The use of visible-light responsive photocatalysts for removing heavy metal ions in wastewater has received great attention.However,the development of photocatalysts with high activity and recyclability remains a huge...The use of visible-light responsive photocatalysts for removing heavy metal ions in wastewater has received great attention.However,the development of photocatalysts with high activity and recyclability remains a huge challenge.Herein,a recyclable carbon fiber cloth-supported porous CdS nanorod photocatalyst was fabricated by a two-step hydrothermal treatment using AgVO_(3) nanowires as templates.The results indicated that under visible-light illumination,the carbon cloth-supported porous CdS nanorods showed improved photocatalytic activity for the reduction of Cr(Ⅵ),with an apparent rate constant exceeding that of carbon cloth-supported CdS nanospheres by a factor of 1.65 times.Moreover,the carbon cloth-supported porous CdS nanorods can be easily separated and be reused.This brings a new perspective for developing photocatalysts with high efficiency and recyclability for wastewater treatment.展开更多
As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods ge...As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.展开更多
The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly comple...The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.展开更多
Enhancing the firefighting protective clothing with exceptional thermal barrier and temperature sensing functions to ensure high fire safety for firefighters has long been anticipated,but it remains a major challenge....Enhancing the firefighting protective clothing with exceptional thermal barrier and temperature sensing functions to ensure high fire safety for firefighters has long been anticipated,but it remains a major challenge.Herein,inspired by the human muscle,an anisotropic fire safety aerogel(ACMCA)with precise self-actuated temperature monitoring performance is developed by combining aramid nanofibers with eicosane/MXene to form an anisotropically oriented conductive network.By combining the two synergies of the negative temperaturedependent thermal conductive eicosane,which induces a high-temperature differential,and directionally ordered MXene that establishes a conductive network along the directional freezing direction.The resultant ACMCA exhibited remarkable thermoelectric properties,with S values reaching 46.78μV K^(−1)andκvalues as low as 0.048 W m^(−1)K^(−1)at room temperature.Moreover,the prepared anisotropic aerogel ACMCA exhibited electrical responsiveness to temperature variations,facilitating its application in intelligent temperature monitoring systems.The designed anisotropic aerogel ACMCA could be incorporated into the firefighting clothing as a thermal barrier layer,demonstrating a wide temperature sensing range(50-400℃)and a rapid response time for early high-temperature alerts(~1.43 s).This work provides novel insights into the design and application of temperature-sensitive anisotropic aramid nanofibers aerogel in firefighting clothing.展开更多
In the workshop of Guangshan White Shark Card Clothing Co.,Ltd.,precision machines are meticulously crafting the tips of card clothing with millimeter-level accuracy.These seemingly tiny textile accessories play a cru...In the workshop of Guangshan White Shark Card Clothing Co.,Ltd.,precision machines are meticulously crafting the tips of card clothing with millimeter-level accuracy.These seemingly tiny textile accessories play a crucial role in the global cotton and chemical fiber industry chains.As China's textile industry encounters trade barriers in the process of globalization,this company specializing in card clothing manufacturing is striving to explore a differentiated path in overseas markets.展开更多
Since the beginning of this year, the China-US economic and trade tensions have brought many challenges to China's clothing export companies. Nevertheless, in the face of difficulties, China's clothing foreign...Since the beginning of this year, the China-US economic and trade tensions have brought many challenges to China's clothing export companies. Nevertheless, in the face of difficulties, China's clothing foreign trade still shows strong resilience and adaptability. From January to May, China's clothing exports showed characteristics such as increased volume, lower prices, category differentiation, and multi-point market layout. Meanwhile, Chinese clothing companies have actively responded to trade friction impacts by closely monitoring tariff negotiations, accelerating transformation and upgrading, exploring diversified international markets, and deepening domestic markets.展开更多
Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,ther...Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,there is limited research on the spatiotemporal characteristics of landslide deformation.This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention(MFA-MRSTGRN)that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion.This model integrates internal seepage factors as data feature enhancements with external triggering factors,allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset.The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules:multilevel feature attention,temporal-residual decomposition,spatial multi-relational graph convolution,and spatiotemporal fusion prediction.This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets,facilitating adaptive exploration of the evolving multi-relational,multi-dimensional spatiotemporal complexities in landslides.When applying this model to predict the displacement of the Liangshuijing landslide,we demonstrate that the MFA-MRSTGRN model surpasses traditional models,such as random forest(RF),long short-term memory(LSTM),and spatial temporal graph convolutional networks(ST-GCN)models in terms of various evaluation metrics including mean absolute error(MAE=1.27 mm),root mean square error(RMSE=1.49 mm),mean absolute percentage error(MAPE=0.026),and R-squared(R^(2)=0.88).Furthermore,feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models.This research provides an advanced and reliable method for landslide displacement prediction.展开更多
As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could ra...As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could range from kilometers to tens of kilometers, and even hundreds and thousands of kilometers. Therefore, it is crucial to develop effective long-range path planning for lunar rovers to meet the demands of lunar patrol exploration. This paper presents a hierarchical map model path planning method that utilizes the existing high-resolution images, digital elevation models and mineral abundance maps. The objective is to address the issue of the construction of lunar rover travel costs in the absence of large-scale, high-resolution digital elevation models. This method models the reference and semantic layers using the middle- and low-resolution remote sensing data. The multi-scale obstacles on the lunar surface are extracted by combining the deep learning algorithm on the high-resolution image, and the obstacle avoidance layer is modeled. A two-stage exploratory path planning decision is employed for long-distance driving path planning on a global–local scale. The proposed method analyzes the long-distance accessibility of various areas of scientific significance, such as Rima Bode. A high-precision digital elevation model is created using stereo images to validate the method. Based on the findings, it can be observed that the entire route spans a distance of 930.32 km. The route demonstrates an impressive ability to avoid meter-level impact craters and linear structures while maintaining an average slope of less than 8°. This paper explores scientific research by traversing at least seven basalt units, uncovering the secrets of lunar volcanic activities, and establishing ‘golden spike’ reference points for lunar stratigraphy. The final result of path planning can serve as a valuable reference for the design, mission demonstration, and subsequent project implementation of the new manned lunar rover.展开更多
Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective metho...Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective method to mitigate the problem,which is able to learn an adaptive segmentation model by transferring knowledge from a rich-labeled source domain.In this paper,we propose a multi-level distribution alignment-based unsupervised domain adaptation network(MDA-Net)for segmentation of 3D neuronal soma images.Distribution alignment is performed in both feature space and output space.In the feature space,features from different scales are adaptively fused to enhance the feature extraction capability for small target somata and con-strained to be domain invariant by adversarial adaptation strategy.In the output space,local discrepancy maps that can reveal the spatial structures of somata are constructed on the predicted segmentation results.Then thedistribution alignment is performed on the local discrepancies maps across domains to obtain a superior discrepancy map in the target domain,achieving refined segmentation performance of neuronal somata.Additionally,after a period of distribution align-ment procedure,a portion of target samples with high confident pseudo-labels are selected as training data,which assist in learning a more adaptive segmentation network.We verified the superiority of the proposed algorithm by comparing several domain adaptation networks on two 3D mouse brain neuronal somata datasets and one macaque brain neuronal soma dataset.展开更多
Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to vari...Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.展开更多
Lithium(Li) metal anodes(LMAs) that employ three-dimensional lithiophilic frameworks are among the most promising options for constructing high-energy-density rechargeable batteries.Herein,hollow ZnS nanosheets with t...Lithium(Li) metal anodes(LMAs) that employ three-dimensional lithiophilic frameworks are among the most promising options for constructing high-energy-density rechargeable batteries.Herein,hollow ZnS nanosheets with the coating of N-doped carbon are modified on the surface of carbon cloth(NCHZS@CC) to serve as the host material for Li metal.It is revealed that the high surface area of NCHZS@CC can significantly reduce local current density and mitigate volume change during cycling.More importantly,the lithiated product of ZnS,confined within the carbon cage,facilitates the uniform deposition of Li metal on carbon fibers and promotes the formation of a stable solid electrolyte interphase enriched with Li_(2)S,thereby improving long-term performance as the cycling progresses.Consequently,the LMAs based on NCHZS@CC demonstrate an impressive cycle life beyond560 h with an ultralow overpotential of 38 mV at a current density of 5 mA cm^(-2)with a capacity of 1 mAh cm^(-2)in the symmetric cell.In addition,when matched with a high mass loading cathode of LiFePO_(4)(11.5 mg cm^(-2)),the assembled full cell displays outstanding performance,achieving 900 cycles at a rate of 2C.展开更多
As "PFC Free" becomes a standard feature for more and more outdoor brands,environmental protection is no longer a distant slogan,but has become a necessary choice in consumer decision-making.When labels‘PFC...As "PFC Free" becomes a standard feature for more and more outdoor brands,environmental protection is no longer a distant slogan,but has become a necessary choice in consumer decision-making.When labels‘PFC free’are attached to products,we cannot help but ask:Where will the next environmental revolution occur?展开更多
An access control model is proposed based on the famous Bell-LaPadula （BLP） model.In the proposed model,hierarchical relationships among departments are built,a new concept named post is proposed,and assigning secur...An access control model is proposed based on the famous Bell-LaPadula （BLP） model.In the proposed model,hierarchical relationships among departments are built,a new concept named post is proposed,and assigning security tags to subjects and objects is greatly simplified.The interoperation among different departments is implemented through assigning multiple security tags to one post, and the more departments are closed on the organization tree,the more secret objects can be exchanged by the staff of the departments.The access control matrices of the department,post and staff are defined.By using the three access control matrices,a multi granularity and flexible discretionary access control policy is implemented.The outstanding merit of the BLP model is inherited,and the new model can guarantee that all the information flow is under control.Finally,our study shows that compared to the BLP model,the proposed model is more flexible.展开更多
Micro-honeycomb ceramics were successfully fabricated through brush-coating with cloth fabric as pore-forming agent. The influence of pore-forming agent and slurry’s moisture content on the micro-honeycomb ceramics w...Micro-honeycomb ceramics were successfully fabricated through brush-coating with cloth fabric as pore-forming agent. The influence of pore-forming agent and slurry’s moisture content on the micro-honeycomb ceramics was investigated. The results indicated that micro-honeycomb ceramics made from pore-forming agent cloth fabric with fibre diameter of 100 μm and slurry with 45% （mass fraction） moisture content have the porosity of 65% （volume fraction）, bending strength of 24.3 MPa, pore size of about 100 μm, cell wall thickness of about 50 μm and porosity of 1131 pore/cm2. It was suggested that the pore size and the porosity could be adjusted using the pore-forming agent and moisture content of the slurry respectively.展开更多
E-commerce has transformed Caoxian into a hub of traditional Chinese attire.STEPPING inside Caoxian’s Youai Cloud Warehouse,a livestreaming base dedicated to hanfu(traditional clothing),it feels less like a clothing ...E-commerce has transformed Caoxian into a hub of traditional Chinese attire.STEPPING inside Caoxian’s Youai Cloud Warehouse,a livestreaming base dedicated to hanfu(traditional clothing),it feels less like a clothing warehouse and more like a time capsule.Thousands of intricately embroidered garments line the racks-from elegant horse-face skirts to modernised editions of traditional Chinese clothing.展开更多
An effective shape signature namely multi-level included angle functions MIAFs is proposed to describe the hierarchy information ranging from global information to local variations of shape.Invariance to rotation tran...An effective shape signature namely multi-level included angle functions MIAFs is proposed to describe the hierarchy information ranging from global information to local variations of shape.Invariance to rotation translation and scaling are the intrinsic properties of the MIAFs.For each contour point the multi-level included angles are obtained based on the paired line segments derived from unequal-arc-length partitions of contour.And a Fourier descriptor derived from multi-level included angle functions MIAFD is presented for efficient shape retrieval.The proposed descriptor is evaluated with the standard performance evaluation method on three shape image databases the MPEG-7 database the Kimia-99 database and the Swedish leaf database. The experimental results of shape retrieval indicate that the MIAFD outperforms the existing Fourier descriptors and has low computational complexity.And the comparison of the MIAFD with other shape description methods also shows that the proposed descriptor has the highest precision at the same recall value which verifies its effectiveness.展开更多
文摘The use of visible-light responsive photocatalysts for removing heavy metal ions in wastewater has received great attention.However,the development of photocatalysts with high activity and recyclability remains a huge challenge.Herein,a recyclable carbon fiber cloth-supported porous CdS nanorod photocatalyst was fabricated by a two-step hydrothermal treatment using AgVO_(3) nanowires as templates.The results indicated that under visible-light illumination,the carbon cloth-supported porous CdS nanorods showed improved photocatalytic activity for the reduction of Cr(Ⅵ),with an apparent rate constant exceeding that of carbon cloth-supported CdS nanospheres by a factor of 1.65 times.Moreover,the carbon cloth-supported porous CdS nanorods can be easily separated and be reused.This brings a new perspective for developing photocatalysts with high efficiency and recyclability for wastewater treatment.
基金National Natural Science Foundation of China(Nos.42301473,42271424,42171397)Chinese Postdoctoral Innovation Talents Support Program(No.BX20230299)+2 种基金China Postdoctoral Science Foundation(No.2023M742884)Natural Science Foundation of Sichuan Province(Nos.24NSFSC2264,2025ZNSFSC0322)Key Research and Development Project of Sichuan Province(No.24ZDYF0633).
文摘As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.
基金financially supported by Guangdong Province Basic and Applied Basic Research Fund Project(Grant No.2022B1515250009)Liaoning Provincial Natural Science Foundation-Doctoral Research Start-up Fund Project(Grant No.2024-BSBA-05)+1 种基金Major Science and Technology Innovation Project in Shandong Province(Grant No.2024CXGC010803)the National Natural Science Foundation of China(Grant Nos.52271269 and 12302147).
文摘The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.
基金funding support from Guiding Project of Scientific Research Plan of Education Department of Hubei Province and Wuhan Textile University School Fund(B)(k24016).
文摘Enhancing the firefighting protective clothing with exceptional thermal barrier and temperature sensing functions to ensure high fire safety for firefighters has long been anticipated,but it remains a major challenge.Herein,inspired by the human muscle,an anisotropic fire safety aerogel(ACMCA)with precise self-actuated temperature monitoring performance is developed by combining aramid nanofibers with eicosane/MXene to form an anisotropically oriented conductive network.By combining the two synergies of the negative temperaturedependent thermal conductive eicosane,which induces a high-temperature differential,and directionally ordered MXene that establishes a conductive network along the directional freezing direction.The resultant ACMCA exhibited remarkable thermoelectric properties,with S values reaching 46.78μV K^(−1)andκvalues as low as 0.048 W m^(−1)K^(−1)at room temperature.Moreover,the prepared anisotropic aerogel ACMCA exhibited electrical responsiveness to temperature variations,facilitating its application in intelligent temperature monitoring systems.The designed anisotropic aerogel ACMCA could be incorporated into the firefighting clothing as a thermal barrier layer,demonstrating a wide temperature sensing range(50-400℃)and a rapid response time for early high-temperature alerts(~1.43 s).This work provides novel insights into the design and application of temperature-sensitive anisotropic aramid nanofibers aerogel in firefighting clothing.
文摘In the workshop of Guangshan White Shark Card Clothing Co.,Ltd.,precision machines are meticulously crafting the tips of card clothing with millimeter-level accuracy.These seemingly tiny textile accessories play a crucial role in the global cotton and chemical fiber industry chains.As China's textile industry encounters trade barriers in the process of globalization,this company specializing in card clothing manufacturing is striving to explore a differentiated path in overseas markets.
文摘Since the beginning of this year, the China-US economic and trade tensions have brought many challenges to China's clothing export companies. Nevertheless, in the face of difficulties, China's clothing foreign trade still shows strong resilience and adaptability. From January to May, China's clothing exports showed characteristics such as increased volume, lower prices, category differentiation, and multi-point market layout. Meanwhile, Chinese clothing companies have actively responded to trade friction impacts by closely monitoring tariff negotiations, accelerating transformation and upgrading, exploring diversified international markets, and deepening domestic markets.
基金the funding support from the National Natural Science Foundation of China(Grant No.52308340)Chongqing Talent Innovation and Entrepreneurship Demonstration Team Project(Grant No.cstc2024ycjh-bgzxm0012)the Science and Technology Projects supported by China Coal Technology and Engineering Chongqing Design and Research Institute(Group)Co.,Ltd.(Grant No.H20230317).
文摘Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,there is limited research on the spatiotemporal characteristics of landslide deformation.This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention(MFA-MRSTGRN)that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion.This model integrates internal seepage factors as data feature enhancements with external triggering factors,allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset.The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules:multilevel feature attention,temporal-residual decomposition,spatial multi-relational graph convolution,and spatiotemporal fusion prediction.This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets,facilitating adaptive exploration of the evolving multi-relational,multi-dimensional spatiotemporal complexities in landslides.When applying this model to predict the displacement of the Liangshuijing landslide,we demonstrate that the MFA-MRSTGRN model surpasses traditional models,such as random forest(RF),long short-term memory(LSTM),and spatial temporal graph convolutional networks(ST-GCN)models in terms of various evaluation metrics including mean absolute error(MAE=1.27 mm),root mean square error(RMSE=1.49 mm),mean absolute percentage error(MAPE=0.026),and R-squared(R^(2)=0.88).Furthermore,feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models.This research provides an advanced and reliable method for landslide displacement prediction.
基金co-supported by the National Key Research and Development Program of China(No.2022YFF0503100)the Youth Innovation Project of Pandeng Program of National Space Science Center,Chinese Academy of Sciences(No.E3PD40012S).
文摘As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could range from kilometers to tens of kilometers, and even hundreds and thousands of kilometers. Therefore, it is crucial to develop effective long-range path planning for lunar rovers to meet the demands of lunar patrol exploration. This paper presents a hierarchical map model path planning method that utilizes the existing high-resolution images, digital elevation models and mineral abundance maps. The objective is to address the issue of the construction of lunar rover travel costs in the absence of large-scale, high-resolution digital elevation models. This method models the reference and semantic layers using the middle- and low-resolution remote sensing data. The multi-scale obstacles on the lunar surface are extracted by combining the deep learning algorithm on the high-resolution image, and the obstacle avoidance layer is modeled. A two-stage exploratory path planning decision is employed for long-distance driving path planning on a global–local scale. The proposed method analyzes the long-distance accessibility of various areas of scientific significance, such as Rima Bode. A high-precision digital elevation model is created using stereo images to validate the method. Based on the findings, it can be observed that the entire route spans a distance of 930.32 km. The route demonstrates an impressive ability to avoid meter-level impact craters and linear structures while maintaining an average slope of less than 8°. This paper explores scientific research by traversing at least seven basalt units, uncovering the secrets of lunar volcanic activities, and establishing ‘golden spike’ reference points for lunar stratigraphy. The final result of path planning can serve as a valuable reference for the design, mission demonstration, and subsequent project implementation of the new manned lunar rover.
基金supported by the Fund of Key Laboratory of Biomedical Engineering of Hainan Province(No.BME20240001)the STI2030-Major Projects(No.2021ZD0200104)the National Natural Science Foundations of China under Grant 61771437.
文摘Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective method to mitigate the problem,which is able to learn an adaptive segmentation model by transferring knowledge from a rich-labeled source domain.In this paper,we propose a multi-level distribution alignment-based unsupervised domain adaptation network(MDA-Net)for segmentation of 3D neuronal soma images.Distribution alignment is performed in both feature space and output space.In the feature space,features from different scales are adaptively fused to enhance the feature extraction capability for small target somata and con-strained to be domain invariant by adversarial adaptation strategy.In the output space,local discrepancy maps that can reveal the spatial structures of somata are constructed on the predicted segmentation results.Then thedistribution alignment is performed on the local discrepancies maps across domains to obtain a superior discrepancy map in the target domain,achieving refined segmentation performance of neuronal somata.Additionally,after a period of distribution align-ment procedure,a portion of target samples with high confident pseudo-labels are selected as training data,which assist in learning a more adaptive segmentation network.We verified the superiority of the proposed algorithm by comparing several domain adaptation networks on two 3D mouse brain neuronal somata datasets and one macaque brain neuronal soma dataset.
文摘Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.
基金financial supports from the National Natural Science Foundation of China(Nos.22279116 and U20A20253)the Natural Science Foundation of Zhejiang Province(Nos.LQ24E020012 and LD22E020006)Jianbing Science and Technology Project of Zhejiang Province(No.2023C01127)
文摘Lithium(Li) metal anodes(LMAs) that employ three-dimensional lithiophilic frameworks are among the most promising options for constructing high-energy-density rechargeable batteries.Herein,hollow ZnS nanosheets with the coating of N-doped carbon are modified on the surface of carbon cloth(NCHZS@CC) to serve as the host material for Li metal.It is revealed that the high surface area of NCHZS@CC can significantly reduce local current density and mitigate volume change during cycling.More importantly,the lithiated product of ZnS,confined within the carbon cage,facilitates the uniform deposition of Li metal on carbon fibers and promotes the formation of a stable solid electrolyte interphase enriched with Li_(2)S,thereby improving long-term performance as the cycling progresses.Consequently,the LMAs based on NCHZS@CC demonstrate an impressive cycle life beyond560 h with an ultralow overpotential of 38 mV at a current density of 5 mA cm^(-2)with a capacity of 1 mAh cm^(-2)in the symmetric cell.In addition,when matched with a high mass loading cathode of LiFePO_(4)(11.5 mg cm^(-2)),the assembled full cell displays outstanding performance,achieving 900 cycles at a rate of 2C.
文摘As "PFC Free" becomes a standard feature for more and more outdoor brands,environmental protection is no longer a distant slogan,but has become a necessary choice in consumer decision-making.When labels‘PFC free’are attached to products,we cannot help but ask:Where will the next environmental revolution occur?
基金The National Natural Science Foundation of China(No.60403027,60773191,70771043)the National High Technology Research and Development Program of China(863 Program)(No.2007AA01Z403)
文摘An access control model is proposed based on the famous Bell-LaPadula （BLP） model.In the proposed model,hierarchical relationships among departments are built,a new concept named post is proposed,and assigning security tags to subjects and objects is greatly simplified.The interoperation among different departments is implemented through assigning multiple security tags to one post, and the more departments are closed on the organization tree,the more secret objects can be exchanged by the staff of the departments.The access control matrices of the department,post and staff are defined.By using the three access control matrices,a multi granularity and flexible discretionary access control policy is implemented.The outstanding merit of the BLP model is inherited,and the new model can guarantee that all the information flow is under control.Finally,our study shows that compared to the BLP model,the proposed model is more flexible.
基金Project (2011WK4013) supported by the Basic Research Program of Hunan Provincial Science and Technology Department, ChinaProject (K1003031-11) supported by the Major Program for the Fundamental Research of Changsha Science and Technology Bureau, China
文摘Micro-honeycomb ceramics were successfully fabricated through brush-coating with cloth fabric as pore-forming agent. The influence of pore-forming agent and slurry’s moisture content on the micro-honeycomb ceramics was investigated. The results indicated that micro-honeycomb ceramics made from pore-forming agent cloth fabric with fibre diameter of 100 μm and slurry with 45% （mass fraction） moisture content have the porosity of 65% （volume fraction）, bending strength of 24.3 MPa, pore size of about 100 μm, cell wall thickness of about 50 μm and porosity of 1131 pore/cm2. It was suggested that the pore size and the porosity could be adjusted using the pore-forming agent and moisture content of the slurry respectively.
文摘E-commerce has transformed Caoxian into a hub of traditional Chinese attire.STEPPING inside Caoxian’s Youai Cloud Warehouse,a livestreaming base dedicated to hanfu(traditional clothing),it feels less like a clothing warehouse and more like a time capsule.Thousands of intricately embroidered garments line the racks-from elegant horse-face skirts to modernised editions of traditional Chinese clothing.
基金The National Natural Science Foundation of China(No.61170116,61375010,60973064)
文摘An effective shape signature namely multi-level included angle functions MIAFs is proposed to describe the hierarchy information ranging from global information to local variations of shape.Invariance to rotation translation and scaling are the intrinsic properties of the MIAFs.For each contour point the multi-level included angles are obtained based on the paired line segments derived from unequal-arc-length partitions of contour.And a Fourier descriptor derived from multi-level included angle functions MIAFD is presented for efficient shape retrieval.The proposed descriptor is evaluated with the standard performance evaluation method on three shape image databases the MPEG-7 database the Kimia-99 database and the Swedish leaf database. The experimental results of shape retrieval indicate that the MIAFD outperforms the existing Fourier descriptors and has low computational complexity.And the comparison of the MIAFD with other shape description methods also shows that the proposed descriptor has the highest precision at the same recall value which verifies its effectiveness.
