,while that of the bigeye tuna is conical,exhibiting the highest volume proportion among the three species.In contrast,the swim bladder of the albacore tuna is both flat and elongated,resembling an arc.Additionally,the surface area and the volume of the bigeye tuna’s swim bladder differ signifi-cantly from those of the albacore tuna.Regarding skeletal and muscular structures,the bigeye tuna has the highest skeletal volume proportion(8.05%),whereas the albacore tuna exhibits the highest muscle volume proportion(95.24%).These morphological differences are closely associated with their respective habitats.This study demonstrates the potential of CT technology in fish morphological research,providing a reliable,non-invasive method for analyzing internal structures,quantifying organ characteristics and improving the accuracy of acoustic stock assessment.展开更多
The impact of heavy reduction on dendritic morphology was explored by combining experimental research and numerical simulation in metallurgy,including a detailed three-dimensional(3D)analysis and reconstruction of den...The impact of heavy reduction on dendritic morphology was explored by combining experimental research and numerical simulation in metallurgy,including a detailed three-dimensional(3D)analysis and reconstruction of dendritic solidification structures.Combining scanning electron microscopy and energy-dispersive scanning analysis and ANSYS simulation,the high-precision image processing software Mimics Research was utilized to conduct the extraction of dendritic morphologies.Reverse engineering software NX Imageware was employed for the 3D reconstruction of two-dimensional dendritic morphologies,restoring the dendritic characteristics in three-dimensional space.The results demonstrate that in a two-dimensional plane,dendrites connect with each other to form irregularly shaped“ring-like”structures.These dendrites have a thickness greater than 0.1 mm along the Z-axis direction,leading to the envelopment of molten steel by dendrites in a 3D space of at least 0.1 mm.This results in obstructed flow,confirming the“bridging”of dendrites in three-dimensional space,resulting in a tendency for central segregation.Dense and dispersed tiny dendrites,under the influence of heat flow direction,interconnect and continuously grow,gradually forming primary and secondary dendrites in three-dimensional space.After the completion of dendritic solidification and growth,these microdendrites appear dense and dispersed on the two-dimensional plane,providing the nuclei for the formation of new dendrites.When reduction occurs at a solid fraction of 0.46,there is a noticeable decrease in dendritic spacing,resulting in improved central segregation.展开更多
This article proposes a three-dimensional light field reconstruction method based on neural radiation field(NeRF)called Infrared NeRF for low resolution thermal infrared scenes.Based on the characteristics of the low ...This article proposes a three-dimensional light field reconstruction method based on neural radiation field(NeRF)called Infrared NeRF for low resolution thermal infrared scenes.Based on the characteristics of the low resolution thermal infrared imaging,various optimizations have been carried out to improve the speed and accuracy of thermal infrared 3D reconstruction.Firstly,inspired by Boltzmann's law of thermal radiation,distance is incorporated into the NeRF model for the first time,resulting in a nonlinear propagation of a single ray and a more accurate description of the physical property that infrared radiation intensity decreases with increasing distance.Secondly,in terms of improving inference speed,based on the phenomenon of high and low frequency distribution of foreground and background in infrared images,a multi ray non-uniform light synthesis strategy is proposed to make the model pay more attention to foreground objects in the scene,reduce the distribution of light in the background,and significantly reduce training time without reducing accuracy.In addition,compared to visible light scenes,infrared images only have a single channel,so fewer network parameters are required.Experiments using the same training data and data filtering method showed that,compared to the original NeRF,the improved network achieved an average improvement of 13.8%and 4.62%in PSNR and SSIM,respectively,while an average decreases of 46%in LPIPS.And thanks to the optimization of network layers and data filtering methods,training only takes about 25%of the original method's time to achieve convergence.Finally,for scenes with weak backgrounds,this article improves the inference speed of the model by 4-6 times compared to the original NeRF by limiting the query interval of the model.展开更多
This paper presents a novel method for reconstructing a highly accurate 3D nose model of the human from 2D images and pre-marked landmarks based on algorithmic methods.The study focuses on the reconstruction of a 3D n...This paper presents a novel method for reconstructing a highly accurate 3D nose model of the human from 2D images and pre-marked landmarks based on algorithmic methods.The study focuses on the reconstruction of a 3D nose model tailored for applications in healthcare and cosmetic surgery.The approach leverages advanced image processing techniques,3D Morphable Models(3DMM),and deformation techniques to overcome the limita-tions of deep learning models,particularly addressing the interpretability issues commonly encountered in medical applications.The proposed method estimates the 3D coordinates of landmark points using a 3D structure estimation algorithm.Sub-landmarks are extracted through image processing techniques and interpolation.The initial surface is generated using a 3DMM,though its accuracy remains limited.To enhance precision,deformation techniques are applied,utilizing the coordinates of 76 identified landmarks and sub-landmarks.The resulting 3D nose model is constructed based on algorithmic methods and pre-marked landmarks.Evaluation of the 3D model is conducted by comparing landmark distances and shape similarity with expert-determined ground truth on 30 Vietnamese volunteers aged 18 to 47,all of whom were either preparing for or required nasal surgery.Experimental results demonstrate a strong agreement between the reconstructed 3D model and the ground truth.The method achieved a mean landmark distance error of 0.631 mm and a shape error of 1.738 mm,demonstrating its potential for medical applications.展开更多
This study aims to develop a high-precision and cost-efficient method for the threedimensional reconstruction of large particles in natural gravel and blasted rock fragments,utilizing Structure from Motion(SfM)and Mul...This study aims to develop a high-precision and cost-efficient method for the threedimensional reconstruction of large particles in natural gravel and blasted rock fragments,utilizing Structure from Motion(SfM)and Multi-View Stereo(MVS)techniques.The proposed approach was applied to characterize the three-dimensional morphology of rockfill dam materials at a real construction site.Particle shape was quantitatively analyzed using shape indices of sphericity,convexity,and angularity.The predominant morphology of natural gravel is characterized as slightly elongated and slightly flat,while rock fragments are slightly elongated and not flat.Probability density distributions of shape indices follow a skewed normal distribution:sphericity and convexity show leftward skewness,whereas angularity is right-skewed.Skewness parameters of sphericity and angularity are consistent between natural gravel and blasted rock fragments,indicating comparable shape asymmetry.Convexity skewness is significantly higher in natural gravel compared to rock fragments,by approximately an order of magnitude.The relationship between size and particle shape shows that form ratios and associated shape descriptors change linearly with the logarithm of size;larger particles approach spherical or cubic forms.The innovative measurements contribute to the particle shape data set of rockfill dam materials,providing valuable insights into the three-dimensional and statistical morphological characteristics of relatively large particles in natural gravel and blasted rock fragments.This approach enhances understanding of particle morphology's impact on the mechanical behavior of granular materials.展开更多
Optical three-dimensional(3D)measurement is a critical tool in micro-nano manufacturing,the automotive industry,and medical technology due to its nondestructive nature,high precision,and sensitivity.However,passive li...Optical three-dimensional(3D)measurement is a critical tool in micro-nano manufacturing,the automotive industry,and medical technology due to its nondestructive nature,high precision,and sensitivity.However,passive light field system still requires a refractive primary lens to collect light of the scene,and structured light can not work well with the highly refractive object.Meta-optics,known for being lightweight,compact,and easily integrable,has enabled advancements in passive metalens-array light fields and active structured light techniques.Here,we propose and experimentally validate a novel 3D measurement metasystem.It features a transmitting metasurface generating chromatic line focuses as depth markers and a symmetrically arranged receiving metasurface collecting depth-dependent spectral responses.A lightweight,physically interpretable algorithm processes these data to yield high-precision depth information efficiently.Experiments on metallic and wafer materials demonstrate a depth accuracy of±20μm and lateral accuracy of±10μm.This single-layer optical metasystem,characterized by simplicity,micro-level accuracy,easy installation and scalability,shows potential for diverse applications,including process control,surface morphology analysis,and production measurement.展开更多
Research on reconstructing imperfect faces is a challenging task.In this study,we explore a data-driven approach using a pre-trained MICA(MetrIC fAce)model combined with 3D printing to address this challenge.We propos...Research on reconstructing imperfect faces is a challenging task.In this study,we explore a data-driven approach using a pre-trained MICA(MetrIC fAce)model combined with 3D printing to address this challenge.We propose a training strategy that utilizes the pre-trained MICA model and self-supervised learning techniques to improve accuracy and reduce the time needed for 3D facial structure reconstruction.Our results demonstrate high accuracy,evaluated by the geometric loss function and various statistical measures.To showcase the effectiveness of the approach,we used 3D printing to create a model that covers facial wounds.The findings indicate that our method produces a model that fits well and achieves comprehensive 3D facial reconstruction.This technique has the potential to aid doctors in treating patients with facial injuries.展开更多
Efficient three-dimensional(3D)building reconstruction from drone imagery often faces data acquisition,storage,and computational challenges because of its reliance on dense point clouds.In this study,we introduced a n...Efficient three-dimensional(3D)building reconstruction from drone imagery often faces data acquisition,storage,and computational challenges because of its reliance on dense point clouds.In this study,we introduced a novel method for efficient and lightweight 3D building reconstruction from drone imagery using line clouds and sparse point clouds.Our approach eliminates the need to generate dense point clouds,and thus significantly reduces the computational burden by reconstructing 3D models directly from sparse data.We addressed the limitations of line clouds for plane detection and reconstruction by using a new algorithm.This algorithm projects 3D line clouds onto a 2D plane,clusters the projections to identify potential planes,and refines them using sparse point clouds to ensure an accurate and efficient model reconstruction.Extensive qualitative and quantitative experiments demonstrated the effectiveness of our method,demonstrating its superiority over existing techniques in terms of simplicity and efficiency.展开更多
BACKGROUND Gastric cancer(GC)remains a significant global health challenge,with high incidence and mortality rates.Neoadjuvant chemotherapy is increasingly used to improve surgical outcomes and long-term survival in a...BACKGROUND Gastric cancer(GC)remains a significant global health challenge,with high incidence and mortality rates.Neoadjuvant chemotherapy is increasingly used to improve surgical outcomes and long-term survival in advanced cases.However,individual responses to treatment vary widely,and current imaging methods often fall short in accurately predicting efficacy.Advanced imaging techniques,such as computed tomography(CT)3D reconstruction and texture analysis,offer potential for more precise assessment of therapeutic response.AIM To explore the application value of CT 3D reconstruction volume change rate,texture feature analysis,and visual features in assessing the efficacy of neoadjuvant chemotherapy for advanced GC.METHODS A retrospective analysis was conducted on the clinical and imaging data of 97 patients with advanced GC who received S-1 plus Oxaliplatin combined chemotherapy regimen neoadjuvant chemotherapy from January 2022 to March 2024.CT texture feature analysis was performed using MaZda software,and ITK-snap software was used to measure the tumor volume change rate before and after chemotherapy.CT visual features were also evaluated.Using postoperative pathological tumor regression grade(TRG)as the gold standard,the correlation between various indicators and chemotherapy efficacy was analyzed,and a predictive model was constructed and internally validated.RESULTS The minimum misclassification rate of texture features in venous phase CT images(7.85%)was lower than in the arterial phase(13.92%).The volume change rate in the effective chemotherapy group(75.20%)was significantly higher than in the ineffective group(41.75%).There was a strong correlation between volume change rate and TRG grade(r=-0.886,P<0.001).Multivariate analysis showed that gastric wall peristalsis(OR=0.286)and thickness change rate≥40%(OR=0.265)were independent predictive factors.Receiver operating characteristic curve analysis indicated that the volume change rate[area under the curve(AUC)=0.885]was superior to the CT visual feature model(AUC=0.795).When the cutoff value was 82.56%,the sensitivity and specificity were 85.62%and 96.45%,respectively.CONCLUSION The CT 3D reconstruction volume change rate can serve as a preferred quantitative indicator for evaluating the efficacy of neoadjuvant chemotherapy in GC.Combining it with a CT visual feature predictive model can further improve the accuracy of efficacy evaluation.展开更多
Photomechanics is a crucial branch of solid mechanics.The localization of point targets constitutes a fundamental problem in optical experimental mechanics,with extensive applications in various missions of unmanned a...Photomechanics is a crucial branch of solid mechanics.The localization of point targets constitutes a fundamental problem in optical experimental mechanics,with extensive applications in various missions of unmanned aerial vehicles.Localizing moving targets is crucial for analyzing their motion characteristics and dynamic properties.Reconstructing the trajectories of points from asynchronous cameras is a significant challenge.It encompasses two coupled sub-problems:Trajectory reconstruction and camera synchronization.Present methods typically address only one of these sub-problems individually.This paper proposes a 3D trajectory reconstruction method for point targets based on asynchronous cameras,simultaneously solving both sub-problems.Firstly,we extend the trajectory intersection method to asynchronous cameras to resolve the limitation of traditional triangulation that requires camera synchronization.Secondly,we develop models for camera temporal information and target motion,based on imaging mechanisms and target dynamics characteristics.The parameters are optimized simultaneously to achieve trajectory reconstruction without accurate time parameters.Thirdly,we optimize the camera rotations alongside the camera time information and target motion parameters,using tighter and more continuous constraints on moving points.The reconstruction accuracy is significantly improved,especially when the camera rotations are inaccurate.Finally,the simulated and real-world experimental results demonstrate the feasibility and accuracy of the proposed method.The real-world results indicate that the proposed algorithm achieved a localization error of 112.95 m at an observation distance range of 15-20 km.展开更多
We present a grid-growth method to reconstruct 3D rock joints with arbitrary joint roughness and persistence.In the first step of this workflow,the joint model is divided into uniform grids.Then by adjusting the posit...We present a grid-growth method to reconstruct 3D rock joints with arbitrary joint roughness and persistence.In the first step of this workflow,the joint model is divided into uniform grids.Then by adjusting the positions of the grids,the joint morphology can be modified to construct models with desired joint roughness and persistence.Accordingly,numerous joint models with different joint roughness and persistence were built.The effects of relevant parameters(such as the number,height,slope of asperities,and the number,area of rock bridges)on the joint roughness coefficient(JRC)and joint persistence were investigated.Finally,an artificially split joint was reconstructed using the method,and the method's accuracy was evaluated by comparing the JRC of the models with that of the artificially split joint.The results showed that the proposed method can effectively control the JRC of joint models by adjusting the number,height,and slope of asperities.The method can also modify the joint persistence of joint models by adjusting the number and area of rock bridges.Additionally,the JRC of models obtained by our method agrees with that of the artificially split surface.Overall,the method demonstrated high accuracy for 3D rock joint reconstruction.展开更多
Neural organoids and confocal microscopy have the potential to play an important role in microconnectome research to understand neural patterns.We present PLayer,a plug-and-play embedded neural system,which demonstrat...Neural organoids and confocal microscopy have the potential to play an important role in microconnectome research to understand neural patterns.We present PLayer,a plug-and-play embedded neural system,which demonstrates the utilization of sparse confocal microscopy layers to interpolate continuous axial resolution.With an embedded system focused on neural network pruning,image scaling,and post-processing,PLayer achieves high-performance metrics with an average structural similarity index of 0.9217 and a peak signal-to-noise ratio of 27.75 dB,all within 20 s.This represents a significant time saving of 85.71%with simplified image processing.By harnessing statistical map estimation in interpolation and incorporating the Vision Transformer–based Restorer,PLayer ensures 2D layer consistency while mitigating heavy computational dependence.As such,PLayer can reconstruct 3D neural organoid confocal data continuously under limited computational power for the wide acceptance of fundamental connectomics and pattern-related research with embedded devices.展开更多
This paper explores the key techniques and challenges in dynamic scene reconstruction with neural radiance fields(NeRF).As an emerging computer vision method,the NeRF has wide application potential,especially in excel...This paper explores the key techniques and challenges in dynamic scene reconstruction with neural radiance fields(NeRF).As an emerging computer vision method,the NeRF has wide application potential,especially in excelling at 3D reconstruction.We first introduce the basic principles and working mechanisms of NeRFs,followed by an in-depth discussion of the technical challenges faced by 3D reconstruction in dynamic scenes,including problems in perspective and illumination changes of moving objects,recognition and modeling of dynamic objects,real-time requirements,data acquisition and calibration,motion estimation,and evaluation mechanisms.We also summarize current state-of-theart approaches to address these challenges,as well as future research trends.The goal is to provide researchers with an in-depth understanding of the application of NeRFs in dynamic scene reconstruction,as well as insights into the key issues faced and future directions.展开更多
3D medical image reconstruction has significantly enhanced diagnostic accuracy,yet the reliance on densely sampled projection data remains a major limitation in clinical practice.Sparse-angle X-ray imaging,though safe...3D medical image reconstruction has significantly enhanced diagnostic accuracy,yet the reliance on densely sampled projection data remains a major limitation in clinical practice.Sparse-angle X-ray imaging,though safer and faster,poses challenges for accurate volumetric reconstruction due to limited spatial information.This study proposes a 3D reconstruction neural network based on adaptive weight fusion(AdapFusionNet)to achieve high-quality 3D medical image reconstruction from sparse-angle X-ray images.To address the issue of spatial inconsistency in multi-angle image reconstruction,an innovative adaptive fusion module was designed to score initial reconstruction results during the inference stage and perform weighted fusion,thereby improving the final reconstruction quality.The reconstruction network is built on an autoencoder(AE)framework and uses orthogonal-angle X-ray images(frontal and lateral projections)as inputs.The encoder extracts 2D features,which the decoder maps into 3D space.This study utilizes a lung CT dataset to obtain complete three-dimensional volumetric data,from which digitally reconstructed radiographs(DRR)are generated at various angles to simulate X-ray images.Since real-world clinical X-ray images rarely come with perfectly corresponding 3D“ground truth,”using CT scans as the three-dimensional reference effectively supports the training and evaluation of deep networks for sparse-angle X-ray 3D reconstruction.Experiments conducted on the LIDC-IDRI dataset with simulated X-ray images(DRR images)as training data demonstrate the superior performance of AdapFusionNet compared to other fusion methods.Quantitative results show that AdapFusionNet achieves SSIM,PSNR,and MAE values of 0.332,13.404,and 0.163,respectively,outperforming other methods(SingleViewNet:0.289,12.363,0.182;AvgFusionNet:0.306,13.384,0.159).Qualitative analysis further confirms that AdapFusionNet significantly enhances the reconstruction of lung and chest contours while effectively reducing noise during the reconstruction process.The findings demonstrate that AdapFusionNet offers significant advantages in 3D reconstruction of sparse-angle X-ray images.展开更多
The alkali adatoms with controlled coverage on the surface have been demonstrated to effectively tune the surface band of quantum materials through in situ electron doping.However,the interplay of orderly arranged alk...The alkali adatoms with controlled coverage on the surface have been demonstrated to effectively tune the surface band of quantum materials through in situ electron doping.However,the interplay of orderly arranged alkali adatoms with the surface states of quantum materials remains unexplored.Here,by using low-temperature scanning tunneling microscopy/spectroscopy(STM/S),we observed the emergent 3×3 super modulation of electronic states on the√3×√3R30°(R3)Cs ordered surface of kagome superconductor CsV_(3)Sb_(5).The nondispersive 3×3 superlattice at R3 ordered surface shows contrast inversion in positive and negative differential conductance maps,indicating a charge order origin.The 3×3 charge order is suppressed with increasing temperature and undetectable at a critical temperature of~62 K.Furthermore,in the Ta substituted sample CsV_(2.6)Ta_(0.4)Sb_(5),where long-range 2×2×2 charge density wave is significantly suppressed,the 3×3 charge order on the R3 ordered surface becomes blurred and much weaker than that in the undoped sample.It indicates that the 3×3 charge order on the R3 ordered surface is directly correlated to the bulk charge density waves in CsV_(3)Sb_(5).Our work provides a new platform for understanding and manipulating the cascade of charge orders in kagome superconductors.展开更多
Lie group analysis method is applied to the extended(3+1)-dimensional Kadomtsev–Petviashvili–Boussinesq equation and the corresponding similarity reduction equations are obtained with various infinitesimal generator...Lie group analysis method is applied to the extended(3+1)-dimensional Kadomtsev–Petviashvili–Boussinesq equation and the corresponding similarity reduction equations are obtained with various infinitesimal generators.By selecting suitable arbitrary functions in the similarity reduction solutions,we obtain abundant invariant solutions,including the trigonometric solution,the kink-lump interaction solution,the interaction solution between lump wave and triangular periodic wave,the two-kink solution,the lump solution,the interaction between a lump and two-kink and the periodic lump solution in different planes.These exact solutions are also given graphically to show the detailed structures of this high dimensional integrable system.展开更多
In this paper,we mainly focus on proving the existence of lump solutions to a generalized(3+1)-dimensional nonlinear differential equation.Hirota’s bilinear method and a quadratic function method are employed to deri...In this paper,we mainly focus on proving the existence of lump solutions to a generalized(3+1)-dimensional nonlinear differential equation.Hirota’s bilinear method and a quadratic function method are employed to derive the lump solutions localized in the whole plane for a(3+1)-dimensional nonlinear differential equation.Three examples of such a nonlinear equation are presented to investigate the exact expressions of the lump solutions.Moreover,the 3d plots and corresponding density plots of the solutions are given to show the space structures of the lump waves.In addition,the breath-wave solutions and several interaction solutions of the(3+1)-dimensional nonlinear differential equation are obtained and their dynamics are analyzed.展开更多
基金financially supported by the Scientific Research Foundation of North China University of Technology(Grant Nos.11005136024XN147-87 and 110051360024XN151-86).
文摘With respect to oceanic fluid dynamics,certain models have appeared,e.g.,an extended time-dependent(3+1)-dimensional shallow water wave equation in an ocean or a river,which we investigate in this paper.Using symbolic computation,we find out,on one hand,a set of bilinear auto-Backlund transformations,which could connect certain solutions of that equation with other solutions of that equation itself,and on the other hand,a set of similarity reductions,which could go from that equation to a known ordinary differential equation.The results in this paper depend on all the oceanic variable coefficients in that equation.
基金supported by the BK21 FOUR funded by the Ministry of Education of Korea and National Research Foundation of Korea,a Korea Agency for Infrastructure Technology Advancement(KAIA)grant funded by the Ministry of Land,Infrastructure,and Transport(Grant 1615013176)IITP(Institute of Information&Coummunications Technology Planning&Evaluation)-ICAN(ICT Challenge and Advanced Network of HRD)grant funded by the Korea government(Ministry of Science and ICT)(RS-2024-00438411).
文摘This paper proposes a novel cargo loading algorithm applicable to automated conveyor-type loading systems.The algorithm offers improvements in computational efficiency and robustness by utilizing the concept of discrete derivatives and introducing logistics-related constraints.Optional consideration of the rotation of the cargoes was made to further enhance the optimality of the solutions,if possible to be physically implemented.Evaluation metrics were developed for accurate evaluation and enhancement of the algorithm’s ability to efficiently utilize the loading space and provide a high level of dynamic stability.Experimental results demonstrate the extensive robustness of the proposed algorithm to the diversity of cargoes present in Business-to-Consumer environments.This study contributes practical advancements in both cargo loading optimization and automation of the logistics industry,with potential applications in last-mile delivery services,warehousing,and supply chain management.
文摘Lie symmetry analysis is applied to a(3+1)-dimensional combined potential Kadomtsev-Petviashvili equation with B-type Kadomtsev-Petviashvili equation(pKP-BKP equation)and the corresponding similarity reduction equations are obtained with the different infinitesimal generators.Invariant solutions with arbitrary functions and constants for the(3+1)-dimensional pKP-BKP equation,including the lump solution,the periodic-lump solution,the two-kink solution,the breather solution and the lump-two-kink solution,have been studied analytically and graphically.
基金funded by the National Key R&D Pro-gram(No.2023YFD2401301)the R&D Program of CNFC Overseas Fishery Co.,Ltd.(No.COFC-C-F-2024-004).
文摘To better understand the biological structure of bigeye tuna(Thunnus obesus),albacore tuna(Thunnus alalunga),and longtail tuna(Thunnus tonggol),computed tomography(CT)was used to scan their bodies,and the data are processed by Mimics software.The skeleton,swim bladder,and muscle of the three tuna species are reconstructed in three dimensions.The surface area and volume of the corresponding parts are measured.The results show that the surface areas of the skeleton of longtail tuna,bigeye tuna,albacore tuna accounted for 28.18%,37.34%,33.45%of their whole body surface areas respectively;the surface areas of swim bladder accounted for 0,2.06%,2.72% of their whole body surface area respectively;and the surface areas of muscle accounted for 71.82%,60.6%,63.83%of their whole body surface areas respectively.And the volumes of skeleton accounted for 28.18%,8.05%,3.84%,the volumes of swim bladder accounted for 0,3.44%,0.92%,and the volumes of muscle accounted for 94.84%,88.51%,95.24%of their body volumes respectively.The swim bladder of the longtail tuna has degenerated,while that of the bigeye tuna is conical,exhibiting the highest volume proportion among the three species.In contrast,the swim bladder of the albacore tuna is both flat and elongated,resembling an arc.Additionally,the surface area and the volume of the bigeye tuna’s swim bladder differ signifi-cantly from those of the albacore tuna.Regarding skeletal and muscular structures,the bigeye tuna has the highest skeletal volume proportion(8.05%),whereas the albacore tuna exhibits the highest muscle volume proportion(95.24%).These morphological differences are closely associated with their respective habitats.This study demonstrates the potential of CT technology in fish morphological research,providing a reliable,non-invasive method for analyzing internal structures,quantifying organ characteristics and improving the accuracy of acoustic stock assessment.
基金supported by Open Foundation of the State Key Laboratory of Refractories and Metallurgy(No.G201711)the National Natural Science Foundation of China(Nos.52104317 and 51874001).
文摘The impact of heavy reduction on dendritic morphology was explored by combining experimental research and numerical simulation in metallurgy,including a detailed three-dimensional(3D)analysis and reconstruction of dendritic solidification structures.Combining scanning electron microscopy and energy-dispersive scanning analysis and ANSYS simulation,the high-precision image processing software Mimics Research was utilized to conduct the extraction of dendritic morphologies.Reverse engineering software NX Imageware was employed for the 3D reconstruction of two-dimensional dendritic morphologies,restoring the dendritic characteristics in three-dimensional space.The results demonstrate that in a two-dimensional plane,dendrites connect with each other to form irregularly shaped“ring-like”structures.These dendrites have a thickness greater than 0.1 mm along the Z-axis direction,leading to the envelopment of molten steel by dendrites in a 3D space of at least 0.1 mm.This results in obstructed flow,confirming the“bridging”of dendrites in three-dimensional space,resulting in a tendency for central segregation.Dense and dispersed tiny dendrites,under the influence of heat flow direction,interconnect and continuously grow,gradually forming primary and secondary dendrites in three-dimensional space.After the completion of dendritic solidification and growth,these microdendrites appear dense and dispersed on the two-dimensional plane,providing the nuclei for the formation of new dendrites.When reduction occurs at a solid fraction of 0.46,there is a noticeable decrease in dendritic spacing,resulting in improved central segregation.
基金Support by the Fundamental Research Funds for the Central Universities(2024300443)the National Natural Science Foundation of China(NSFC)Young Scientists Fund(62405131)。
文摘This article proposes a three-dimensional light field reconstruction method based on neural radiation field(NeRF)called Infrared NeRF for low resolution thermal infrared scenes.Based on the characteristics of the low resolution thermal infrared imaging,various optimizations have been carried out to improve the speed and accuracy of thermal infrared 3D reconstruction.Firstly,inspired by Boltzmann's law of thermal radiation,distance is incorporated into the NeRF model for the first time,resulting in a nonlinear propagation of a single ray and a more accurate description of the physical property that infrared radiation intensity decreases with increasing distance.Secondly,in terms of improving inference speed,based on the phenomenon of high and low frequency distribution of foreground and background in infrared images,a multi ray non-uniform light synthesis strategy is proposed to make the model pay more attention to foreground objects in the scene,reduce the distribution of light in the background,and significantly reduce training time without reducing accuracy.In addition,compared to visible light scenes,infrared images only have a single channel,so fewer network parameters are required.Experiments using the same training data and data filtering method showed that,compared to the original NeRF,the improved network achieved an average improvement of 13.8%and 4.62%in PSNR and SSIM,respectively,while an average decreases of 46%in LPIPS.And thanks to the optimization of network layers and data filtering methods,training only takes about 25%of the original method's time to achieve convergence.Finally,for scenes with weak backgrounds,this article improves the inference speed of the model by 4-6 times compared to the original NeRF by limiting the query interval of the model.
文摘This paper presents a novel method for reconstructing a highly accurate 3D nose model of the human from 2D images and pre-marked landmarks based on algorithmic methods.The study focuses on the reconstruction of a 3D nose model tailored for applications in healthcare and cosmetic surgery.The approach leverages advanced image processing techniques,3D Morphable Models(3DMM),and deformation techniques to overcome the limita-tions of deep learning models,particularly addressing the interpretability issues commonly encountered in medical applications.The proposed method estimates the 3D coordinates of landmark points using a 3D structure estimation algorithm.Sub-landmarks are extracted through image processing techniques and interpolation.The initial surface is generated using a 3DMM,though its accuracy remains limited.To enhance precision,deformation techniques are applied,utilizing the coordinates of 76 identified landmarks and sub-landmarks.The resulting 3D nose model is constructed based on algorithmic methods and pre-marked landmarks.Evaluation of the 3D model is conducted by comparing landmark distances and shape similarity with expert-determined ground truth on 30 Vietnamese volunteers aged 18 to 47,all of whom were either preparing for or required nasal surgery.Experimental results demonstrate a strong agreement between the reconstructed 3D model and the ground truth.The method achieved a mean landmark distance error of 0.631 mm and a shape error of 1.738 mm,demonstrating its potential for medical applications.
基金National Natural Science Foundation of China,Grant/Award Numbers:51809290,51979093,52239009Project funded by Tibet Autonomous Region Key R&D Plan,Grant/Award Number:XZ202101ZY0002GPostgraduate Research&Practice Innovation Program of Jiangsu Province,Grant/Award Number:No.KYCX22_0656。
文摘This study aims to develop a high-precision and cost-efficient method for the threedimensional reconstruction of large particles in natural gravel and blasted rock fragments,utilizing Structure from Motion(SfM)and Multi-View Stereo(MVS)techniques.The proposed approach was applied to characterize the three-dimensional morphology of rockfill dam materials at a real construction site.Particle shape was quantitatively analyzed using shape indices of sphericity,convexity,and angularity.The predominant morphology of natural gravel is characterized as slightly elongated and slightly flat,while rock fragments are slightly elongated and not flat.Probability density distributions of shape indices follow a skewed normal distribution:sphericity and convexity show leftward skewness,whereas angularity is right-skewed.Skewness parameters of sphericity and angularity are consistent between natural gravel and blasted rock fragments,indicating comparable shape asymmetry.Convexity skewness is significantly higher in natural gravel compared to rock fragments,by approximately an order of magnitude.The relationship between size and particle shape shows that form ratios and associated shape descriptors change linearly with the logarithm of size;larger particles approach spherical or cubic forms.The innovative measurements contribute to the particle shape data set of rockfill dam materials,providing valuable insights into the three-dimensional and statistical morphological characteristics of relatively large particles in natural gravel and blasted rock fragments.This approach enhances understanding of particle morphology's impact on the mechanical behavior of granular materials.
基金financial supports from the National Key R&D Program of China (2021YFA1401200)Beijing Outstanding Young Scientist Program (BJJWZYJH01201910007022)+1 种基金National Natural Science Foundation of China (No. U21A20140, No. 92050117, No. 62105024) programBeijing Natural Science Foundation (JQ24028)
文摘Optical three-dimensional(3D)measurement is a critical tool in micro-nano manufacturing,the automotive industry,and medical technology due to its nondestructive nature,high precision,and sensitivity.However,passive light field system still requires a refractive primary lens to collect light of the scene,and structured light can not work well with the highly refractive object.Meta-optics,known for being lightweight,compact,and easily integrable,has enabled advancements in passive metalens-array light fields and active structured light techniques.Here,we propose and experimentally validate a novel 3D measurement metasystem.It features a transmitting metasurface generating chromatic line focuses as depth markers and a symmetrically arranged receiving metasurface collecting depth-dependent spectral responses.A lightweight,physically interpretable algorithm processes these data to yield high-precision depth information efficiently.Experiments on metallic and wafer materials demonstrate a depth accuracy of±20μm and lateral accuracy of±10μm.This single-layer optical metasystem,characterized by simplicity,micro-level accuracy,easy installation and scalability,shows potential for diverse applications,including process control,surface morphology analysis,and production measurement.
文摘Research on reconstructing imperfect faces is a challenging task.In this study,we explore a data-driven approach using a pre-trained MICA(MetrIC fAce)model combined with 3D printing to address this challenge.We propose a training strategy that utilizes the pre-trained MICA model and self-supervised learning techniques to improve accuracy and reduce the time needed for 3D facial structure reconstruction.Our results demonstrate high accuracy,evaluated by the geometric loss function and various statistical measures.To showcase the effectiveness of the approach,we used 3D printing to create a model that covers facial wounds.The findings indicate that our method produces a model that fits well and achieves comprehensive 3D facial reconstruction.This technique has the potential to aid doctors in treating patients with facial injuries.
基金Supported by the Guangdong Major Project of Basic and Applied Basic Research (2023B0303000016)the National Natural Science Foundation of China (U21A20515)。
文摘Efficient three-dimensional(3D)building reconstruction from drone imagery often faces data acquisition,storage,and computational challenges because of its reliance on dense point clouds.In this study,we introduced a novel method for efficient and lightweight 3D building reconstruction from drone imagery using line clouds and sparse point clouds.Our approach eliminates the need to generate dense point clouds,and thus significantly reduces the computational burden by reconstructing 3D models directly from sparse data.We addressed the limitations of line clouds for plane detection and reconstruction by using a new algorithm.This algorithm projects 3D line clouds onto a 2D plane,clusters the projections to identify potential planes,and refines them using sparse point clouds to ensure an accurate and efficient model reconstruction.Extensive qualitative and quantitative experiments demonstrated the effectiveness of our method,demonstrating its superiority over existing techniques in terms of simplicity and efficiency.
文摘BACKGROUND Gastric cancer(GC)remains a significant global health challenge,with high incidence and mortality rates.Neoadjuvant chemotherapy is increasingly used to improve surgical outcomes and long-term survival in advanced cases.However,individual responses to treatment vary widely,and current imaging methods often fall short in accurately predicting efficacy.Advanced imaging techniques,such as computed tomography(CT)3D reconstruction and texture analysis,offer potential for more precise assessment of therapeutic response.AIM To explore the application value of CT 3D reconstruction volume change rate,texture feature analysis,and visual features in assessing the efficacy of neoadjuvant chemotherapy for advanced GC.METHODS A retrospective analysis was conducted on the clinical and imaging data of 97 patients with advanced GC who received S-1 plus Oxaliplatin combined chemotherapy regimen neoadjuvant chemotherapy from January 2022 to March 2024.CT texture feature analysis was performed using MaZda software,and ITK-snap software was used to measure the tumor volume change rate before and after chemotherapy.CT visual features were also evaluated.Using postoperative pathological tumor regression grade(TRG)as the gold standard,the correlation between various indicators and chemotherapy efficacy was analyzed,and a predictive model was constructed and internally validated.RESULTS The minimum misclassification rate of texture features in venous phase CT images(7.85%)was lower than in the arterial phase(13.92%).The volume change rate in the effective chemotherapy group(75.20%)was significantly higher than in the ineffective group(41.75%).There was a strong correlation between volume change rate and TRG grade(r=-0.886,P<0.001).Multivariate analysis showed that gastric wall peristalsis(OR=0.286)and thickness change rate≥40%(OR=0.265)were independent predictive factors.Receiver operating characteristic curve analysis indicated that the volume change rate[area under the curve(AUC)=0.885]was superior to the CT visual feature model(AUC=0.795).When the cutoff value was 82.56%,the sensitivity and specificity were 85.62%and 96.45%,respectively.CONCLUSION The CT 3D reconstruction volume change rate can serve as a preferred quantitative indicator for evaluating the efficacy of neoadjuvant chemotherapy in GC.Combining it with a CT visual feature predictive model can further improve the accuracy of efficacy evaluation.
基金supported by the Hunan Provin〓〓cial Natural Science Foundation for Excellent Young Scholars(Grant No.2023JJ20045)the National Natural Science Foundation of China(Grant No.12372189)。
文摘Photomechanics is a crucial branch of solid mechanics.The localization of point targets constitutes a fundamental problem in optical experimental mechanics,with extensive applications in various missions of unmanned aerial vehicles.Localizing moving targets is crucial for analyzing their motion characteristics and dynamic properties.Reconstructing the trajectories of points from asynchronous cameras is a significant challenge.It encompasses two coupled sub-problems:Trajectory reconstruction and camera synchronization.Present methods typically address only one of these sub-problems individually.This paper proposes a 3D trajectory reconstruction method for point targets based on asynchronous cameras,simultaneously solving both sub-problems.Firstly,we extend the trajectory intersection method to asynchronous cameras to resolve the limitation of traditional triangulation that requires camera synchronization.Secondly,we develop models for camera temporal information and target motion,based on imaging mechanisms and target dynamics characteristics.The parameters are optimized simultaneously to achieve trajectory reconstruction without accurate time parameters.Thirdly,we optimize the camera rotations alongside the camera time information and target motion parameters,using tighter and more continuous constraints on moving points.The reconstruction accuracy is significantly improved,especially when the camera rotations are inaccurate.Finally,the simulated and real-world experimental results demonstrate the feasibility and accuracy of the proposed method.The real-world results indicate that the proposed algorithm achieved a localization error of 112.95 m at an observation distance range of 15-20 km.
基金supported by the National Natural Science Foundation of China(Nos.12172019 and 42477210).
文摘We present a grid-growth method to reconstruct 3D rock joints with arbitrary joint roughness and persistence.In the first step of this workflow,the joint model is divided into uniform grids.Then by adjusting the positions of the grids,the joint morphology can be modified to construct models with desired joint roughness and persistence.Accordingly,numerous joint models with different joint roughness and persistence were built.The effects of relevant parameters(such as the number,height,slope of asperities,and the number,area of rock bridges)on the joint roughness coefficient(JRC)and joint persistence were investigated.Finally,an artificially split joint was reconstructed using the method,and the method's accuracy was evaluated by comparing the JRC of the models with that of the artificially split joint.The results showed that the proposed method can effectively control the JRC of joint models by adjusting the number,height,and slope of asperities.The method can also modify the joint persistence of joint models by adjusting the number and area of rock bridges.Additionally,the JRC of models obtained by our method agrees with that of the artificially split surface.Overall,the method demonstrated high accuracy for 3D rock joint reconstruction.
基金supported by the National Key R&D Program of China(Grant No.2021YFA1001000)the National Natural Science Foundation of China(Grant Nos.82111530212,U23A20282,and 61971255)+2 种基金the Natural Science Founda-tion of Guangdong Province(Grant No.2021B1515020092)the Shenzhen Bay Laboratory Fund(Grant No.SZBL2020090501014)the Shenzhen Science,Technology and Innovation Commission(Grant Nos.KJZD20231023094659002,JCYJ20220530142809022,and WDZC20220811170401001).
文摘Neural organoids and confocal microscopy have the potential to play an important role in microconnectome research to understand neural patterns.We present PLayer,a plug-and-play embedded neural system,which demonstrates the utilization of sparse confocal microscopy layers to interpolate continuous axial resolution.With an embedded system focused on neural network pruning,image scaling,and post-processing,PLayer achieves high-performance metrics with an average structural similarity index of 0.9217 and a peak signal-to-noise ratio of 27.75 dB,all within 20 s.This represents a significant time saving of 85.71%with simplified image processing.By harnessing statistical map estimation in interpolation and incorporating the Vision Transformer–based Restorer,PLayer ensures 2D layer consistency while mitigating heavy computational dependence.As such,PLayer can reconstruct 3D neural organoid confocal data continuously under limited computational power for the wide acceptance of fundamental connectomics and pattern-related research with embedded devices.
基金supported by ZTE Industry-UniversityInstitute Cooperation Funds under Grant No.2023ZTE03-04.
文摘This paper explores the key techniques and challenges in dynamic scene reconstruction with neural radiance fields(NeRF).As an emerging computer vision method,the NeRF has wide application potential,especially in excelling at 3D reconstruction.We first introduce the basic principles and working mechanisms of NeRFs,followed by an in-depth discussion of the technical challenges faced by 3D reconstruction in dynamic scenes,including problems in perspective and illumination changes of moving objects,recognition and modeling of dynamic objects,real-time requirements,data acquisition and calibration,motion estimation,and evaluation mechanisms.We also summarize current state-of-theart approaches to address these challenges,as well as future research trends.The goal is to provide researchers with an in-depth understanding of the application of NeRFs in dynamic scene reconstruction,as well as insights into the key issues faced and future directions.
基金Supported by Sichuan Science and Technology Program(2023YFSY0026,2023YFH0004).
文摘3D medical image reconstruction has significantly enhanced diagnostic accuracy,yet the reliance on densely sampled projection data remains a major limitation in clinical practice.Sparse-angle X-ray imaging,though safer and faster,poses challenges for accurate volumetric reconstruction due to limited spatial information.This study proposes a 3D reconstruction neural network based on adaptive weight fusion(AdapFusionNet)to achieve high-quality 3D medical image reconstruction from sparse-angle X-ray images.To address the issue of spatial inconsistency in multi-angle image reconstruction,an innovative adaptive fusion module was designed to score initial reconstruction results during the inference stage and perform weighted fusion,thereby improving the final reconstruction quality.The reconstruction network is built on an autoencoder(AE)framework and uses orthogonal-angle X-ray images(frontal and lateral projections)as inputs.The encoder extracts 2D features,which the decoder maps into 3D space.This study utilizes a lung CT dataset to obtain complete three-dimensional volumetric data,from which digitally reconstructed radiographs(DRR)are generated at various angles to simulate X-ray images.Since real-world clinical X-ray images rarely come with perfectly corresponding 3D“ground truth,”using CT scans as the three-dimensional reference effectively supports the training and evaluation of deep networks for sparse-angle X-ray 3D reconstruction.Experiments conducted on the LIDC-IDRI dataset with simulated X-ray images(DRR images)as training data demonstrate the superior performance of AdapFusionNet compared to other fusion methods.Quantitative results show that AdapFusionNet achieves SSIM,PSNR,and MAE values of 0.332,13.404,and 0.163,respectively,outperforming other methods(SingleViewNet:0.289,12.363,0.182;AvgFusionNet:0.306,13.384,0.159).Qualitative analysis further confirms that AdapFusionNet significantly enhances the reconstruction of lung and chest contours while effectively reducing noise during the reconstruction process.The findings demonstrate that AdapFusionNet offers significant advantages in 3D reconstruction of sparse-angle X-ray images.
基金Project supported by the National Key Research and Development Project of China(Grant Nos.2022YFA1204100 and 2019YFA0308500)the National Natural Science Foundation of China(Grant No.62488201)+1 种基金the CAS Project for Young Scientists in Basic Research(Grant No.YSBR-003)the Innovation Program of Quantum Science and Technology(Grant No.2021ZD0302700)。
文摘The alkali adatoms with controlled coverage on the surface have been demonstrated to effectively tune the surface band of quantum materials through in situ electron doping.However,the interplay of orderly arranged alkali adatoms with the surface states of quantum materials remains unexplored.Here,by using low-temperature scanning tunneling microscopy/spectroscopy(STM/S),we observed the emergent 3×3 super modulation of electronic states on the√3×√3R30°(R3)Cs ordered surface of kagome superconductor CsV_(3)Sb_(5).The nondispersive 3×3 superlattice at R3 ordered surface shows contrast inversion in positive and negative differential conductance maps,indicating a charge order origin.The 3×3 charge order is suppressed with increasing temperature and undetectable at a critical temperature of~62 K.Furthermore,in the Ta substituted sample CsV_(2.6)Ta_(0.4)Sb_(5),where long-range 2×2×2 charge density wave is significantly suppressed,the 3×3 charge order on the R3 ordered surface becomes blurred and much weaker than that in the undoped sample.It indicates that the 3×3 charge order on the R3 ordered surface is directly correlated to the bulk charge density waves in CsV_(3)Sb_(5).Our work provides a new platform for understanding and manipulating the cascade of charge orders in kagome superconductors.
文摘Lie group analysis method is applied to the extended(3+1)-dimensional Kadomtsev–Petviashvili–Boussinesq equation and the corresponding similarity reduction equations are obtained with various infinitesimal generators.By selecting suitable arbitrary functions in the similarity reduction solutions,we obtain abundant invariant solutions,including the trigonometric solution,the kink-lump interaction solution,the interaction solution between lump wave and triangular periodic wave,the two-kink solution,the lump solution,the interaction between a lump and two-kink and the periodic lump solution in different planes.These exact solutions are also given graphically to show the detailed structures of this high dimensional integrable system.
基金supported by the National Natural Science Foundation of China(Nos.12101572,12371256)2023 Shanxi Province Graduate Innovation Project(No.2023KY614)the 19th Graduate Science and Technology Project of North University of China(No.20231943)。
文摘In this paper,we mainly focus on proving the existence of lump solutions to a generalized(3+1)-dimensional nonlinear differential equation.Hirota’s bilinear method and a quadratic function method are employed to derive the lump solutions localized in the whole plane for a(3+1)-dimensional nonlinear differential equation.Three examples of such a nonlinear equation are presented to investigate the exact expressions of the lump solutions.Moreover,the 3d plots and corresponding density plots of the solutions are given to show the space structures of the lump waves.In addition,the breath-wave solutions and several interaction solutions of the(3+1)-dimensional nonlinear differential equation are obtained and their dynamics are analyzed.
