After spinal cord injury,impairment of the sensorimotor circuit can lead to dysfunction in the motor,sensory,proprioceptive,and autonomic nervous systems.Functional recovery is often hindered by constraints on the tim...After spinal cord injury,impairment of the sensorimotor circuit can lead to dysfunction in the motor,sensory,proprioceptive,and autonomic nervous systems.Functional recovery is often hindered by constraints on the timing of interventions,combined with the limitations of current methods.To address these challenges,various techniques have been developed to aid in the repair and reconstruction of neural circuits at different stages of injury.Notably,neuromodulation has garnered considerable attention for its potential to enhance nerve regeneration,provide neuroprotection,restore neurons,and regulate the neural reorganization of circuits within the cerebral cortex and corticospinal tract.To improve the effectiveness of these interventions,the implementation of multitarget early interventional neuromodulation strategies,such as electrical and magnetic stimulation,is recommended to enhance functional recovery across different phases of nerve injury.This review concisely outlines the challenges encountered following spinal cord injury,synthesizes existing neurostimulation techniques while emphasizing neuroprotection,repair,and regeneration of impaired connections,and advocates for multi-targeted,task-oriented,and timely interventions.展开更多
AIM:To evaluate the efficacy and safety of decellularized conjunctival stroma(DCS)as a novel biomaterial by comparing its grafting outcomes with amniotic membrane(AM)when used for conjunctival reconstruction after pri...AIM:To evaluate the efficacy and safety of decellularized conjunctival stroma(DCS)as a novel biomaterial by comparing its grafting outcomes with amniotic membrane(AM)when used for conjunctival reconstruction after primary pterygium excision.METHODS:This randomized,parallel-controlled study with allocation concealment enrolled 40 patients with primary pterygium.Participants were randomly assigned to two groups using the sealed envelope method:the DCS group(n=20)and the AM group(n=18),receiving DCS and AM grafts respectively.Slit-lamp photography of the operative eyes was performed preoperatively and at 1,3,5,7,10,30,90,and 180d postoperatively.Best-corrected visual acuity(BCVA)and symptom scores were recorded simultaneously.In vivo confocal microscopy was conducted at 3 and 6mo postoperatively.RESULTS:All participants exhibited improved postoperative symptoms.The mean age was 60±9y(male/female ratio:6/14)in the DCS group and 56±12y(male/female ratio:7/11)in the AM group.The average epithelial healing time was 9.89±3.54d in the DCS group and 8.17±1.34d in the AM group(P=0.084).One recurrence case was observed in each group.Postoperative graft hemorrhage was significantly more severe in the DCS group than in the AM group only at 30d postoperatively(P=0.011).In vivo confocal microscopy revealed conjunctival epithelial cell growth in both groups at 90d postoperatively,while clear corneo-conjunctival cell boundaries were observed until 180d postoperatively.CONCLUSION:DCS used in primary pterygium surgery has a safety profile comparable to AM.It promotes rapid postoperative conjunctival healing,achieves a relatively low pterygium recurrence rate,and yields outcomes similar to AM.DCS provides a novel biomaterial option for conjunctival reconstruction after pterygium excision and the treatment of other conjunctival injuries.展开更多
Radiation dose reduction in computed tomography(CT)can be achieved by decreasing the number of projections.However,reconstructing CT images via filtered back projection algorithm from sparse-view projections often con...Radiation dose reduction in computed tomography(CT)can be achieved by decreasing the number of projections.However,reconstructing CT images via filtered back projection algorithm from sparse-view projections often contains severe streak artifacts,affecting clinical diagnosis.To address this issue,this paper proposes TransitNet,an iterative unrolling deep neural network that combines model-driven data consistency,a physical a prior constraint,with deep learning’s feature extraction capabilities.TransitNet employs a novel iterative architecture,implementing flexible physical constraints through learnable data consistency operations,utilizing Transformer’s self-attention mechanism to model long-range dependencies in image features,and introducing linear attention mechanisms to reduce self-attention’s computational complexity from quadratic to linear.Extensive experiments demonstrate that this method exhibits significant advantages in both reconstruction quality and computational efficiency,effectively suppressing streak artifacts while preserving structures and details of images.展开更多
Grating-based X-ray phase-contrast imaging enhances the contrast of imaged objects,particularly soft tissues.However,the radiation dose in computed tomography(CT)is generally excessive owing to the complex collection ...Grating-based X-ray phase-contrast imaging enhances the contrast of imaged objects,particularly soft tissues.However,the radiation dose in computed tomography(CT)is generally excessive owing to the complex collection scheme.Sparse-view CT collection reduces the radiation dose,but with reduced resolution and reconstructed artifacts particularly in analytical reconstruction methods.Recently,deep learning has been employed in sparse-view CT reconstruction and achieved stateof-the-art results.Nevertheless,its low generalization performance and requirement for abundant training datasets have hindered the practical application of deep learning in phase-contrast CT.In this study,a CT model was used to generate a substantial number of simulated training datasets,thereby circumventing the need for experimental datasets.By training a network with simulated training datasets,the proposed method achieves high generalization performance in attenuationbased CT and phase-contrast CT,despite the lack of sufficient experimental datasets.In experiments utilizing only half of the CT data,our proposed method obtained an image quality comparable to that of the filtered back-projection algorithm with full-view projection.The proposed method simultaneously addresses two challenges in phase-contrast three-dimensional imaging,namely the lack of experimental datasets and the high exposure dose,through model-driven deep learning.This method significantly accelerates the practical application of phase-contrast CT.展开更多
Neutron computed tomography(NCT)is widely used as a noninvasive measurement technique in nuclear engineering,thermal hydraulics,and cultural heritage.The neutron source intensity of NCT is usually low and the scan tim...Neutron computed tomography(NCT)is widely used as a noninvasive measurement technique in nuclear engineering,thermal hydraulics,and cultural heritage.The neutron source intensity of NCT is usually low and the scan time is long,resulting in a projection image containing severe noise.To reduce the scanning time and increase the image reconstruction quality,an effective reconstruction algorithm must be selected.In CT image reconstruction,the reconstruction algorithms can be divided into three categories:analytical algorithms,iterative algorithms,and deep learning.Because the analytical algorithm requires complete projection data,it is not suitable for reconstruction in harsh environments,such as strong radia-tion,high temperature,and high pressure.Deep learning requires large amounts of data and complex models,which cannot be easily deployed,as well as has a high computational complexity and poor interpretability.Therefore,this paper proposes the OS-SART-PDTV iterative algorithm,which uses the ordered subset simultaneous algebraic reconstruction technique(OS-SART)algorithm to reconstruct the image and the first-order primal–dual algorithm to solve the total variation(PDTV),for sparse-view NCT three-dimensional reconstruction.The novel algorithm was compared with other algorithms(FBP,OS-SART-TV,OS-SART-AwTV,and OS-SART-FGPTV)by simulating the experimental data and actual neutron projection experiments.The reconstruction results demonstrate that the proposed algorithm outperforms the FBP,OS-SART-TV,OS-SART-AwTV,and OS-SART-FGPTV algorithms in terms of preserving edge structure,denoising,and suppressing artifacts.展开更多
Deep-sea mineral resource transportation predominantly utilizes hydraulic pipeline methodology.Environmental factors induce vibrations in flexible pipelines,thereby affecting the internal flow characteristics.Therefor...Deep-sea mineral resource transportation predominantly utilizes hydraulic pipeline methodology.Environmental factors induce vibrations in flexible pipelines,thereby affecting the internal flow characteristics.Therefore,real-time monitoring of solid–liquid two-phase flow in pipelines is crucial for system maintenance.This study develops an autoencoder-based deep learning framework to reconstruct three-dimensional solid–liquid two-phase flow within flexible vibrating pipelines utilizing sparse wall information from sensors.Within this framework,separate X-model and F-model with distinct hidden-layer structures are established to reconstruct the coordinates and flow field information on the computational domain grid of the pipeline under traveling wave vibration.Following hyperparameter optimization,the models achieved high reconstruction accuracy,demonstrating R^(2)values of 0.990 and 0.945,respectively.The models’robustness is evaluated across three aspects:vibration parameters,physical fields,and vibration modes,demonstrating good reconstruction performance.Results concerning sensors show that 20 sensors(0.06%of total grids)achieve a balance between accuracy and cost,with superior accuracy obtained when arranged along the full length of the pipe compared to a dense arrangement at the front end.The models exhibited a signal-to-noise ratio tolerance of approximately 27 dB,with reconstruction accuracy being more affected by sensor failures at both ends of the pipeline.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 study examines the effectiveness of artificial intelligence techniques in generating high-quality environmental data for species introductory site selection systems.Combining Strengths,Weaknesses,Opportunities,Th...This study examines the effectiveness of artificial intelligence techniques in generating high-quality environmental data for species introductory site selection systems.Combining Strengths,Weaknesses,Opportunities,Threats(SWOT)analysis data with Variation Autoencoder(VAE)and Generative AdversarialNetwork(GAN)the network framework model(SAE-GAN),is proposed for environmental data reconstruction.The model combines two popular generative models,GAN and VAE,to generate features conditional on categorical data embedding after SWOT Analysis.The model is capable of generating features that resemble real feature distributions and adding sample factors to more accurately track individual sample data.Reconstructed data is used to retain more semantic information to generate features.The model was applied to species in Southern California,USA,citing SWOT analysis data to train the model.Experiments show that the model is capable of integrating data from more comprehensive analyses than traditional methods and generating high-quality reconstructed data from them,effectively solving the problem of insufficient data collection in development environments.The model is further validated by the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)classification assessment commonly used in the environmental data domain.This study provides a reliable and rich source of training data for species introduction site selection systems and makes a significant contribution to ecological and sustainable development.展开更多
Water splitting hinges crucially on the availability of electrocatalysts for the oxygen evolution reaction.The surface reconstruction has been widely observed in perovskite catalysts,and the reconstruction degree has ...Water splitting hinges crucially on the availability of electrocatalysts for the oxygen evolution reaction.The surface reconstruction has been widely observed in perovskite catalysts,and the reconstruction degree has been often correlated with the activity enhancement.Here,a systematic study on the roles of Fe substitution in activation of perovskite LaNiO_(3)is reported.The substituting Fe content influences both current change tendency and surface reconstruction degree.LaNi_(0.9)Fe_(0.1)O_(3)is found exhibiting a volcano-peak intrinsic activity in both pristine and reconstructed among all substituted perovskites in the LaNi_(1-x)Fe_(x)O_(3)(x=0.00,0.10,0.25,0.50,0.75,1.00)series.The reconstructed LaNi_(0.9)Fe_(0.1)O_(3)shows a higher intrinsic activity than most reported NiFe-based catalysts.Besides,density functional theory calculations reveal that Fe substitution can lower the O 2p level,which thus stabilize lattice oxygen in LaNi0.9Fe0.1O3 and ensure its long-term stability.Furthermore,it is vital interesting that activity of the reconstructed catalysts relied more on the surface chemistry rather than the reconstruction degree.The effect of Fe on the degree of surface reconstruction of the perovskite is decoupled from that on its activity enhancement after surface reconstruction.This finding showcases the importance to customize the surface chemistry of reconstructed catalysts for water oxidation.展开更多
The surgical approach for patellar instability usually refers to reconstruction of the medial patellofemoral ligament associated with an osteotomy of the tibial tuberosity or a trochleoplasty when required.The medial ...The surgical approach for patellar instability usually refers to reconstruction of the medial patellofemoral ligament associated with an osteotomy of the tibial tuberosity or a trochleoplasty when required.The medial patellotibial ligament and the medial patellomeniscal ligament are secondary stabilizers of the patella.Despite this,both the medial patellotibial and patellofemoral ligaments aid in patellar rotation and tilt when the knee is flexed beyond 45°.The medial patellotibial ligament plays a particularly important role in the final stages of stretching in extension and between 40 degrees to 90 degrees of flexion.The clinical relevance and surgical indications for medial patellotibial ligament reconstruction associated with medial patellofemoral ligament reconstruction are still controversial.This editorial explores the surgical indications and clinical results for medial patellotibial ligament reconstruction to improve readers’understanding of this technique,especially because reported clinical outcomes have remained sparse.展开更多
BACKGROUND Bioabsorbable interference screws are a widely used option for graft fixation in anterior cruciate ligament(ACL)reconstruction.Their ability to degrade over time and avoid secondary hardware removal makes t...BACKGROUND Bioabsorbable interference screws are a widely used option for graft fixation in anterior cruciate ligament(ACL)reconstruction.Their ability to degrade over time and avoid secondary hardware removal makes them advantageous.However,complications such as breakage and intra-articular migration of screws can cause significant clinical issues,including joint pain,swelling,and cartilage damage.Early diagnosis and management are critical in such cases.CASE SUMMARY A 26-year-old male presented with knee pain and swelling one year after ACL reconstruction using a hamstring graft and bioabsorbable tibial interference screw.The patient had been engaged in rigorous physical activity as part of military training.Clinical examination revealed mild effusion without instability,and imaging showed screw breakage with intra-articular migration.Therapeutic arthroscopy confirmed intact graft tension,and broken screw fragments were removed successfully.The patient resumed normal activity two weeks after surgery.CONCLUSION This case highlights the potential complications associated with bioabsorbable screws,emphasizing the need for meticulous surgical technique,postoperative monitoring,and timely intervention.A comprehensive review of the literature illustrates the mechanisms,risk factors,and preventive strategies associated with screw-related complications.展开更多
Structural reconstruction of electrocatalysts plays a pivotal role in catalytic performances for CO_(2)reduction reaction(CO_(2)RR),whereas the behavior is by far superficially understood.Here,we report that CO_(2)acc...Structural reconstruction of electrocatalysts plays a pivotal role in catalytic performances for CO_(2)reduction reaction(CO_(2)RR),whereas the behavior is by far superficially understood.Here,we report that CO_(2)accessibility results in a universal self-adaptive structural reconstruction from Cu_(2)O to Cu@CuxO composites,ending with feeding gas-dependent microstructures and catalytic performances.The CO_(2)-rich atmosphere favors reconstruction for CO_(2)RR,whereas the CO_(2)-deficient one prefers that for hydrogen evolution reaction.With the assistance of spectroscopic analysis and theoretical calculations,we uncover a CO_(2)-induced passivation behavior by identifying a reductionresistant but catalytic active Cu(I)-rich amorphous layer stabilized by*CO intermediates.Additionally,we find extra CO production is indispensable for the robust production of C2H4.An inverse correlation between durability and FECO/FEC2H4 is disclosed,suggesting that the selfstabilization process involving the absorption of*CO intermediates on Cu(I)sites is essential for durable electrolysis.Guided by this insight,we design hollow Cu_(2)O nanospheres for durable and selective CO_(2)RR electrolysis in producing C2H4.Our work recognizes the previously overlooked passivation reconstruction and self-stabilizing behavior and highlights the critical role of the local atmosphere in modulating reconstruction and catalytic processes.展开更多
Image super-resolution reconstruction technology is currently widely used in medical imaging,video surveillance,and industrial quality inspection.It not only enhances image quality but also improves details and visual...Image super-resolution reconstruction technology is currently widely used in medical imaging,video surveillance,and industrial quality inspection.It not only enhances image quality but also improves details and visual perception,significantly increasing the utility of low-resolution images.In this study,an improved image superresolution reconstruction model based on Generative Adversarial Networks(SRGAN)was proposed.This model introduced a channel and spatial attention mechanism(CSAB)in the generator,allowing it to effectively leverage the information from the input image to enhance feature representations and capture important details.The discriminator was designed with an improved PatchGAN architecture,which more accurately captured local details and texture information of the image.With these enhanced generator and discriminator architectures and an optimized loss function design,this method demonstrated superior performance in image quality assessment metrics.Experimental results showed that this model outperforms traditional methods,presenting more detailed and realistic image details in the visual effects.展开更多
The morphological description of wear particles in lubricating oil is crucial for wear state monitoring and fault diagnosis in aero-engines.Accurately and comprehensively acquiring three-dimensional(3D)morphological d...The morphological description of wear particles in lubricating oil is crucial for wear state monitoring and fault diagnosis in aero-engines.Accurately and comprehensively acquiring three-dimensional(3D)morphological data of these particles has became a key focus in wear debris analysis.Herein,we develop a novel multi-view polarization-sensitive optical coherence tomography(PS-OCT)method to achieve accurate 3D morphology detection and reconstruction of aero-engine lubricant wear particles,effectively resolving occlusion-induced information loss while enabling material-specific characterization.The particle morphology is captured by multi-view imaging,followed by filtering,sharpening,and contour recognition.The method integrates advanced registration algorithms with Poisson reconstruction to generate high-precision 3D models.This approach not only provides accurate 3D morphological reconstruction but also mitigates information loss caused by particle occlusion,ensuring model completeness.Furthermore,by collecting polarization characteristics of typical metals and their oxides in aero-engine lubricants,this work comprehensively characterizes and comparatively analyzes particle polarization properties using Stokes vectors,polarization uniformity,and cumulative phase retardation,and obtains a three-dimensional model containing polarization information.Ultimately,the proposed method enables multidimensional information acquisition for the reliable identification of abrasive particle types.展开更多
Cyclops lesion is a fibrous nodule on the tibial side of the knee and it is one of the common complications that arises after anterior cruciate ligament (ACL) reconstruction, causing loss of knee extension. A presenta...Cyclops lesion is a fibrous nodule on the tibial side of the knee and it is one of the common complications that arises after anterior cruciate ligament (ACL) reconstruction, causing loss of knee extension. A presentation dominated by recurrent hemarthrosis is a rare presentation of this lesion. In this case report, we have discussed about a male patient who presented with recurrent hemarthrosis and inability to extend the knee joint fully 8 months after ACL reconstruction. Cyclops lesion was identified by clinical examination and magnetic resonance imaging (MRI). Recurrence after initial excision of the lesion occurred and complete resolution happened during the second operation when cauterization was done. It is imperative that treatment should include coagulation of the vascularized stump to avoid any recurrence.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
As a complement to X-ray computed tomography(CT),neutron tomography has been extensively used in nuclear engineer-ing,materials science,cultural heritage,and industrial applications.Reconstruction of the attenuation m...As a complement to X-ray computed tomography(CT),neutron tomography has been extensively used in nuclear engineer-ing,materials science,cultural heritage,and industrial applications.Reconstruction of the attenuation matrix for neutron tomography with a traditional analytical algorithm requires hundreds of projection views in the range of 0°to 180°and typically takes several hours to complete.Such a low time-resolved resolution degrades the quality of neutron imaging.Decreasing the number of projection acquisitions is an important approach to improve the time resolution of images;however,this requires efficient reconstruction algorithms.Therefore,sparse-view reconstruction algorithms in neutron tomography need to be investigated.In this study,we investigated the three-dimensional reconstruction algorithm for sparse-view neu-tron CT scans.To enhance the reconstructed image quality of neutron CT,we propose an algorithm that uses OS-SART to reconstruct images and a split Bregman to solve for the total variation(SBTV).A comparative analysis of the performances of each reconstruction algorithm was performed using simulated and actual experimental data.According to the analyzed results,OS-SART-SBTV is superior to the other algorithms in terms of denoising,suppressing artifacts,and preserving detailed structural information of images.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
On January 7,2025,a 6.8-magnitude earthquake struck Dingri County,Xigaze City,Xizang.On March 3,efforts for post-disaster reconstruction were initiated.By October 31,all newly built,repaired,and reinforced houses had ...On January 7,2025,a 6.8-magnitude earthquake struck Dingri County,Xigaze City,Xizang.On March 3,efforts for post-disaster reconstruction were initiated.By October 31,all newly built,repaired,and reinforced houses had been fully completed and handed over to residents in the earthquake-affected areas of Dingri and surrounding areas,enabling them to move into new homes within the same year they experienced the impact.展开更多
Objective This is a self-controlled multicenter retrospective study based on the clinical efficacy and complications of physiological reconstruction in the treatment of moderate and severe pelvic organ prolapse.Method...Objective This is a self-controlled multicenter retrospective study based on the clinical efficacy and complications of physiological reconstruction in the treatment of moderate and severe pelvic organ prolapse.Methods From December 2014 to August 2021,517 women were included and registered for physiological reconstruction at four Chinese urogynecology institutions.We enrolled 364 women with POP-Q stage≥3.The degree of POP was quantified via a POP-Q system.The surgical purpose of physiological reconstruction is to repair the vagina,levator ani muscle,perineum,and urogenital hiatus and adopt a repair method in accordance with the axial direction of physiology.All 330 evaluable participants were followed for 2 years.The evaluation indices included the PFDI-20,PGI-I,PFIQ-7,PISQ-12,PGI-I,and PGI-S.All complications were coded according to the category-time-site system proposed by the International Urogynecological Association(IUGA)and International Continence Society(ICS).Results Compared with the preoperative POP-Q scores,statistically significant improvements were observed at the 6-month,1-year and 2-year time points(P<0.001).Statistically significant improvements in quality of life were observed across all time points.Conclusions Physiologic reconstructive surgical techniques combined with modified anterior pelvic floor mesh implantation could help restore the physiologic axis and vaginal shape,which may be the most important factors in maintaining the functional position of pelvic floor organs and is the most effective method for repairing the pelvic fascia tendon arch.This surgical method is safe,feasible,and effective in patients with severe prolapse.展开更多
基金supported by the National Key Research and Development Program of China,No.2023YFC3603705(to DX)the National Natural Science Foundation of China,No.82302866(to YZ).
文摘After spinal cord injury,impairment of the sensorimotor circuit can lead to dysfunction in the motor,sensory,proprioceptive,and autonomic nervous systems.Functional recovery is often hindered by constraints on the timing of interventions,combined with the limitations of current methods.To address these challenges,various techniques have been developed to aid in the repair and reconstruction of neural circuits at different stages of injury.Notably,neuromodulation has garnered considerable attention for its potential to enhance nerve regeneration,provide neuroprotection,restore neurons,and regulate the neural reorganization of circuits within the cerebral cortex and corticospinal tract.To improve the effectiveness of these interventions,the implementation of multitarget early interventional neuromodulation strategies,such as electrical and magnetic stimulation,is recommended to enhance functional recovery across different phases of nerve injury.This review concisely outlines the challenges encountered following spinal cord injury,synthesizes existing neurostimulation techniques while emphasizing neuroprotection,repair,and regeneration of impaired connections,and advocates for multi-targeted,task-oriented,and timely interventions.
基金Supported by grants from the National Natural Science Foundation of China(No.82171018,No.82371022)Beijing Hospitals Authority’s Ascent Plan(No.DFL20240202)+2 种基金The Youth Beijing Scholars Program(No.022)High Level Public Health Technical Talents Construction Project from Beijing(Jie Y)Beijing Municipal Public Welfare Development and Reform Pilot Project for Medical Research Institutes(No.2023YFC2410401).
文摘AIM:To evaluate the efficacy and safety of decellularized conjunctival stroma(DCS)as a novel biomaterial by comparing its grafting outcomes with amniotic membrane(AM)when used for conjunctival reconstruction after primary pterygium excision.METHODS:This randomized,parallel-controlled study with allocation concealment enrolled 40 patients with primary pterygium.Participants were randomly assigned to two groups using the sealed envelope method:the DCS group(n=20)and the AM group(n=18),receiving DCS and AM grafts respectively.Slit-lamp photography of the operative eyes was performed preoperatively and at 1,3,5,7,10,30,90,and 180d postoperatively.Best-corrected visual acuity(BCVA)and symptom scores were recorded simultaneously.In vivo confocal microscopy was conducted at 3 and 6mo postoperatively.RESULTS:All participants exhibited improved postoperative symptoms.The mean age was 60±9y(male/female ratio:6/14)in the DCS group and 56±12y(male/female ratio:7/11)in the AM group.The average epithelial healing time was 9.89±3.54d in the DCS group and 8.17±1.34d in the AM group(P=0.084).One recurrence case was observed in each group.Postoperative graft hemorrhage was significantly more severe in the DCS group than in the AM group only at 30d postoperatively(P=0.011).In vivo confocal microscopy revealed conjunctival epithelial cell growth in both groups at 90d postoperatively,while clear corneo-conjunctival cell boundaries were observed until 180d postoperatively.CONCLUSION:DCS used in primary pterygium surgery has a safety profile comparable to AM.It promotes rapid postoperative conjunctival healing,achieves a relatively low pterygium recurrence rate,and yields outcomes similar to AM.DCS provides a novel biomaterial option for conjunctival reconstruction after pterygium excision and the treatment of other conjunctival injuries.
基金National Natural Science Foundation of China under grant (62071281)Local Science and Technology Development Fund Project Guided by the Central Government under grant (YDZJSX2021A003)。
文摘Radiation dose reduction in computed tomography(CT)can be achieved by decreasing the number of projections.However,reconstructing CT images via filtered back projection algorithm from sparse-view projections often contains severe streak artifacts,affecting clinical diagnosis.To address this issue,this paper proposes TransitNet,an iterative unrolling deep neural network that combines model-driven data consistency,a physical a prior constraint,with deep learning’s feature extraction capabilities.TransitNet employs a novel iterative architecture,implementing flexible physical constraints through learnable data consistency operations,utilizing Transformer’s self-attention mechanism to model long-range dependencies in image features,and introducing linear attention mechanisms to reduce self-attention’s computational complexity from quadratic to linear.Extensive experiments demonstrate that this method exhibits significant advantages in both reconstruction quality and computational efficiency,effectively suppressing streak artifacts while preserving structures and details of images.
基金supported by the National Natural Science Foundation of China(Nos.U2032148,U2032157,11775224)USTC Research Funds of the Double First-Class Initiative(No.YD2310002008)the National Key Research and Development Program of China(No.2017YFA0402904),the Youth Innovation Promotion Association,CAS(No.2020457)。
文摘Grating-based X-ray phase-contrast imaging enhances the contrast of imaged objects,particularly soft tissues.However,the radiation dose in computed tomography(CT)is generally excessive owing to the complex collection scheme.Sparse-view CT collection reduces the radiation dose,but with reduced resolution and reconstructed artifacts particularly in analytical reconstruction methods.Recently,deep learning has been employed in sparse-view CT reconstruction and achieved stateof-the-art results.Nevertheless,its low generalization performance and requirement for abundant training datasets have hindered the practical application of deep learning in phase-contrast CT.In this study,a CT model was used to generate a substantial number of simulated training datasets,thereby circumventing the need for experimental datasets.By training a network with simulated training datasets,the proposed method achieves high generalization performance in attenuationbased CT and phase-contrast CT,despite the lack of sufficient experimental datasets.In experiments utilizing only half of the CT data,our proposed method obtained an image quality comparable to that of the filtered back-projection algorithm with full-view projection.The proposed method simultaneously addresses two challenges in phase-contrast three-dimensional imaging,namely the lack of experimental datasets and the high exposure dose,through model-driven deep learning.This method significantly accelerates the practical application of phase-contrast CT.
基金supported by the National Key Research and Development Program of China(No.2022YFB1902700)the Joint Fund of Ministry of Education for Equipment Pre-research(No.8091B042203)+5 种基金the National Natural Science Foundation of China(No.11875129)the Fund of the State Key Laboratory of Intense Pulsed Radiation Simulation and Effect(No.SKLIPR1810)the Fund of Innovation Center of Radiation Application(No.KFZC2020020402)the Fund of the State Key Laboratory of Nuclear Physics and Technology,Peking University(No.NPT2023KFY06)the Joint Innovation Fund of China National Uranium Co.,Ltd.,State Key Laboratory of Nuclear Resources and Environment,East China University of Technology(No.2022NRE-LH-02)the Fundamental Research Funds for the Central Universities(No.2023JG001).
文摘Neutron computed tomography(NCT)is widely used as a noninvasive measurement technique in nuclear engineering,thermal hydraulics,and cultural heritage.The neutron source intensity of NCT is usually low and the scan time is long,resulting in a projection image containing severe noise.To reduce the scanning time and increase the image reconstruction quality,an effective reconstruction algorithm must be selected.In CT image reconstruction,the reconstruction algorithms can be divided into three categories:analytical algorithms,iterative algorithms,and deep learning.Because the analytical algorithm requires complete projection data,it is not suitable for reconstruction in harsh environments,such as strong radia-tion,high temperature,and high pressure.Deep learning requires large amounts of data and complex models,which cannot be easily deployed,as well as has a high computational complexity and poor interpretability.Therefore,this paper proposes the OS-SART-PDTV iterative algorithm,which uses the ordered subset simultaneous algebraic reconstruction technique(OS-SART)algorithm to reconstruct the image and the first-order primal–dual algorithm to solve the total variation(PDTV),for sparse-view NCT three-dimensional reconstruction.The novel algorithm was compared with other algorithms(FBP,OS-SART-TV,OS-SART-AwTV,and OS-SART-FGPTV)by simulating the experimental data and actual neutron projection experiments.The reconstruction results demonstrate that the proposed algorithm outperforms the FBP,OS-SART-TV,OS-SART-AwTV,and OS-SART-FGPTV algorithms in terms of preserving edge structure,denoising,and suppressing artifacts.
基金financial support by the National Natural Science Foundation of China (Nos.52471293 and 12372270)the National Youth Science Foundation of China (Nos.52101322 and 52108375)+3 种基金the Program for Intergovernmental International S&T Cooperation Projects of Shanghai Municipality, China (Nos.24510711100 and 22160710200)The Oceanic Interdisciplinary Program of Shanghai Jiao Tong University (No.SL2022PT101)funded by the Open Fund of the State Key Laboratory of Coastal and Offshore Engineering of Dalian University of Technology (No.LP2415)National Key R&D Program of China (No.2023YFC2811600)
文摘Deep-sea mineral resource transportation predominantly utilizes hydraulic pipeline methodology.Environmental factors induce vibrations in flexible pipelines,thereby affecting the internal flow characteristics.Therefore,real-time monitoring of solid–liquid two-phase flow in pipelines is crucial for system maintenance.This study develops an autoencoder-based deep learning framework to reconstruct three-dimensional solid–liquid two-phase flow within flexible vibrating pipelines utilizing sparse wall information from sensors.Within this framework,separate X-model and F-model with distinct hidden-layer structures are established to reconstruct the coordinates and flow field information on the computational domain grid of the pipeline under traveling wave vibration.Following hyperparameter optimization,the models achieved high reconstruction accuracy,demonstrating R^(2)values of 0.990 and 0.945,respectively.The models’robustness is evaluated across three aspects:vibration parameters,physical fields,and vibration modes,demonstrating good reconstruction performance.Results concerning sensors show that 20 sensors(0.06%of total grids)achieve a balance between accuracy and cost,with superior accuracy obtained when arranged along the full length of the pipe compared to a dense arrangement at the front end.The models exhibited a signal-to-noise ratio tolerance of approximately 27 dB,with reconstruction accuracy being more affected by sensor failures at both ends of the pipeline.
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supported by the Fundamental Research Funds for the Liaoning Universities(LJ212410146025).
文摘This study examines the effectiveness of artificial intelligence techniques in generating high-quality environmental data for species introductory site selection systems.Combining Strengths,Weaknesses,Opportunities,Threats(SWOT)analysis data with Variation Autoencoder(VAE)and Generative AdversarialNetwork(GAN)the network framework model(SAE-GAN),is proposed for environmental data reconstruction.The model combines two popular generative models,GAN and VAE,to generate features conditional on categorical data embedding after SWOT Analysis.The model is capable of generating features that resemble real feature distributions and adding sample factors to more accurately track individual sample data.Reconstructed data is used to retain more semantic information to generate features.The model was applied to species in Southern California,USA,citing SWOT analysis data to train the model.Experiments show that the model is capable of integrating data from more comprehensive analyses than traditional methods and generating high-quality reconstructed data from them,effectively solving the problem of insufficient data collection in development environments.The model is further validated by the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)classification assessment commonly used in the environmental data domain.This study provides a reliable and rich source of training data for species introduction site selection systems and makes a significant contribution to ecological and sustainable development.
基金funded by the National Key R&D Program of China(2021YFA1501101)the National Natural Science Foundation of China(No.22471103,22425105,22201111,21931001,22221001,and 22271124)+5 种基金Young Elite Scientists Sponsorship Program by CAST(2023QNRC001)the Special Fund Project of Guiding Scientific and Technological Innovation Development of Gansu Province(2019ZX-04)the 111 Project(B20027)as well as the National Natural Science Foundation of Gansu Province(22JR5RA470)the Fundamental Research Funds for the Central Universities(lzujbky-2023-eyt03)supported by the Agency for Science,Technology and Research(A*STAR)MTC Individual Research Grants(IRG)M22K2c0078.
文摘Water splitting hinges crucially on the availability of electrocatalysts for the oxygen evolution reaction.The surface reconstruction has been widely observed in perovskite catalysts,and the reconstruction degree has been often correlated with the activity enhancement.Here,a systematic study on the roles of Fe substitution in activation of perovskite LaNiO_(3)is reported.The substituting Fe content influences both current change tendency and surface reconstruction degree.LaNi_(0.9)Fe_(0.1)O_(3)is found exhibiting a volcano-peak intrinsic activity in both pristine and reconstructed among all substituted perovskites in the LaNi_(1-x)Fe_(x)O_(3)(x=0.00,0.10,0.25,0.50,0.75,1.00)series.The reconstructed LaNi_(0.9)Fe_(0.1)O_(3)shows a higher intrinsic activity than most reported NiFe-based catalysts.Besides,density functional theory calculations reveal that Fe substitution can lower the O 2p level,which thus stabilize lattice oxygen in LaNi0.9Fe0.1O3 and ensure its long-term stability.Furthermore,it is vital interesting that activity of the reconstructed catalysts relied more on the surface chemistry rather than the reconstruction degree.The effect of Fe on the degree of surface reconstruction of the perovskite is decoupled from that on its activity enhancement after surface reconstruction.This finding showcases the importance to customize the surface chemistry of reconstructed catalysts for water oxidation.
文摘The surgical approach for patellar instability usually refers to reconstruction of the medial patellofemoral ligament associated with an osteotomy of the tibial tuberosity or a trochleoplasty when required.The medial patellotibial ligament and the medial patellomeniscal ligament are secondary stabilizers of the patella.Despite this,both the medial patellotibial and patellofemoral ligaments aid in patellar rotation and tilt when the knee is flexed beyond 45°.The medial patellotibial ligament plays a particularly important role in the final stages of stretching in extension and between 40 degrees to 90 degrees of flexion.The clinical relevance and surgical indications for medial patellotibial ligament reconstruction associated with medial patellofemoral ligament reconstruction are still controversial.This editorial explores the surgical indications and clinical results for medial patellotibial ligament reconstruction to improve readers’understanding of this technique,especially because reported clinical outcomes have remained sparse.
文摘BACKGROUND Bioabsorbable interference screws are a widely used option for graft fixation in anterior cruciate ligament(ACL)reconstruction.Their ability to degrade over time and avoid secondary hardware removal makes them advantageous.However,complications such as breakage and intra-articular migration of screws can cause significant clinical issues,including joint pain,swelling,and cartilage damage.Early diagnosis and management are critical in such cases.CASE SUMMARY A 26-year-old male presented with knee pain and swelling one year after ACL reconstruction using a hamstring graft and bioabsorbable tibial interference screw.The patient had been engaged in rigorous physical activity as part of military training.Clinical examination revealed mild effusion without instability,and imaging showed screw breakage with intra-articular migration.Therapeutic arthroscopy confirmed intact graft tension,and broken screw fragments were removed successfully.The patient resumed normal activity two weeks after surgery.CONCLUSION This case highlights the potential complications associated with bioabsorbable screws,emphasizing the need for meticulous surgical technique,postoperative monitoring,and timely intervention.A comprehensive review of the literature illustrates the mechanisms,risk factors,and preventive strategies associated with screw-related complications.
基金supported by the National Natural Science Foundation of China(Grant No.22479097)the Shanghai Science and Technology Committee(Grant No.23ZR1433000)the National High-Level Talent Program for Young Scholars,the Start-up Fund(F.S.)from Shanghai Jiao Tong University.
文摘Structural reconstruction of electrocatalysts plays a pivotal role in catalytic performances for CO_(2)reduction reaction(CO_(2)RR),whereas the behavior is by far superficially understood.Here,we report that CO_(2)accessibility results in a universal self-adaptive structural reconstruction from Cu_(2)O to Cu@CuxO composites,ending with feeding gas-dependent microstructures and catalytic performances.The CO_(2)-rich atmosphere favors reconstruction for CO_(2)RR,whereas the CO_(2)-deficient one prefers that for hydrogen evolution reaction.With the assistance of spectroscopic analysis and theoretical calculations,we uncover a CO_(2)-induced passivation behavior by identifying a reductionresistant but catalytic active Cu(I)-rich amorphous layer stabilized by*CO intermediates.Additionally,we find extra CO production is indispensable for the robust production of C2H4.An inverse correlation between durability and FECO/FEC2H4 is disclosed,suggesting that the selfstabilization process involving the absorption of*CO intermediates on Cu(I)sites is essential for durable electrolysis.Guided by this insight,we design hollow Cu_(2)O nanospheres for durable and selective CO_(2)RR electrolysis in producing C2H4.Our work recognizes the previously overlooked passivation reconstruction and self-stabilizing behavior and highlights the critical role of the local atmosphere in modulating reconstruction and catalytic processes.
文摘Image super-resolution reconstruction technology is currently widely used in medical imaging,video surveillance,and industrial quality inspection.It not only enhances image quality but also improves details and visual perception,significantly increasing the utility of low-resolution images.In this study,an improved image superresolution reconstruction model based on Generative Adversarial Networks(SRGAN)was proposed.This model introduced a channel and spatial attention mechanism(CSAB)in the generator,allowing it to effectively leverage the information from the input image to enhance feature representations and capture important details.The discriminator was designed with an improved PatchGAN architecture,which more accurately captured local details and texture information of the image.With these enhanced generator and discriminator architectures and an optimized loss function design,this method demonstrated superior performance in image quality assessment metrics.Experimental results showed that this model outperforms traditional methods,presenting more detailed and realistic image details in the visual effects.
文摘The morphological description of wear particles in lubricating oil is crucial for wear state monitoring and fault diagnosis in aero-engines.Accurately and comprehensively acquiring three-dimensional(3D)morphological data of these particles has became a key focus in wear debris analysis.Herein,we develop a novel multi-view polarization-sensitive optical coherence tomography(PS-OCT)method to achieve accurate 3D morphology detection and reconstruction of aero-engine lubricant wear particles,effectively resolving occlusion-induced information loss while enabling material-specific characterization.The particle morphology is captured by multi-view imaging,followed by filtering,sharpening,and contour recognition.The method integrates advanced registration algorithms with Poisson reconstruction to generate high-precision 3D models.This approach not only provides accurate 3D morphological reconstruction but also mitigates information loss caused by particle occlusion,ensuring model completeness.Furthermore,by collecting polarization characteristics of typical metals and their oxides in aero-engine lubricants,this work comprehensively characterizes and comparatively analyzes particle polarization properties using Stokes vectors,polarization uniformity,and cumulative phase retardation,and obtains a three-dimensional model containing polarization information.Ultimately,the proposed method enables multidimensional information acquisition for the reliable identification of abrasive particle types.
文摘Cyclops lesion is a fibrous nodule on the tibial side of the knee and it is one of the common complications that arises after anterior cruciate ligament (ACL) reconstruction, causing loss of knee extension. A presentation dominated by recurrent hemarthrosis is a rare presentation of this lesion. In this case report, we have discussed about a male patient who presented with recurrent hemarthrosis and inability to extend the knee joint fully 8 months after ACL reconstruction. Cyclops lesion was identified by clinical examination and magnetic resonance imaging (MRI). Recurrence after initial excision of the lesion occurred and complete resolution happened during the second operation when cauterization was done. It is imperative that treatment should include coagulation of the vascularized stump to avoid any recurrence.
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.
基金supported by the National Key Research and Development Program of China(No.2022YFB1902700)the National Natural Science Foundation of China(No.11875129)+3 种基金the Fund of the State Key Laboratory of Intense Pulsed Radiation Simulation and Effect(No.SKLIPR1810)the Fund of Innovation Center of Radiation Application(No.KFZC2020020402)the Fund of the State Key Laboratory of Nuclear Physics and Technology,Peking University(No.NPT2020KFY08)the Joint Innovation Fund of China National Uranium Co.,Ltd.,State Key Laboratory of Nuclear Resources and Environment,East China University of Technology(No.2022NRE-LH-02).
文摘As a complement to X-ray computed tomography(CT),neutron tomography has been extensively used in nuclear engineer-ing,materials science,cultural heritage,and industrial applications.Reconstruction of the attenuation matrix for neutron tomography with a traditional analytical algorithm requires hundreds of projection views in the range of 0°to 180°and typically takes several hours to complete.Such a low time-resolved resolution degrades the quality of neutron imaging.Decreasing the number of projection acquisitions is an important approach to improve the time resolution of images;however,this requires efficient reconstruction algorithms.Therefore,sparse-view reconstruction algorithms in neutron tomography need to be investigated.In this study,we investigated the three-dimensional reconstruction algorithm for sparse-view neu-tron CT scans.To enhance the reconstructed image quality of neutron CT,we propose an algorithm that uses OS-SART to reconstruct images and a split Bregman to solve for the total variation(SBTV).A comparative analysis of the performances of each reconstruction algorithm was performed using simulated and actual experimental data.According to the analyzed results,OS-SART-SBTV is superior to the other algorithms in terms of denoising,suppressing artifacts,and preserving detailed structural information of images.
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.
文摘On January 7,2025,a 6.8-magnitude earthquake struck Dingri County,Xigaze City,Xizang.On March 3,efforts for post-disaster reconstruction were initiated.By October 31,all newly built,repaired,and reinforced houses had been fully completed and handed over to residents in the earthquake-affected areas of Dingri and surrounding areas,enabling them to move into new homes within the same year they experienced the impact.
基金supported by the National Natural Science Foundation of China(No.82260297)Yunnan Province Clinical Research Center for Chronic Kidney Disease(No.202102AA100060).
文摘Objective This is a self-controlled multicenter retrospective study based on the clinical efficacy and complications of physiological reconstruction in the treatment of moderate and severe pelvic organ prolapse.Methods From December 2014 to August 2021,517 women were included and registered for physiological reconstruction at four Chinese urogynecology institutions.We enrolled 364 women with POP-Q stage≥3.The degree of POP was quantified via a POP-Q system.The surgical purpose of physiological reconstruction is to repair the vagina,levator ani muscle,perineum,and urogenital hiatus and adopt a repair method in accordance with the axial direction of physiology.All 330 evaluable participants were followed for 2 years.The evaluation indices included the PFDI-20,PGI-I,PFIQ-7,PISQ-12,PGI-I,and PGI-S.All complications were coded according to the category-time-site system proposed by the International Urogynecological Association(IUGA)and International Continence Society(ICS).Results Compared with the preoperative POP-Q scores,statistically significant improvements were observed at the 6-month,1-year and 2-year time points(P<0.001).Statistically significant improvements in quality of life were observed across all time points.Conclusions Physiologic reconstructive surgical techniques combined with modified anterior pelvic floor mesh implantation could help restore the physiologic axis and vaginal shape,which may be the most important factors in maintaining the functional position of pelvic floor organs and is the most effective method for repairing the pelvic fascia tendon arch.This surgical method is safe,feasible,and effective in patients with severe prolapse.
