Urban spatial morphology(USM)optimization is critical to balancing biodiversity conservation and sustainable urbanization.However,previous studies predominantly focused on the socio-economic efficiency and static ecol...Urban spatial morphology(USM)optimization is critical to balancing biodiversity conservation and sustainable urbanization.However,previous studies predominantly focused on the socio-economic efficiency and static ecological metrics and rarely addressed the dynamic USM optimization across spatial scales.Here,we developed a multi-level ecological network(MEN)framework to resolve the tension between urban expansion and ecological integrity.By integrating the cost-weighted distance analysis with a hierarchical network transmission mechanism,we established a cross-scale spatial optimization system,which coordinated the regional ecological corridors and local habitat patches.Comparative experiments with conventional single-scale approaches and scenario simulations using the PLUS model show that the MEN framework had superior performance in three dimensions:(1)spatial governance:the primary-level network(peri-urban natural reserves)effectively contained urban sprawl,and the secondary-level network(intra-urban green corridors)mitigated habitat fragmentation and improved the built-environment;(2)scenario robustness:the model maintained an optimal compactness-loose balance in multiple development pathways;(3)landscape metrics:patch fragmentation decreased by 18.25%,and the internal landscape richness improved by 10.66%compared to the scenario without USM optimization.The findings provide new insight to establish a hierarchical ecological optimization framework as a nature-based spatial protocol to reconcile metropolitan growth with landscape sustainability.展开更多
The influence of different solution and aging conditions on the microstructure,impact toughness,and crack initiation and propagation mechanisms of the novel α+β titanium alloy Ti6422 was systematically investigated....The influence of different solution and aging conditions on the microstructure,impact toughness,and crack initiation and propagation mechanisms of the novel α+β titanium alloy Ti6422 was systematically investigated.By adjusting the furnace cooling time after solution treatment and the aging temperature,Ti6422 alloy samples were developed with a multi-level lamellar microstructure,in-cluding microscaleαcolonies and α_(p) lamellae,as well as nanoscale α_(s) phases.Extending the furnace cooling time after solution treatment at 920℃ for 1 h from 240 to 540 min,followed by aging at 600℃ for 6 h,increased the α_(p) lamella content,reduced the α_(s) phase content,expanded theαcolonies and α_(p) lamellae size,and improved the impact toughness from 22.7 to 53.8 J/cm^(2).Additionally,under the same solution treatment,raising the aging temperature from 500 to 700℃ resulted in a decrease in the α_(s) phase content and a growth in the thickness of the α_(p) lamella and α_(s) phase.The impact toughness increased significantly with these changes.Samples with high α_(p) lamellae content or large α_(s) phase size exhibited high crack initiation and propagation energies.Impact deformation caused severe kinking of the α_(p) lamellae in crack initiation and propagation areas,leading to a uniform and high-density kernel average misorientation(KAM)distribu-tion,enhancing plastic deformation coordination and uniformity.Moreover,the multidirectional arrangement of coarserαcolonies and α_(p) lamellae continuously deflect the crack propagation direction,inhibiting crack propagation.展开更多
In the references[4,11,12],the authors gave some modular forms overΓ^(0)(2).In this note,we proceed with the study of cancellation formulas relating to the modular forms.
Modular truss space deployable antennas are key for future large aperture,high precision antennas,already proven in various in-orbit applications globally.This paper introduces a design method for a tetrahedral basic ...Modular truss space deployable antennas are key for future large aperture,high precision antennas,already proven in various in-orbit applications globally.This paper introduces a design method for a tetrahedral basic unit mechanism with dual height positioning nodes.A parametric model is established,and its DOF are analyzed to confirm the mechanism's validity.The new tetrahedral basic unit mechanism constructed by this method is a single DOF mechanism and can locate different parabolic node heights.In order to further adapt to the parabolic and large aperture requirements of the deployable antenna of the truss,a combination unit and modular unit mechanism are developed based on this tetrahedral unit.The DOF and deployment characteristics of the modular unit mechanism are analyzed and validated through simulations.Various networking methods for the modular units are proposed,followed by a comprehensive performance comparison of different modular truss deployable antenna mechanisms.A prototype model of the modular unit mechanism is also developed,with deployment experiments demonstrating the mechanism's simplicity,low DOF,and large deployment ratio.The findings of this study provide a theoretical and technical basis for the future design and development of truss deployable antenna mechanisms.展开更多
There is no common accepted way for calculating the valve power loss of modular multilevel converter(MMC).Valve power loss estimation based on analytical calculation is inaccurate to address the switching power loss a...There is no common accepted way for calculating the valve power loss of modular multilevel converter(MMC).Valve power loss estimation based on analytical calculation is inaccurate to address the switching power loss and valve power loss estimation based on detailed electro-magnetic simulation is of low speed.To solve this problem,a method of valve power loss estimation based on the detailed equivalent simulation model of MMC is proposed.Results of valve power loss analysis of 201-level 500MW MMC operating at 50Hz~1000Hz are presented.It is seen that the valve power loss of a MMC increased by 12,40 and 93%under 200Hz,500Hz and 1000Hz operating frequency.The article concludes that in a device with isolated inner AC system,MMC operating at higher frequency will be more competitive than typical 50Hz/60Hz MMC with moderate increase of operating power loss and significant reduction of the size of the AC components.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
Small modular reactor(SMR)belongs to the research forefront of nuclear reactor technology.Nowadays,advancement of intelligent control technologies paves a new way to the design and build of unmanned SMR.The autonomous...Small modular reactor(SMR)belongs to the research forefront of nuclear reactor technology.Nowadays,advancement of intelligent control technologies paves a new way to the design and build of unmanned SMR.The autonomous control process of SMR can be divided into three stages,say,state diagnosis,autonomous decision-making and coordinated control.In this paper,the autonomous state recognition and task planning of unmanned SMR are investigated.An operating condition recognition method based on the knowledge base of SMR operation is proposed by using the artificial neural network(ANN)technology,which constructs a basis for the state judgment of intelligent reactor control path planning.An improved reinforcement learning path planning algorithm is utilized to implement the path transfer decision-makingThis algorithm performs condition transitions with minimal cost under specified modes.In summary,the full range control path intelligent decision-planning technology of SMR is realized,thus provides some theoretical basis for the design and build of unmanned SMR in the future.展开更多
Lignans have been established as a privileged scaffold in drug discovery,particularly in anticancer and antioxidant properties.Concise and efficient construction of lignans and their derivatives in a single operation ...Lignans have been established as a privileged scaffold in drug discovery,particularly in anticancer and antioxidant properties.Concise and efficient construction of lignans and their derivatives in a single operation holds great medicinal significance for structure-activity relationship studies yet remains challenging.Drawing inspiration from the biosynthesis of lignans,we present a general,high-step-economy palladium-catalyzed reaction that converts simple chemical feedstocks into dehydrodibenzylbutyrolactone lignans through the in-situ construction and coupling of two phenylpropanoid molecules.The diversity of organoboronic acids and the editability of enyne provide a powerful platform for the rapid construction of lignan libraries,featuring 82 lignans analogs,collective syntheses of 10 distinct lignan skeletons,and 13 hybrid molecules combining pharmacophore fragments with drug and derivatives.The subtle combination of phosphine ligands with quinones for switching chemoselectivity is vital to the success of this protocol.展开更多
The modular design pattern revolutionizes the monolithic morphology of traditional spacecraft into the reconfigurable combination of modular units.However,due to the morphological changes,the effective takeover contro...The modular design pattern revolutionizes the monolithic morphology of traditional spacecraft into the reconfigurable combination of modular units.However,due to the morphological changes,the effective takeover control of the combination through multiple independent modules,including the controller and actuator modules,remains a challenge.In this paper,a robust takeover control scheme with high allocation accuracy,independent of precise inertia,is proposed for the reconfigurable combination in the presence of the inertia uncertainty,model parameters uncertainty,communication delay,and external disturbance.By reregulating the conditions for performance synthesis into a symmetric form with similar structure,a hybrid non-fragile H_(2)/H_(∞)controller is designed for handling two types of controller gain perturbations,achieving superior performance with less energy consumption through simultaneous perturbation suppression.Moreover,through temporarily storing the allocation signals in the initial stage to cover the upper bound of the communication delay,the proposed distributed dynamic allocation scheme enables the actuator modules to implement the control signals jointly to stabilize the combination.Distinguished from general allocators,the proposed high-precision allocation scheme under communication delay can not only ensure full exploitation of controller performance,but also dynamically adjust allocation coefficients based on energy consumption index of controller modules to prevent actuator saturation.Numerical simulations demonstrate the superiority of the proposed hybrid non-fragile controller and the allocation scheme.展开更多
Tetracycline(TC)residues from anthropogenic activities undesirably present in nature as an emerging sustainability challenge and thereby require innovations in remediation technologies.Herein,as inspired by the microc...Tetracycline(TC)residues from anthropogenic activities undesirably present in nature as an emerging sustainability challenge and thereby require innovations in remediation technologies.Herein,as inspired by the microcompartment structure in living organisms,we adopt a synthetic biology approach to engineer the FerTiG,a modular enzyme assembly,to robustly scavenge TC residues with improved performance.The FerTiG consists of three functional modules,namely,a TC degradation module(Tet(X4)),a cofactor recycling module glucose dehydrogenase(GDH),and a protection module(ferritin),to organize diverse catalytic processes simultaneously as a biological circuit.The incorporation of GDH suitably fuels the FerTiG-dependent TC degradation by regenerating expensive nicotinamide adenine dinucleotide phosphate(NADPH)cofactor with glucose.The ferritin shields the catalytic core of FerTiG to resiliently decompose TC under unfavorable conditions.Due to collaboration among functional modules,FerTiG strongly catalyzes the residual TC removal from multiple environmental matrices.The degradation pathways and environmental/biological safety of FerTiG are then elaborated,indicating the promising readiness for the application of FerTiG.In summary,this work presents a synthetic biology-based strategy to spontaneously impose residual antibiotic biodegradation for better sustainability management.The FerTiG is engineered as a proof-of-principle for TC removal;however,this'microcompartment-mimick ing'concept is of great interest in mitigating other sustainability challenges where modular catalytic machinery is applied.展开更多
This article focuses on the municipal prefabricated bathroom station.It elaborates on its modular design concept,including key design points such as spatial layout,functional modules,and determination of key parameter...This article focuses on the municipal prefabricated bathroom station.It elaborates on its modular design concept,including key design points such as spatial layout,functional modules,and determination of key parameters;introduces the optimization of intelligent production processes,precision control,and integration of construction technology,and also mentions the verification of full lifecycle applications and quality control;as well as emphasizes the importance of BIM+IoT platform and looks forward to the future.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
Based on the analysis and research of the airworthiness objective of integrated modular avionics system(IMA),and the characteristics of IMA system’s comprehensive and complex cross-linking with other airborne systems...Based on the analysis and research of the airworthiness objective of integrated modular avionics system(IMA),and the characteristics of IMA system’s comprehensive and complex cross-linking with other airborne systems,the extraction strategy of IMA system’s compliance flight test subjects and the selection method of IMA system’s compliance flight test parameters are proposed.The data analysis method based on the abnormal probability matrix of the IMA system is proposed for the first time,and the abnormal state information of the IMA system can be quickly identified.The compliance flight test of the IMA system is completed with limited flight test resources,which achieves the purpose of saving flight test sorties and improving flight test efficiency.This research has been successfully applied to the airworthiness certification flight test of a certain civil transport aircraft in China,and can provide technical support for the subsequent type flight test.展开更多
In clinical practice,the irregular shapes of traumas pose a significant challenge in rapidly manufacturing personalized scaffolds.To address these challenges,inspired by LEGO■ bricks,this study proposed a novel conce...In clinical practice,the irregular shapes of traumas pose a significant challenge in rapidly manufacturing personalized scaffolds.To address these challenges,inspired by LEGO■ bricks,this study proposed a novel concept of modular scaffolds and developed an innovative system based on machine vision for their rapid and intelligent assembly tailored to defect shapes.Trapezoidal interfaces effectively connect standardized bone units based on magnesium-doped silicate calcium,ensuring high stability of the modular scaffolds,with compressive strength up to 135 MPa and bending strength up to 17 MPa.Through self-developed defect recognition and reconstruction algorithms,defect recognition and personalized assembly schemes for bone scaffolds can be achieved autonomously.Modular scaffolds seamlessly integrate with surrounding bone tissue,promoting new bone growth,with no apparent differences compared to fully 3D printed integral scaffolds in the skull and femur repair experiments.In summary,the adoption of modular scaffolds not only integrates personalization and standardization but also satisfies the optimal treatment window.展开更多
With the increasing demand for secure infrastructure such as hydrogen refueling stations,chemical plants,and energy storage systems,the need for protective structures capable of withstanding close-in detonations has b...With the increasing demand for secure infrastructure such as hydrogen refueling stations,chemical plants,and energy storage systems,the need for protective structures capable of withstanding close-in detonations has become more critical.Existing design guidelines for protective walls(e.g.,UFC 3-340-02)primarily address mid-and far-field explosions,providing limited insights into near-field effects.Considering the effect of slight slopes(<40°)on reducing maximum reflected overpressure is deemed negligible.This study investigated the effectiveness of a reinforced concrete(RC)modular protection system(MPS)incorpo rating a diagonally tapered wall in attenuating re flected overpressures from closein detonations.Full-scale field experiments using a 51.3 kg TNT charge,representing the explosion energy of a typical hydrogen vessel rupture,demonstrated that a wall with a 7°slope significantly outperformed a vertical wall of equivalent concrete volume in terms of blast resistance.Observed structural responses included cracking,horizontal shear failure,and overturning.Complementary simulations using a validated computational fluid dynamics(CFD)model showed that the tapered wall reduced peak overpressure by 30%-40%compared to an equivalent vertical wall.This result highlights the potential of minor geometric modifications to enhance blast resilience.The tapered design effectively redirects incident blast waves,reducing localized damage while also conserving material,thus preserving modular benefits such as ease of transport and reusability.These findings suggest that diagonally tapered RC-based MPSs can offer a practical and resilient solution for industrial and military applications subject to near-field or sequential blast threats.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
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
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
基金National Key Research and Development Program of China,No.2019YFD1101304National Natural Science Foundation of China,No.52278059+1 种基金Natural Science Foundation of Hunan Province of China,No.2024JJ8316Hunan Provincial Innovation Foundation For Postgraduate,No.CX20250634。
文摘Urban spatial morphology(USM)optimization is critical to balancing biodiversity conservation and sustainable urbanization.However,previous studies predominantly focused on the socio-economic efficiency and static ecological metrics and rarely addressed the dynamic USM optimization across spatial scales.Here,we developed a multi-level ecological network(MEN)framework to resolve the tension between urban expansion and ecological integrity.By integrating the cost-weighted distance analysis with a hierarchical network transmission mechanism,we established a cross-scale spatial optimization system,which coordinated the regional ecological corridors and local habitat patches.Comparative experiments with conventional single-scale approaches and scenario simulations using the PLUS model show that the MEN framework had superior performance in three dimensions:(1)spatial governance:the primary-level network(peri-urban natural reserves)effectively contained urban sprawl,and the secondary-level network(intra-urban green corridors)mitigated habitat fragmentation and improved the built-environment;(2)scenario robustness:the model maintained an optimal compactness-loose balance in multiple development pathways;(3)landscape metrics:patch fragmentation decreased by 18.25%,and the internal landscape richness improved by 10.66%compared to the scenario without USM optimization.The findings provide new insight to establish a hierarchical ecological optimization framework as a nature-based spatial protocol to reconcile metropolitan growth with landscape sustainability.
基金supported by the National Natural Science Foundation of China(No.52090041).
文摘The influence of different solution and aging conditions on the microstructure,impact toughness,and crack initiation and propagation mechanisms of the novel α+β titanium alloy Ti6422 was systematically investigated.By adjusting the furnace cooling time after solution treatment and the aging temperature,Ti6422 alloy samples were developed with a multi-level lamellar microstructure,in-cluding microscaleαcolonies and α_(p) lamellae,as well as nanoscale α_(s) phases.Extending the furnace cooling time after solution treatment at 920℃ for 1 h from 240 to 540 min,followed by aging at 600℃ for 6 h,increased the α_(p) lamella content,reduced the α_(s) phase content,expanded theαcolonies and α_(p) lamellae size,and improved the impact toughness from 22.7 to 53.8 J/cm^(2).Additionally,under the same solution treatment,raising the aging temperature from 500 to 700℃ resulted in a decrease in the α_(s) phase content and a growth in the thickness of the α_(p) lamella and α_(s) phase.The impact toughness increased significantly with these changes.Samples with high α_(p) lamellae content or large α_(s) phase size exhibited high crack initiation and propagation energies.Impact deformation caused severe kinking of the α_(p) lamellae in crack initiation and propagation areas,leading to a uniform and high-density kernel average misorientation(KAM)distribu-tion,enhancing plastic deformation coordination and uniformity.Moreover,the multidirectional arrangement of coarserαcolonies and α_(p) lamellae continuously deflect the crack propagation direction,inhibiting crack propagation.
文摘In the references[4,11,12],the authors gave some modular forms overΓ^(0)(2).In this note,we proceed with the study of cancellation formulas relating to the modular forms.
基金sponsored by the National Natural Science Foundation of China(No.52075467)Hebei Province Fund Outstanding Youth Fund Project,China(No.E2024203107)。
文摘Modular truss space deployable antennas are key for future large aperture,high precision antennas,already proven in various in-orbit applications globally.This paper introduces a design method for a tetrahedral basic unit mechanism with dual height positioning nodes.A parametric model is established,and its DOF are analyzed to confirm the mechanism's validity.The new tetrahedral basic unit mechanism constructed by this method is a single DOF mechanism and can locate different parabolic node heights.In order to further adapt to the parabolic and large aperture requirements of the deployable antenna of the truss,a combination unit and modular unit mechanism are developed based on this tetrahedral unit.The DOF and deployment characteristics of the modular unit mechanism are analyzed and validated through simulations.Various networking methods for the modular units are proposed,followed by a comprehensive performance comparison of different modular truss deployable antenna mechanisms.A prototype model of the modular unit mechanism is also developed,with deployment experiments demonstrating the mechanism's simplicity,low DOF,and large deployment ratio.The findings of this study provide a theoretical and technical basis for the future design and development of truss deployable antenna mechanisms.
基金supported by the PowerChina Hubei Electric Engineering Corporation。
文摘There is no common accepted way for calculating the valve power loss of modular multilevel converter(MMC).Valve power loss estimation based on analytical calculation is inaccurate to address the switching power loss and valve power loss estimation based on detailed electro-magnetic simulation is of low speed.To solve this problem,a method of valve power loss estimation based on the detailed equivalent simulation model of MMC is proposed.Results of valve power loss analysis of 201-level 500MW MMC operating at 50Hz~1000Hz are presented.It is seen that the valve power loss of a MMC increased by 12,40 and 93%under 200Hz,500Hz and 1000Hz operating frequency.The article concludes that in a device with isolated inner AC system,MMC operating at higher frequency will be more competitive than typical 50Hz/60Hz MMC with moderate increase of operating power loss and significant reduction of the size of the AC components.
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.
文摘Small modular reactor(SMR)belongs to the research forefront of nuclear reactor technology.Nowadays,advancement of intelligent control technologies paves a new way to the design and build of unmanned SMR.The autonomous control process of SMR can be divided into three stages,say,state diagnosis,autonomous decision-making and coordinated control.In this paper,the autonomous state recognition and task planning of unmanned SMR are investigated.An operating condition recognition method based on the knowledge base of SMR operation is proposed by using the artificial neural network(ANN)technology,which constructs a basis for the state judgment of intelligent reactor control path planning.An improved reinforcement learning path planning algorithm is utilized to implement the path transfer decision-makingThis algorithm performs condition transitions with minimal cost under specified modes.In summary,the full range control path intelligent decision-planning technology of SMR is realized,thus provides some theoretical basis for the design and build of unmanned SMR in the future.
基金Financial support was provided by the State Key Laboratory of Pulp and Paper Engineering(No.2022PY01)the National Natural Science Foundation of China(Nos.22231002 and 21871095)the Key-Area Research and Development Program of Guangdong Province(No.2020B010188001)。
文摘Lignans have been established as a privileged scaffold in drug discovery,particularly in anticancer and antioxidant properties.Concise and efficient construction of lignans and their derivatives in a single operation holds great medicinal significance for structure-activity relationship studies yet remains challenging.Drawing inspiration from the biosynthesis of lignans,we present a general,high-step-economy palladium-catalyzed reaction that converts simple chemical feedstocks into dehydrodibenzylbutyrolactone lignans through the in-situ construction and coupling of two phenylpropanoid molecules.The diversity of organoboronic acids and the editability of enyne provide a powerful platform for the rapid construction of lignan libraries,featuring 82 lignans analogs,collective syntheses of 10 distinct lignan skeletons,and 13 hybrid molecules combining pharmacophore fragments with drug and derivatives.The subtle combination of phosphine ligands with quinones for switching chemoselectivity is vital to the success of this protocol.
基金co-supported by the National Natural Science Foundation of China(No.12372048)the China Postdoctoral Science Foundation(No.2023M742835)+3 种基金the Guangdong Basic and Applied Basic Research Foundation,China(No.2023A1515011421)the Aeronautical Science Foundation of China(No.2022Z004053001)the Fundamental Research Funds for the Central Universities,China(No.D5000210833)the Young Talent Fund of Association for Science and Technology in Shaanxi,China(No.20220509)。
文摘The modular design pattern revolutionizes the monolithic morphology of traditional spacecraft into the reconfigurable combination of modular units.However,due to the morphological changes,the effective takeover control of the combination through multiple independent modules,including the controller and actuator modules,remains a challenge.In this paper,a robust takeover control scheme with high allocation accuracy,independent of precise inertia,is proposed for the reconfigurable combination in the presence of the inertia uncertainty,model parameters uncertainty,communication delay,and external disturbance.By reregulating the conditions for performance synthesis into a symmetric form with similar structure,a hybrid non-fragile H_(2)/H_(∞)controller is designed for handling two types of controller gain perturbations,achieving superior performance with less energy consumption through simultaneous perturbation suppression.Moreover,through temporarily storing the allocation signals in the initial stage to cover the upper bound of the communication delay,the proposed distributed dynamic allocation scheme enables the actuator modules to implement the control signals jointly to stabilize the combination.Distinguished from general allocators,the proposed high-precision allocation scheme under communication delay can not only ensure full exploitation of controller performance,but also dynamically adjust allocation coefficients based on energy consumption index of controller modules to prevent actuator saturation.Numerical simulations demonstrate the superiority of the proposed hybrid non-fragile controller and the allocation scheme.
基金supported by the National Natural Science Foundation of China(32121004 and 32102720)the Guangzhou Science and Technology Plan Project(2024A04J6509)+3 种基金the National Key Research and Development Program of China(2023YFD1800100)the Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program(2019BT02N054)the Double First-Class Discipline Promotion Project(2023B10564003)the 111 Project(D20008)。
文摘Tetracycline(TC)residues from anthropogenic activities undesirably present in nature as an emerging sustainability challenge and thereby require innovations in remediation technologies.Herein,as inspired by the microcompartment structure in living organisms,we adopt a synthetic biology approach to engineer the FerTiG,a modular enzyme assembly,to robustly scavenge TC residues with improved performance.The FerTiG consists of three functional modules,namely,a TC degradation module(Tet(X4)),a cofactor recycling module glucose dehydrogenase(GDH),and a protection module(ferritin),to organize diverse catalytic processes simultaneously as a biological circuit.The incorporation of GDH suitably fuels the FerTiG-dependent TC degradation by regenerating expensive nicotinamide adenine dinucleotide phosphate(NADPH)cofactor with glucose.The ferritin shields the catalytic core of FerTiG to resiliently decompose TC under unfavorable conditions.Due to collaboration among functional modules,FerTiG strongly catalyzes the residual TC removal from multiple environmental matrices.The degradation pathways and environmental/biological safety of FerTiG are then elaborated,indicating the promising readiness for the application of FerTiG.In summary,this work presents a synthetic biology-based strategy to spontaneously impose residual antibiotic biodegradation for better sustainability management.The FerTiG is engineered as a proof-of-principle for TC removal;however,this'microcompartment-mimick ing'concept is of great interest in mitigating other sustainability challenges where modular catalytic machinery is applied.
文摘This article focuses on the municipal prefabricated bathroom station.It elaborates on its modular design concept,including key design points such as spatial layout,functional modules,and determination of key parameters;introduces the optimization of intelligent production processes,precision control,and integration of construction technology,and also mentions the verification of full lifecycle applications and quality control;as well as emphasizes the importance of BIM+IoT platform and looks forward to the future.
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.
文摘Based on the analysis and research of the airworthiness objective of integrated modular avionics system(IMA),and the characteristics of IMA system’s comprehensive and complex cross-linking with other airborne systems,the extraction strategy of IMA system’s compliance flight test subjects and the selection method of IMA system’s compliance flight test parameters are proposed.The data analysis method based on the abnormal probability matrix of the IMA system is proposed for the first time,and the abnormal state information of the IMA system can be quickly identified.The compliance flight test of the IMA system is completed with limited flight test resources,which achieves the purpose of saving flight test sorties and improving flight test efficiency.This research has been successfully applied to the airworthiness certification flight test of a certain civil transport aircraft in China,and can provide technical support for the subsequent type flight test.
基金supported by the Zhejiang Provincial Natural Science Foundation of China(LY22E050011)National Natural Science Foundation of China(T2121004,51805475)。
文摘In clinical practice,the irregular shapes of traumas pose a significant challenge in rapidly manufacturing personalized scaffolds.To address these challenges,inspired by LEGO■ bricks,this study proposed a novel concept of modular scaffolds and developed an innovative system based on machine vision for their rapid and intelligent assembly tailored to defect shapes.Trapezoidal interfaces effectively connect standardized bone units based on magnesium-doped silicate calcium,ensuring high stability of the modular scaffolds,with compressive strength up to 135 MPa and bending strength up to 17 MPa.Through self-developed defect recognition and reconstruction algorithms,defect recognition and personalized assembly schemes for bone scaffolds can be achieved autonomously.Modular scaffolds seamlessly integrate with surrounding bone tissue,promoting new bone growth,with no apparent differences compared to fully 3D printed integral scaffolds in the skull and femur repair experiments.In summary,the adoption of modular scaffolds not only integrates personalization and standardization but also satisfies the optimal treatment window.
基金supported by the Dong-A University of the Republic of Korea research fund。
文摘With the increasing demand for secure infrastructure such as hydrogen refueling stations,chemical plants,and energy storage systems,the need for protective structures capable of withstanding close-in detonations has become more critical.Existing design guidelines for protective walls(e.g.,UFC 3-340-02)primarily address mid-and far-field explosions,providing limited insights into near-field effects.Considering the effect of slight slopes(<40°)on reducing maximum reflected overpressure is deemed negligible.This study investigated the effectiveness of a reinforced concrete(RC)modular protection system(MPS)incorpo rating a diagonally tapered wall in attenuating re flected overpressures from closein detonations.Full-scale field experiments using a 51.3 kg TNT charge,representing the explosion energy of a typical hydrogen vessel rupture,demonstrated that a wall with a 7°slope significantly outperformed a vertical wall of equivalent concrete volume in terms of blast resistance.Observed structural responses included cracking,horizontal shear failure,and overturning.Complementary simulations using a validated computational fluid dynamics(CFD)model showed that the tapered wall reduced peak overpressure by 30%-40%compared to an equivalent vertical wall.This result highlights the potential of minor geometric modifications to enhance blast resilience.The tapered design effectively redirects incident blast waves,reducing localized damage while also conserving material,thus preserving modular benefits such as ease of transport and reusability.These findings suggest that diagonally tapered RC-based MPSs can offer a practical and resilient solution for industrial and military applications subject to near-field or sequential blast threats.
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.
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.
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.
