In this article the affiliation of Jin-Ke Shen,Nai-Teng Wu,Li-Yuan Wang,Gang Jiang,Jin Li,Gui-Long Liu,Xian-Ming Liu were incorrectly given as:State Key Laboratory of Chemistry and Utilization of Carbon Based Energy R...In this article the affiliation of Jin-Ke Shen,Nai-Teng Wu,Li-Yuan Wang,Gang Jiang,Jin Li,Gui-Long Liu,Xian-Ming Liu were incorrectly given as:State Key Laboratory of Chemistry and Utilization of Carbon Based Energy Resources,School of Chemical Engineering and Technology,Xinjiang University,Urumqi 830046,China.展开更多
Accurate seasonal precipitation forecasts,especially for extreme events,are crucial to preventing meteorological hazards and their potential impacts on national development,social activity,and security.However,the int...Accurate seasonal precipitation forecasts,especially for extreme events,are crucial to preventing meteorological hazards and their potential impacts on national development,social activity,and security.However,the intensity of summer precipitation is often largely underestimated in many current dynamic models.This study uses a deep learning method called Cycle-Consistent Generative Adversarial Networks(CycleGAN)to improve the seasonal forecasts for June-JulyAugust precipitation in southeastern China by the Nanjing University of Information Science and Technology Climate Forecast System(NUIST-CFS 1.0).The results suggest that the CycleGAN-based model significantly improves the accuracy in predicting the spatiotemporal distribution of summer precipitation compared to the traditional quantile mapping(QM)method.Using the unpaired bias-correction model,we can also obtain advanced forecasts of the frequency,intensity,and duration of extreme precipitation events over the dynamic model predictions.This study expands the potential applications of deep learning models toward improving seasonal precipitation forecasts.展开更多
Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronar...Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image classification.Image denoising is done by a U-Net architecture that ensures effective image denoising.Attenuation correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of classification.Finally,a novel multi-scale diluted convolution(MSDC)network is proposed.It merges the features extracted in different scales and makes the model learn the features more efficiently.Three scales of filters with size 3×3 are used to extract features.All three steps are compared with state-of-the-art methods.The proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of 39.7.The proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.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
The Zenith Hydrostatic Delay(ZHD)is essential for high-precision Global Navigation Satellite System(GNSS)and Very Long Baseline Interferometry(VLBI)data processing.Accurate estimation of ZHD relies on in situ atmosphe...The Zenith Hydrostatic Delay(ZHD)is essential for high-precision Global Navigation Satellite System(GNSS)and Very Long Baseline Interferometry(VLBI)data processing.Accurate estimation of ZHD relies on in situ atmospheric pressure,which is primarily variable in the vertical direction.Current atmospheric pressure is either site-specific or has limited spatial coverage,necessitating vertical corrections for broader applicability.This study introduces a model that uses a Gaussian function for the vertical correction of atmospheric pressure when in situ meteorological observations are unavailable.Validation with the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis(ERA5)reveals an average Bias and RMS for the new model of 0.31 h Pa and 2.96 h Pa,respectively.This corresponds to improvements of 37.5%and 80.3%in terms of RMS compared to two commonly used models(T0and Tvmodels)that require in situ meteorological observations,respectively.Additional validation with radiosonde data shows an average Bias and RMS of 1.85 h Pa and 4.87 h Pa,corresponding to the improvement of 42.8%and 71.1%in RMS compared with T0and Tv models,respectively.These accuracies are sufficient for calculating ZHD to an accuracy of 1 mm by performing atmospheric pressure vertical correction.The new model can correct atmospheric pressure from meteorological stations or numerical weather forecasts to different heights of the troposphere.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
BACKGROUND Transcatheter arterial chemoembolization(TACE)is a key treatment approach for advanced invasive liver cancer(infiltrative hepatocellular carcinoma).However,its therapeutic response can be difficult to evalu...BACKGROUND Transcatheter arterial chemoembolization(TACE)is a key treatment approach for advanced invasive liver cancer(infiltrative hepatocellular carcinoma).However,its therapeutic response can be difficult to evaluate accurately using conventional two-dimensional imaging criteria due to the tumor’s diffuse and multifocal growth pattern.Volumetric imaging,especially enhanced tumor volume(ETV),offers a more comprehensive assessment.Nonetheless,bias field inhomogeneity in magnetic resonance imaging(MRI)poses challenges,potentially skewing volumetric measurements and undermining prognostic evaluation.AIM To investigate whether MRI bias field correction enhances the accuracy of volumetric assessment of infiltrative hepatocellular carcinoma treated with TACE,and to analyze how this improved measurement impacts prognostic prediction.METHODS We retrospectively collected data from 105 patients with invasive liver cancer who underwent TACE treatment at the Affiliated Hospital of Xuzhou Medical University from January 2020 to January 2024.The improved N4 bias field correction algorithm was applied to process MRI images,and the ETV before and after treatment was calculated.The ETV measurements before and after correction were compared,and their relationship with patient prognosis was analyzed.A Cox proportional hazards model was used to evaluate prognostic factors,with Martingale residual analysis determining the optimal cutoff value,followed by survival analysis.RESULTS Bias field correction significantly affected ETV measurements,with the corrected baseline ETV mean(505.235 cm^(3))being significantly lower than before correction(825.632 cm^(3),P<0.001).Cox analysis showed that the hazard ratio(HR)for corrected baseline ETV(HR=1.165,95%CI:1.069-1.268)was higher than before correction(HR=1.063,95%CI:1.031-1.095).Using 412 cm^(3) as the cutoff,the group with baseline ETV<415 cm^(3) had a longer median survival time compared to the≥415 cm^(3) group(18.523 months vs 8.926 months,P<0.001).The group with an ETV reduction rate≥41%had better prognosis than the<41%group(17.862 months vs 9.235 months,P=0.006).Multivariate analysis confirmed that ETV reduction rate(HR=0.412,P<0.001),Child-Pugh classification(HR=0.298,P<0.001),and Barcelona Clinic Liver Cancer stage(HR=0.578,P=0.045)were independent prognostic factors.CONCLUSION Volume imaging based on MRI bias field correction can improve the accuracy of evaluating the efficacy of TACE treatment for invasive liver cancer.The corrected ETV and its reduction rate can serve as independent indicators for predicting patient prognosis,providing important reference for developing individualized treatment strategies.展开更多
Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination...Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion.This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence,aiming to provide general guidance on appropriate imaging examination selection,comprehensive and accurate imaging assessment for early orthodontic treatment patients.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
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
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
The hot deformation behavior of as-extruded Ti-6554 alloy was investigated through isothermal compression at 700–950°C and 0.001–1 s^(−1).The temperature rise under different deformation conditions was calculat...The hot deformation behavior of as-extruded Ti-6554 alloy was investigated through isothermal compression at 700–950°C and 0.001–1 s^(−1).The temperature rise under different deformation conditions was calculated,and the curve was corrected.The strain compensation constitutive model of as-extruded Ti-6554 alloy based on temperature rise correction was established.The microstructure evolution under different conditions was analyzed,and the dynamic recrystallization(DRX)mechanism was revealed.The results show that the flow stress decreases with the increase in strain rate and the decrease in deformation temperature.The deformation temperature rise gradually increases with the increase in strain rate and the decrease in deformation temperature.At 700°C/1 s^(−1),the temperature rise reaches 100°C.The corrected curve value is higher than the measured value,and the strain compensation constitutive model has high prediction accuracy.The precipitation of theαphase occurs during deformation in the twophase region,which promotes DRX process of theβphase.At low strain rate,the volume fraction of dynamic recrystallization increases with the increase in deformation temperature.DRX mechanism includes continuous DRX and discontinuous DRX.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
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
The forecast results of temperature based on the intelligent grids of the Central Meteorological Observatory and the meteorological bureau of the autonomous region and the numerical forecast model of the European Cent...The forecast results of temperature based on the intelligent grids of the Central Meteorological Observatory and the meteorological bureau of the autonomous region and the numerical forecast model of the European Center(EC model)from February to December in 2022 were used.Based on the data of the national intelligent grid forecast,the intelligent grid forecast of the regional bureau,EC model,etc.,temperature was predicted.According to the research of the grid point forecast synthesis algorithm with the highest accuracy rate in the recent three days,the temperature grid point correction was conducted in two forms of stations and grids.In order to reduce the deviation caused by the seasonal system temperature difference,a temperature prediction model was established by using the rolling forecast errors of 5,10,15,20,25 and 30 d as the basis data.The verification and evaluation of objective correction results show that the accuracy rate of temperature forecast by the intelligent grid of the regional bureau,the national intelligent grid,and EC model could be increased by 10%,8%,and 12%,respectively.展开更多
Correction to:Rare Met.https://doi.org/10.1007/s12598-021-01815-z In the original publication,Fig.5 was published with few mistakes.The correct version of Fig.5 is given in this correction.
文摘In this article the affiliation of Jin-Ke Shen,Nai-Teng Wu,Li-Yuan Wang,Gang Jiang,Jin Li,Gui-Long Liu,Xian-Ming Liu were incorrectly given as:State Key Laboratory of Chemistry and Utilization of Carbon Based Energy Resources,School of Chemical Engineering and Technology,Xinjiang University,Urumqi 830046,China.
基金supported by the National Key Research and Development Program of China(Grant No.2020YFA0608000)the National Natural Science Foundation of China(Grant No.42030605)+1 种基金CAAI-MindSpore Academic Fund Research Projects(CAAIXSJLJJ2023MindSpore11)the program of China Scholarships Council(No.CXXM2101180001)。
文摘Accurate seasonal precipitation forecasts,especially for extreme events,are crucial to preventing meteorological hazards and their potential impacts on national development,social activity,and security.However,the intensity of summer precipitation is often largely underestimated in many current dynamic models.This study uses a deep learning method called Cycle-Consistent Generative Adversarial Networks(CycleGAN)to improve the seasonal forecasts for June-JulyAugust precipitation in southeastern China by the Nanjing University of Information Science and Technology Climate Forecast System(NUIST-CFS 1.0).The results suggest that the CycleGAN-based model significantly improves the accuracy in predicting the spatiotemporal distribution of summer precipitation compared to the traditional quantile mapping(QM)method.Using the unpaired bias-correction model,we can also obtain advanced forecasts of the frequency,intensity,and duration of extreme precipitation events over the dynamic model predictions.This study expands the potential applications of deep learning models toward improving seasonal precipitation forecasts.
基金the Research Grant of Kwangwoon University in 2024.
文摘Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image classification.Image denoising is done by a U-Net architecture that ensures effective image denoising.Attenuation correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of classification.Finally,a novel multi-scale diluted convolution(MSDC)network is proposed.It merges the features extracted in different scales and makes the model learn the features more efficiently.Three scales of filters with size 3×3 are used to extract features.All three steps are compared with state-of-the-art methods.The proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of 39.7.The proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.
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supported by the National Natural Science Foundation of China(42304018)the National Natural Science Foundation of China(42330105,42064002,42074035)+3 种基金the Guangxi Natural Science Foundation of China(Guike AD23026177,2020GXNSFBA297145)the Foundation of Guilin University of Technology(GUTQDJJ6616032)Guangxi Key Laboratory of Spatial Information and Geomatics(21238-21-05)the Innovation Project of Guangxi Graduate Education(YCSW2023341)。
文摘The Zenith Hydrostatic Delay(ZHD)is essential for high-precision Global Navigation Satellite System(GNSS)and Very Long Baseline Interferometry(VLBI)data processing.Accurate estimation of ZHD relies on in situ atmospheric pressure,which is primarily variable in the vertical direction.Current atmospheric pressure is either site-specific or has limited spatial coverage,necessitating vertical corrections for broader applicability.This study introduces a model that uses a Gaussian function for the vertical correction of atmospheric pressure when in situ meteorological observations are unavailable.Validation with the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis(ERA5)reveals an average Bias and RMS for the new model of 0.31 h Pa and 2.96 h Pa,respectively.This corresponds to improvements of 37.5%and 80.3%in terms of RMS compared to two commonly used models(T0and Tvmodels)that require in situ meteorological observations,respectively.Additional validation with radiosonde data shows an average Bias and RMS of 1.85 h Pa and 4.87 h Pa,corresponding to the improvement of 42.8%and 71.1%in RMS compared with T0and Tv models,respectively.These accuracies are sufficient for calculating ZHD to an accuracy of 1 mm by performing atmospheric pressure vertical correction.The new model can correct atmospheric pressure from meteorological stations or numerical weather forecasts to different heights of the troposphere.
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BACKGROUND Transcatheter arterial chemoembolization(TACE)is a key treatment approach for advanced invasive liver cancer(infiltrative hepatocellular carcinoma).However,its therapeutic response can be difficult to evaluate accurately using conventional two-dimensional imaging criteria due to the tumor’s diffuse and multifocal growth pattern.Volumetric imaging,especially enhanced tumor volume(ETV),offers a more comprehensive assessment.Nonetheless,bias field inhomogeneity in magnetic resonance imaging(MRI)poses challenges,potentially skewing volumetric measurements and undermining prognostic evaluation.AIM To investigate whether MRI bias field correction enhances the accuracy of volumetric assessment of infiltrative hepatocellular carcinoma treated with TACE,and to analyze how this improved measurement impacts prognostic prediction.METHODS We retrospectively collected data from 105 patients with invasive liver cancer who underwent TACE treatment at the Affiliated Hospital of Xuzhou Medical University from January 2020 to January 2024.The improved N4 bias field correction algorithm was applied to process MRI images,and the ETV before and after treatment was calculated.The ETV measurements before and after correction were compared,and their relationship with patient prognosis was analyzed.A Cox proportional hazards model was used to evaluate prognostic factors,with Martingale residual analysis determining the optimal cutoff value,followed by survival analysis.RESULTS Bias field correction significantly affected ETV measurements,with the corrected baseline ETV mean(505.235 cm^(3))being significantly lower than before correction(825.632 cm^(3),P<0.001).Cox analysis showed that the hazard ratio(HR)for corrected baseline ETV(HR=1.165,95%CI:1.069-1.268)was higher than before correction(HR=1.063,95%CI:1.031-1.095).Using 412 cm^(3) as the cutoff,the group with baseline ETV<415 cm^(3) had a longer median survival time compared to the≥415 cm^(3) group(18.523 months vs 8.926 months,P<0.001).The group with an ETV reduction rate≥41%had better prognosis than the<41%group(17.862 months vs 9.235 months,P=0.006).Multivariate analysis confirmed that ETV reduction rate(HR=0.412,P<0.001),Child-Pugh classification(HR=0.298,P<0.001),and Barcelona Clinic Liver Cancer stage(HR=0.578,P=0.045)were independent prognostic factors.CONCLUSION Volume imaging based on MRI bias field correction can improve the accuracy of evaluating the efficacy of TACE treatment for invasive liver cancer.The corrected ETV and its reduction rate can serve as independent indicators for predicting patient prognosis,providing important reference for developing individualized treatment strategies.
基金supports by the National Natural Science Foundation of China(Nos.82201135)"2015"Cultivation Program for Reserve Talents for Academic Leaders of Nanjing Stomatological School,Medical School of Nanjing University(No.0223A204).
文摘Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion.This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence,aiming to provide general guidance on appropriate imaging examination selection,comprehensive and accurate imaging assessment for early orthodontic treatment patients.
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.
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.
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National Key R&D Program of China(2022YFB3706901)National Natural Science Foundation of China(52274382)Key Research and Development Program of Hubei Province(2022BAA024)。
文摘The hot deformation behavior of as-extruded Ti-6554 alloy was investigated through isothermal compression at 700–950°C and 0.001–1 s^(−1).The temperature rise under different deformation conditions was calculated,and the curve was corrected.The strain compensation constitutive model of as-extruded Ti-6554 alloy based on temperature rise correction was established.The microstructure evolution under different conditions was analyzed,and the dynamic recrystallization(DRX)mechanism was revealed.The results show that the flow stress decreases with the increase in strain rate and the decrease in deformation temperature.The deformation temperature rise gradually increases with the increase in strain rate and the decrease in deformation temperature.At 700°C/1 s^(−1),the temperature rise reaches 100°C.The corrected curve value is higher than the measured value,and the strain compensation constitutive model has high prediction accuracy.The precipitation of theαphase occurs during deformation in the twophase region,which promotes DRX process of theβphase.At low strain rate,the volume fraction of dynamic recrystallization increases with the increase in deformation temperature.DRX mechanism includes continuous DRX and discontinuous DRX.
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.
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The forecast results of temperature based on the intelligent grids of the Central Meteorological Observatory and the meteorological bureau of the autonomous region and the numerical forecast model of the European Center(EC model)from February to December in 2022 were used.Based on the data of the national intelligent grid forecast,the intelligent grid forecast of the regional bureau,EC model,etc.,temperature was predicted.According to the research of the grid point forecast synthesis algorithm with the highest accuracy rate in the recent three days,the temperature grid point correction was conducted in two forms of stations and grids.In order to reduce the deviation caused by the seasonal system temperature difference,a temperature prediction model was established by using the rolling forecast errors of 5,10,15,20,25 and 30 d as the basis data.The verification and evaluation of objective correction results show that the accuracy rate of temperature forecast by the intelligent grid of the regional bureau,the national intelligent grid,and EC model could be increased by 10%,8%,and 12%,respectively.
文摘Correction to:Rare Met.https://doi.org/10.1007/s12598-021-01815-z In the original publication,Fig.5 was published with few mistakes.The correct version of Fig.5 is given in this correction.
