Previous multi-view 3D human pose estimation methods neither correlate different human joints in each view nor model learnable correlations between the same joints in different views explicitly,meaning that skeleton s...Previous multi-view 3D human pose estimation methods neither correlate different human joints in each view nor model learnable correlations between the same joints in different views explicitly,meaning that skeleton structure information is not utilized and multi-view pose information is not completely fused.Moreover,existing graph convolutional operations do not consider the specificity of different joints and different views of pose information when processing skeleton graphs,making the correlation weights between nodes in the graph and their neighborhood nodes shared.Existing Graph Convolutional Networks(GCNs)cannot extract global and deeplevel skeleton structure information and view correlations efficiently.To solve these problems,pre-estimated multiview 2D poses are designed as a multi-view skeleton graph to fuse skeleton priors and view correlations explicitly to process occlusion problem,with the skeleton-edge and symmetry-edge representing the structure correlations between adjacent joints in each viewof skeleton graph and the view-edge representing the view correlations between the same joints in different views.To make graph convolution operation mine elaborate and sufficient skeleton structure information and view correlations,different correlation weights are assigned to different categories of neighborhood nodes and further assigned to each node in the graph.Based on the graph convolution operation proposed above,a Residual Graph Convolution(RGC)module is designed as the basic module to be combined with the simplified Hourglass architecture to construct the Hourglass-GCN as our 3D pose estimation network.Hourglass-GCNwith a symmetrical and concise architecture processes three scales ofmulti-viewskeleton graphs to extract local-to-global scale and shallow-to-deep level skeleton features efficiently.Experimental results on common large 3D pose dataset Human3.6M and MPI-INF-3DHP show that Hourglass-GCN outperforms some excellent methods in 3D pose estimation accuracy.展开更多
The study of rock failure mechanisms is fundamental to geotechnical engineering,as it enhances design quality and mitigates disaster risks.This research employed in situ compression tests on 3D-printed rocklike sample...The study of rock failure mechanisms is fundamental to geotechnical engineering,as it enhances design quality and mitigates disaster risks.This research employed in situ compression tests on 3D-printed rocklike samples with a single flaw,combining Micro-CT scans and a specialized loading device to analyze their behavior.Mechanical properties and failure modes of these printed samples were compared to those of natural flawed sandstones,demonstrating the capability of 3D printing to replicate natural rock characteristics.By reconstructing 3D crack evolution from 2D CT images and applying digital volume correlation(DVC),the study visualized internal strain fields and established a relationship between strain patterns and rock failure.The results reveal that crack initiation consistently occurs at the flaw,advancing into tensile and secondary shear or mixed cracks.For flaw angles(α)ranging from 0°to 45°,the 3D-printed samples exhibited a higher number of newly formed cracks and a faster increase in crack volume with strain.In contrast,for flaw angles of 45°≤α≤90°,the opposite trend was observed.The internal strain field exhibited significant strain localization,with this uneven distribution playing a critical role in sample failure.When the flaw angle was in the range of 0°≤α≤30°,failure was primarily driven by tensile cracks,forming distinct tensile bands.Conversely,for 30°<α≤90°,a combination of tensile and shear cracks dominated the failure,producing both shear and tensile bands in the sample.Additionally,the strain field component ε_(yy) showed a strong correlation with the evolution of internal damage,providing valuable insights into the underlying rock failure mechanisms.展开更多
Ionospheric disturbances caused by acoustic waves emitted during earthquakes were studied using the Global Navigation Satellite System(GNSS)to analyze the changes in total electron content(TEC)values.GNSS signals norm...Ionospheric disturbances caused by acoustic waves emitted during earthquakes were studied using the Global Navigation Satellite System(GNSS)to analyze the changes in total electron content(TEC)values.GNSS signals normally propagate from satellites to receivers through the ionosphere layer.The delayed signals can be used to obtain TEC values by passing through the layer.Therefore,this study aims to analyze Coseismic Ionospheric Disturbances(CIDs)in six earthquakes,including 2016 M7.8 New Zealand(about 0.49 TECU),2018 M7.9 Alaska(about 0.20 TECU),2005 M7.2 California(about 0.29 TECU),2023 M7.5 Turkey(about 0.49 TECU),2012 M8.6 Sumatra(about 2.98 TECU),and 2012 M8.2 Sumatra(about 1.49 TECU)earthquakes.The propagation speed of the wave from the earthquake epicenter,identified as an acoustic wave,was estimated to be between 0.6 and 1.0 km/s.The 3D tomography modeling was performed to analyze the TEC height variations in the ionosphere to obtain a more accurate spatial analysis of TEC due to earthquakes.Moreover,checkerboard accuracy tests were applied to test the resolution of the 3D tomography model.The maximum ionization correlation test was also conducted for the six earthquakes to determine variations in the maximum ionization height of the ionosphere.The correlation test results between magnitude and maximum CID height produced a moderate correlation.The greater the earthquake magnitude,the higher the maximum CID detected.This is because greater earthquake produces compressed energy,which reduces the ionospheric density and reaches the maximum height.In addition,the maximum CID height is higher at night than in the afternoon because the E layer disappears at night.展开更多
3D printing,as a versatile additive manufacturing technique,offers high design flexibility,rapid prototyping,minimal material waste,and the capability to fabricate complex,customized geometries.These attributes make i...3D printing,as a versatile additive manufacturing technique,offers high design flexibility,rapid prototyping,minimal material waste,and the capability to fabricate complex,customized geometries.These attributes make it particularly well-suited for low-temperature hydrogen electrochemical conversion devices—specifically,proton exchange membrane fuel cells,proton exchange membrane electrolyzer cells,anion exchange membrane electrolyzer cells,and alkaline electrolyzers—which demand finely structured components such as catalyst layers,gas diffusion layers,electrodes,porous transport layers,and bipolar plates.This review provides a focused and critical summary of the current progress in applying 3D printing technologies to these key components.It begins with a concise introduction to the principles and classifications of mainstream 3D printing methods relevant to the hydrogen energy sector and proceeds to analyze their specific applications and performance impacts across different device architectures.Finally,the review identifies existing technical challenges and outlines future research directions to accelerate the integration of 3D printing in nextgeneration low-temperature hydrogen energy systems.展开更多
Flexible electronics face critical challenges in achieving monolithic three-dimensional(3D)integration,including material compatibility,structural stability,and scalable fabrication methods.Inspired by the tactile sen...Flexible electronics face critical challenges in achieving monolithic three-dimensional(3D)integration,including material compatibility,structural stability,and scalable fabrication methods.Inspired by the tactile sensing mechanism of the human skin,we have developed a flexible monolithic 3D-integrated tactile sensing system based on a holey MXene paste,where each vertical one-body unit simultaneously functions as a microsupercapacitor and pressure sensor.The in-plane mesopores of MXene significantly improve ion accessibility,mitigate the self-stacking of nanosheets,and allow the holey MXene to multifunctionally act as a sensing material,an active electrode,and a conductive interconnect,thus drastically reducing the interface mismatch and enhancing the mechanical robustness.Furthermore,we fabricate a large-scale device using a blade-coating and stamping method,which demonstrates excellent mechanical flexibility,low-power consumption,rapid response,and stable long-term operation.As a proof-of-concept application,we integrate our sensing array into a smart access control system,leveraging deep learning to accurately identify users based on their unique pressing behaviors.This study provides a promising approach for designing highly integrated,intelligent,and flexible electronic systems for advanced human-computer interactions and personalized electronics.展开更多
基金supported in part by the National Natural Science Foundation of China under Grants 61973065,U20A20197,61973063.
文摘Previous multi-view 3D human pose estimation methods neither correlate different human joints in each view nor model learnable correlations between the same joints in different views explicitly,meaning that skeleton structure information is not utilized and multi-view pose information is not completely fused.Moreover,existing graph convolutional operations do not consider the specificity of different joints and different views of pose information when processing skeleton graphs,making the correlation weights between nodes in the graph and their neighborhood nodes shared.Existing Graph Convolutional Networks(GCNs)cannot extract global and deeplevel skeleton structure information and view correlations efficiently.To solve these problems,pre-estimated multiview 2D poses are designed as a multi-view skeleton graph to fuse skeleton priors and view correlations explicitly to process occlusion problem,with the skeleton-edge and symmetry-edge representing the structure correlations between adjacent joints in each viewof skeleton graph and the view-edge representing the view correlations between the same joints in different views.To make graph convolution operation mine elaborate and sufficient skeleton structure information and view correlations,different correlation weights are assigned to different categories of neighborhood nodes and further assigned to each node in the graph.Based on the graph convolution operation proposed above,a Residual Graph Convolution(RGC)module is designed as the basic module to be combined with the simplified Hourglass architecture to construct the Hourglass-GCN as our 3D pose estimation network.Hourglass-GCNwith a symmetrical and concise architecture processes three scales ofmulti-viewskeleton graphs to extract local-to-global scale and shallow-to-deep level skeleton features efficiently.Experimental results on common large 3D pose dataset Human3.6M and MPI-INF-3DHP show that Hourglass-GCN outperforms some excellent methods in 3D pose estimation accuracy.
基金supported by the Korea Institute of Energy Technology Evaluation and Planning(KETEP)grant funded by the Korea Government(MOTIE)(Grant No.20214000000500,Training program of CCUS for the green growth)by the National Research Foundation of Korea(NRF)grant funded by the Korea Government(MSIT)(Grant No.2022R1F1A1076409)the support from the Chinese Scholarship Council for awarding a scholarship(CSC No.202106820011).
文摘The study of rock failure mechanisms is fundamental to geotechnical engineering,as it enhances design quality and mitigates disaster risks.This research employed in situ compression tests on 3D-printed rocklike samples with a single flaw,combining Micro-CT scans and a specialized loading device to analyze their behavior.Mechanical properties and failure modes of these printed samples were compared to those of natural flawed sandstones,demonstrating the capability of 3D printing to replicate natural rock characteristics.By reconstructing 3D crack evolution from 2D CT images and applying digital volume correlation(DVC),the study visualized internal strain fields and established a relationship between strain patterns and rock failure.The results reveal that crack initiation consistently occurs at the flaw,advancing into tensile and secondary shear or mixed cracks.For flaw angles(α)ranging from 0°to 45°,the 3D-printed samples exhibited a higher number of newly formed cracks and a faster increase in crack volume with strain.In contrast,for flaw angles of 45°≤α≤90°,the opposite trend was observed.The internal strain field exhibited significant strain localization,with this uneven distribution playing a critical role in sample failure.When the flaw angle was in the range of 0°≤α≤30°,failure was primarily driven by tensile cracks,forming distinct tensile bands.Conversely,for 30°<α≤90°,a combination of tensile and shear cracks dominated the failure,producing both shear and tensile bands in the sample.Additionally,the strain field component ε_(yy) showed a strong correlation with the evolution of internal damage,providing valuable insights into the underlying rock failure mechanisms.
基金supported by the Master's Thesis Research Program of the Ministry of Education and Culture of the Republic of Indonesia,Sepuluh Nopember Institute of Technology with grant number 2002/PKS/ITS/2023 contract number 112/E5/PG.02.00.PL/2023.
文摘Ionospheric disturbances caused by acoustic waves emitted during earthquakes were studied using the Global Navigation Satellite System(GNSS)to analyze the changes in total electron content(TEC)values.GNSS signals normally propagate from satellites to receivers through the ionosphere layer.The delayed signals can be used to obtain TEC values by passing through the layer.Therefore,this study aims to analyze Coseismic Ionospheric Disturbances(CIDs)in six earthquakes,including 2016 M7.8 New Zealand(about 0.49 TECU),2018 M7.9 Alaska(about 0.20 TECU),2005 M7.2 California(about 0.29 TECU),2023 M7.5 Turkey(about 0.49 TECU),2012 M8.6 Sumatra(about 2.98 TECU),and 2012 M8.2 Sumatra(about 1.49 TECU)earthquakes.The propagation speed of the wave from the earthquake epicenter,identified as an acoustic wave,was estimated to be between 0.6 and 1.0 km/s.The 3D tomography modeling was performed to analyze the TEC height variations in the ionosphere to obtain a more accurate spatial analysis of TEC due to earthquakes.Moreover,checkerboard accuracy tests were applied to test the resolution of the 3D tomography model.The maximum ionization correlation test was also conducted for the six earthquakes to determine variations in the maximum ionization height of the ionosphere.The correlation test results between magnitude and maximum CID height produced a moderate correlation.The greater the earthquake magnitude,the higher the maximum CID detected.This is because greater earthquake produces compressed energy,which reduces the ionospheric density and reaches the maximum height.In addition,the maximum CID height is higher at night than in the afternoon because the E layer disappears at night.
基金the support from the National Natural Science Foundation of China(Nos.22208376,UA22A20429)the Qingdao New Energy Shandong Laboratory Open Project(QNESL OP 202303)+3 种基金Shandong Provincial Natural Science Foundation(Nos.ZR2024QB175,ZR2023LFG005)Fundamental Research Funds for the Central Universities(No.25CX07002A)National Natural Science Foundation of China(Z202401390008)The Hunan Provincial Natural Science Foundation(2025JJ60301)。
文摘3D printing,as a versatile additive manufacturing technique,offers high design flexibility,rapid prototyping,minimal material waste,and the capability to fabricate complex,customized geometries.These attributes make it particularly well-suited for low-temperature hydrogen electrochemical conversion devices—specifically,proton exchange membrane fuel cells,proton exchange membrane electrolyzer cells,anion exchange membrane electrolyzer cells,and alkaline electrolyzers—which demand finely structured components such as catalyst layers,gas diffusion layers,electrodes,porous transport layers,and bipolar plates.This review provides a focused and critical summary of the current progress in applying 3D printing technologies to these key components.It begins with a concise introduction to the principles and classifications of mainstream 3D printing methods relevant to the hydrogen energy sector and proceeds to analyze their specific applications and performance impacts across different device architectures.Finally,the review identifies existing technical challenges and outlines future research directions to accelerate the integration of 3D printing in nextgeneration low-temperature hydrogen energy systems.
基金supported by the National Natural Science Foundation of China(52272177,12204010)the Foundation for the Introduction of High-Level Talents of Anhui University(S020118002/097)+1 种基金the University Synergy Innovation Program of Anhui Province(GXXT-2023-066)the Scientific Research Project of Anhui Provincial Higher Education Institution(2023AH040008)。
文摘Flexible electronics face critical challenges in achieving monolithic three-dimensional(3D)integration,including material compatibility,structural stability,and scalable fabrication methods.Inspired by the tactile sensing mechanism of the human skin,we have developed a flexible monolithic 3D-integrated tactile sensing system based on a holey MXene paste,where each vertical one-body unit simultaneously functions as a microsupercapacitor and pressure sensor.The in-plane mesopores of MXene significantly improve ion accessibility,mitigate the self-stacking of nanosheets,and allow the holey MXene to multifunctionally act as a sensing material,an active electrode,and a conductive interconnect,thus drastically reducing the interface mismatch and enhancing the mechanical robustness.Furthermore,we fabricate a large-scale device using a blade-coating and stamping method,which demonstrates excellent mechanical flexibility,low-power consumption,rapid response,and stable long-term operation.As a proof-of-concept application,we integrate our sensing array into a smart access control system,leveraging deep learning to accurately identify users based on their unique pressing behaviors.This study provides a promising approach for designing highly integrated,intelligent,and flexible electronic systems for advanced human-computer interactions and personalized electronics.
