To address the challenges of insufficient visualization in the industrial robot assembly operation system and the limitation of visualizing only geometric attributes of physical properties,a method is proposed for con...To address the challenges of insufficient visualization in the industrial robot assembly operation system and the limitation of visualizing only geometric attributes of physical properties,a method is proposed for constructing an industrial robot assembly system based on virtual reality technology.Focusing on the shaft hole assembly,the mechanical characteristics of the industrial robot shaft hole assembly process are analyzed and a dynamic model is established for shaft hole assembly operations.The key elements of virtual assembly operations for industrial robots are summarized and a five-dimensional model is proposed for industrial robot virtual operations.Utilizing the Unity3D engine based on the 5-D model for industrial robot virtual operations,an industrial robot shaft hole assembly system is developed.This system enables virtual assembly operations,displays physical attributes,and provides valuable references for the research of virtual systems.展开更多
Porous titanium(Ti)scaffolds have been extensively utilized as bone substitute scaffolds due to their superior biocompatibility and excellent mechanical properties.However,naturally formed TiO2 on the surface limits f...Porous titanium(Ti)scaffolds have been extensively utilized as bone substitute scaffolds due to their superior biocompatibility and excellent mechanical properties.However,naturally formed TiO2 on the surface limits fast osseointegration.Different biomolecules have been widely utilized to overcome this issue;however,homogeneous porous Ti scaffolds could not simultaneously deliver multiple biomolecules that have different release behaviors.In this study,functionally graded porous Ti scaffolds(FGPTs)with dense inner and porous outer parts were fabricated using a two-body combination and densification procedure.FGPTs with growth factor(BMP-2)and antibiotics(TCH)exhibited suitable mechanical properties as bone substituting material and presented good structural stability.The release of BMP-2 was considerably prolonged,whereas the release of TCH was comparable to that of homogenous porous titanium scaffolds(control group).The osteogenic differentiation obtained using FGPTs was maintained due to the prolonged release of BMP-2.The antimicrobial properties of these scaffolds were verified using S.aureus in terms of prior release time.In addition,various candidates for graded porous Ti scaffolds with altered pore characteristics were presented.展开更多
Assembly errors have great influence on assembly quality in robotic assembly systems. Error analysis is directed to the propagations and accumula-tions of various errors and their effect on assembly success.Using the ...Assembly errors have great influence on assembly quality in robotic assembly systems. Error analysis is directed to the propagations and accumula-tions of various errors and their effect on assembly success.Using the screw coordinates, assembly errors are represented as 'error twist', the extremely compact expression. According to the law of screw composition, relative position and orientation errors of mating parts are computed and the necessary condition of assembly success is concluded. A new simple method for measuring assembly errors is also proposed based on the transformation law of a screw.Because of the compact representation of error, the model presented for error analysis can be applied to various part- mating types and especially useful for error analysis of complexity assembly.展开更多
Today＇s production systems are demanded to exhibit an increased flexibility and mutability in order to deal with dynamically changing conditions, objectives and an increasing number of product variants within industr...Today＇s production systems are demanded to exhibit an increased flexibility and mutability in order to deal with dynamically changing conditions, objectives and an increasing number of product variants within industrial turbulent environments. Flexible automated systems are requested in order to improve dynamic production efficiency, e.g. robot-based hardware and PC-based controllers, but these usually induce a significantly higher production complexity, whereby the efforts for planning and programming, but also setups and reconfiguration, expand. In this paper a definition and some concepts of self-optimizing assembly systems are presented to describe possible ways to reduce the planning efforts in complex production systems. The concept of self-optimization in assembly systems will be derived from a theoretical approach and will be transferred to a specific application scenario---the automated assembly of a miniaturized solid state laser--where the challenges of unpredictable influences from e.g. component tolerances can be overcome by the help of self-optimization.展开更多
Product assembly occupies an extremely important position in the whole production process of products. At present, due to the growing demand of consumers for personalized and customized products, the traditional manua...Product assembly occupies an extremely important position in the whole production process of products. At present, due to the growing demand of consumers for personalized and customized products, the traditional manual assembly method is inefficient, and pure automatic assembly is difficult and costly, which is difficult to meet the production needs of enterprises. Therefore, the intelligent assembly system of human-computer integration arises at the historic moment and realizes high-quality and high-efficiency product assembly.展开更多
Presents a multi robot cooperative assembly system (MRCAS) which is composed of an organizer computer, three industrial robots, PUMA 562 mounted on an omni directional vehicle, PUMA 760 and Adept I and organized into ...Presents a multi robot cooperative assembly system (MRCAS) which is composed of an organizer computer, three industrial robots, PUMA 562 mounted on an omni directional vehicle, PUMA 760 and Adept I and organized into a hierarchical structure with the cooperation organization on the top and the coordination motion at the bottom to solve the main problem of coordination and cooperation among robots, and concludes with experimental results that MRCAS is reconfigurable and adaptable as the mission changes.展开更多
Targeted protein degradation(TPD)is an innovative strategy for selectively eliminating pathogenic proteins,enabling precise degradation of once-undruggable targets in cancer therapy.However,current TPD molecules are o...Targeted protein degradation(TPD)is an innovative strategy for selectively eliminating pathogenic proteins,enabling precise degradation of once-undruggable targets in cancer therapy.However,current TPD molecules are often limited by poor tumor targeting and the need for high doses.To overcome these limitations,assembly/disassembly-based TPD systems have been proposed to effectively degrade proteins of interest and enhance therapeutic efficacy.Herein,we summarize the recent advances in such TPD systems and categorize the strategies employed,including nanosphere morphology of assembled TPD systems,nanofiber morphology of assembled TPD systems,carrier-mediated TPD release systems,and stimulus-induced free TPD molecule formation nanosystems.Finally,we outline future directions and identify the remaining challenges in assembly/disassembly-based TPD systems.展开更多
With the increasing concerns about energy consumption and environmental protection, minimizing energy consumption while ensuring desired productivity becomes more and more important in flexible assembly systems(FASs) ...With the increasing concerns about energy consumption and environmental protection, minimizing energy consumption while ensuring desired productivity becomes more and more important in flexible assembly systems(FASs) design and operation. However, because of the complexity of deadlock-prone FASs, only a few researchers have addressed their scheduling problems. Besides, no existing literature in the field of scheduling of deadlock-prone FASs takes energy consumption minimization as the optimization criterion to our best knowledge. This paper presents an A^(*)-based hybrid heuristic search algorithm to minimize the total energy consumption of FASs with tool change processes. Based on a developed Petri net(PN) model, two energy functions are proposed to calculate the energy consumption of FASs. To achieve better performance, six new heuristic functions are designed to guide the search process by considering the features of FASs. Besides, two selection functions are proposed to evaluate the prospects of vertexes and choose the promising ones.Moreover, a dynamic window is applied in the algorithm to limit the search space, and a deadlock prevention policy is used to ensure feasible schedules. Experimental results show that the proposed algorithm can effectively find feasible schedules for FASs,and a well-designed heuristic function is likely to obtain schedules to meet industrial application requirements.展开更多
Microorganisms can colonize the surface of microplastics(MPs)to form a distinctive microbiome,known as a“plastisphere”which is regarded as an anthropogenic niche for microbial growth.However,bacterial community asse...Microorganisms can colonize the surface of microplastics(MPs)to form a distinctive microbiome,known as a“plastisphere”which is regarded as an anthropogenic niche for microbial growth.However,bacterial community assembly in virgin and aging MP plastispheres across different habitats is poorly understood.This study aims to assess the variations in bacterial community assembly across different niches and habitats with an in situ ex-periment,in which constructed forest wetland(FW),natural lake wetland(LW),and lotus pond wetland(LP)were habitats,and plastispheres of virgin and aging low-density polyethylene(LDPE)MPs,as well as surround-ing wetland soils were niches.Significant niche-related differences in bacterial communities were observed,with lower diversity and enrichment of potential plastic-degrading bacteria in the plastisphere than in the soil bacterial communities.Furthermore,habitat-related differences exerted a more pronounced influence on the beta-diversity patterns of the bacterial communities.The linear regression analyses indicated that the local species pool con-tributed more to bacterial community assembly in the LW wetland,whereas the relative abundance of species was the primary factor in the LP wetland.The null model analysis indicated that plastisphere bacterial communi-ties were predominantly driven by the stochastic process,with a more deterministic assembly observed in the LP wetland and soil bacterial communities.Additionally,the primary ecological process shaping plastisphere com-munities shifted from drift in the virgin LDPE to homogenising dispersal in the aging LDPE.This study provides new insights into the fate and ecological impacts of MPs in wetlands,thereby facilitating the effective regulations of plastic pollution.展开更多
Ecological floating bed is an important biological remediation method for water pollution control.During the removal of excess nutrients and pollutants,changes in environmental factors affect the characteristics of mi...Ecological floating bed is an important biological remediation method for water pollution control.During the removal of excess nutrients and pollutants,changes in environmental factors affect the characteristics of microorganisms in aquatic ecosystems.To understand the influences of ecological floating beds on size-fractionated microorganisms,we investigated the community assembly and nitrogen metabolic characteristics of three size-fractionated microorganism groups in the ecological floating bed area,using 18S rDNA,16S rDNA metabarcoding,and metagenomic sequencing techniques.Firstly,we discovered substantial differences between size-fractionated groups in the diversity and compositions of both microeukaryotic and bacterial communities,as well as the influences of floating beds on specific groups.The floating beds appeared to provide more habitats for heterotrophs and symbiotes while potentially inhibiting the growth of certain phytoplankton(cyanobacteria).Secondly,we observed that microeukaryotic and bacterial communities were predominantly influenced by stochastic and deterministic processes,respectively,and they both exhibited distinct patterns across different size-fractionated groups.Notably,microeukaryotic community assembly demonstrated a greater sensitivity to ecological floating beds,as indicated by an increase in dispersal limitation processes.Finally,the nitrogen metabolism functional genes revealed that microbes associated with large-sized particles played a crucial role in dissimilatory nitrate reduction to ammonium(DNRA)and denitrification processes within the floating bed area,thereby facilitating the removal of excess nitrogen nutrients from the water.In contrast,freeliving microorganisms from small-sized groups were linked mainly to the genes involved in nitrogen assimilation and assimilatory nitrate reduction to ammonium(ANRA)processes.These findings help understand the impact of ecological floating beds on the diversity and functional characteristics of microorganism communities in different size-fractionated groups.展开更多
Gold nanoclusters(AuNCs)are ultrasmall(<2 nm)aggregates of gold atoms that exhibit discrete electronic states,size-dependent photoluminescence,and exceptional biocompatibility,making them ideal candidates for thera...Gold nanoclusters(AuNCs)are ultrasmall(<2 nm)aggregates of gold atoms that exhibit discrete electronic states,size-dependent photoluminescence,and exceptional biocompatibility,making them ideal candidates for theranostic applications.Their tunable surface chemistry enables targeted delivery,while strong near-infrared emission and environmental responsiveness allow for sensitive detection and deep-tissue imaging.Recent advances have revealed that controlled assembly of AuNCs into higher-order architectures-guided by biological scaffolds such as nucleic acids,peptides,and proteins-can markedly enhance their optical and electronic properties through aggregation-induced emission(AiE)and stabilization of surface ligands.This review summarizes recent progress in the design and biomedical applications of AuNC assemblies generated using biomolecules as structure-directing scaffolds.Covalent and noncovalent interactions with biomolecules enable the formation of well-defined one-,two-,and three-dimensional structures with tunable morphologies and sizes.These assemblies display distinctive photophysical behaviors that have been exploited for biosensing,bioimaging,and therapeutic applications in both cellular and in vivo models.Compared with individual AuNCs,assembled systems offer improved uptake,prolonged circulation,and efficient clearance,while protecting labile cargos such as nucleic acids and proteins.Moreover,their ordered and defined architectures can be engineered for controlled drug release and synergistic photo-or radiotherapeutic effects.Despite these advances,fundamental understanding of how structural organization governs photophysical responses remains limited.Elucidating parameters such as intercluster spacing and loading density will be essential for optimizing performance.Overall,biologically guided AuNC assemblies represent a powerful platform for multifunctional biosensing and therapy,bridging nanoscale design with biological function.展开更多
IR64 is an elite Xian/indica variety developed by International Rice Research Institute(IRRl)in 1985,which has been the most widely grown variety and core breeding parent in South/Southeast Asia(Mackill and Khush,2018...IR64 is an elite Xian/indica variety developed by International Rice Research Institute(IRRl)in 1985,which has been the most widely grown variety and core breeding parent in South/Southeast Asia(Mackill and Khush,2018).IR64 has been utilized to develop stress-tolerant(such as drought-adapted and submergenceresistant)near-isogenic lines,underscoring its great potential in agricultural genomics(Tanaka et al.,2020).展开更多
Fungi play crucial roles in nutrient acquisition,plant growth promotion,and the enhancement of resistance to both abiotic and biotic stresses.However,studies on the fungal communities associated with peas (Pisum sativ...Fungi play crucial roles in nutrient acquisition,plant growth promotion,and the enhancement of resistance to both abiotic and biotic stresses.However,studies on the fungal communities associated with peas (Pisum sativum L.) remain limited.In this study,we systematically investigated the ecological effects of host niches (soil,root,stem,leaf,and pod) and genotypes on the diversity and composition of fungal communities in peas using a multi-level approach that encompassed pattern recognition (β-diversity decomposition),mechanism validation (neutral community model testing),and dynamic tracking methods (migration pathway source-tracking).The results revealed that the dominant fungal phyla across niches and genotypes were Ascomycota,Basidiomycota,and Mortierellomycota,and the community structures of the soil–plant continuum were primarily determined by the pea niches rather than genotypes.β-diversity decomposition was largely attributed to species replacement rather than richness differences,indicating strong niche specificity and microbial replacement across microhabitats.Neutral model analysis revealed that stochastic processes influenced genotypeassociated communities,while deterministic processes played a dominant role in niche-based community assembly.Source-tracking analysis identified niche-to-niche fungal migration,with Erysiphe,Fusarium,Cephaliophora,Ascobolus,Alternaria,and Aspergillus as the key genera.Migration rates from exogenous to endogenous niches were low (1.3–61.5%),whereas those within exogenous (64.4–83.7%) or endogenous (73.9–96.4%) compartments were much higher,suggesting that the pea epidermis acts as a selective barrier that filters and enriches microbial communities prior to internal colonization.This study provides comprehensive insights into the mechanisms of host filtering,enrichment and microbial sourcing,which increases our understanding of the assembly rules of the pea-associated fungal microbiome.展开更多
Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone t...Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone to errors and lacks consistency,emphasizing the need for a reliable and automated inspection system.Leveraging both object detection and image segmentation approaches,this research proposes a vision-based solution for the detection of various kinds of tools in the toolkit using deep learning(DL)models.Two Intel RealSense D455f depth cameras were arranged in a top down configuration to capture both RGB and depth images of the toolkits.After applying multiple constraints and enhancing them through preprocessing and augmentation,a dataset consisting of 3300 annotated RGB-D photos was generated.Several DL models were selected through a comprehensive assessment of mean Average Precision(mAP),precision-recall equilibrium,inference latency(target≥30 FPS),and computational burden,resulting in a preference for YOLO and Region-based Convolutional Neural Networks(R-CNN)variants over ViT-based models due to the latter’s increased latency and resource requirements.YOLOV5,YOLOV8,YOLOV11,Faster R-CNN,and Mask R-CNN were trained on the annotated dataset and evaluated using key performance metrics(Recall,Accuracy,F1-score,and Precision).YOLOV11 demonstrated balanced excellence with 93.0%precision,89.9%recall,and a 90.6%F1-score in object detection,as well as 96.9%precision,95.3%recall,and a 96.5%F1-score in instance segmentation with an average inference time of 25 ms per frame(≈40 FPS),demonstrating real-time performance.Leveraging these results,a YOLOV11-based windows application was successfully deployed in a real-time assembly line environment,where it accurately processed live video streams to detect and segment tools within toolkits,demonstrating its practical effectiveness in industrial automation.The application is capable of precisely measuring socket dimensions by utilising edge detection techniques on YOLOv11 segmentation masks,in addition to detection and segmentation.This makes it possible to do specification-level quality control right on the assembly line,which improves the ability to examine things in real time.The implementation is a big step forward for intelligent manufacturing in the Industry 4.0 paradigm.It provides a scalable,efficient,and accurate way to do automated inspection and dimensional verification activities.展开更多
Aircraft assembly is characterized by stringent precedence constraints,limited resource availability,spatial restrictions,and a high degree of manual intervention.These factors lead to considerable variability in oper...Aircraft assembly is characterized by stringent precedence constraints,limited resource availability,spatial restrictions,and a high degree of manual intervention.These factors lead to considerable variability in operator workloads and significantly increase the complexity of scheduling.To address this challenge,this study investigates the Aircraft Pulsating Assembly Line Scheduling Problem(APALSP)under skilled operator allocation,with the objective of minimizing assembly completion time.A mathematical model considering skilled operator allocation is developed,and a Q-Learning improved Particle Swarm Optimization algorithm(QLPSO)is proposed.In the algorithm design,a reverse scheduling strategy is adopted to effectively manage large-scale precedence constraints.Moreover,a reverse sequence encoding method is introduced to generate operation sequences,while a time decoding mechanism is employed to determine completion times.The problem is further reformulated as a Markov Decision Process(MDP)with explicitly defined state and action spaces.Within QLPSO,the Q-learning mechanism adaptively adjusts inertia weights and learning factors,thereby achieving a balance between exploration capability and convergence performance.To validate the effectiveness of the proposed approach,extensive computational experiments are conducted on benchmark instances of different scales,including small,medium,large,and ultra-large cases.The results demonstrate that QLPSO consistently delivers stable and high-quality solutions across all scenarios.In ultra-large-scale instances,it improves the best solution by 25.2%compared with the Genetic Algorithm(GA)and enhances the average solution by 16.9%over the Q-learning algorithm,showing clear advantages over the comparative methods.These findings not only confirm the effectiveness of the proposed algorithm but also provide valuable theoretical references and practical guidance for the intelligent scheduling optimization of aircraft pulsating assembly lines.展开更多
Adjuvants enhance and prolong the immune response to therapeutic agents,such as drugs and vaccines.However,conventional adjuvants have limitations in terms of immune specificity and duration.Nanoadjuvants can leverage...Adjuvants enhance and prolong the immune response to therapeutic agents,such as drugs and vaccines.However,conventional adjuvants have limitations in terms of immune specificity and duration.Nanoadjuvants can leverage their nanoscale size to increase the capture efficacy of antigens by antigen-presenting cells and improve immunogen presentation for targeted delivery.Furthermore,noninvasive visualization of bifunctional nanoadjuvants with integrated efficacy and imaging postdelivery can provide insights into in vivo distribution and performance,aiding in the optimization and design of new dosage forms.This review systematically summarizes the structure,assembly,and function of nanoadjuvants alongside contrast agents.It delves into the impact of complex structures formed by nanoadjuvant-contrast agent interactions on antigen presentation,migration,imaging tracking,and visualization of immune cell recruitment.It also discusses how imaging can determine optimal immune intervals,vaccine safety,and toxicity while enabling diagnostic and therapeutic integration.Moreover,this paper discusses potential applications of novel adjuvants and promising imaging technologies that could have implications for future vaccine and drug development endeavors.展开更多
Legume-based intercropping enhances asymbiotic biological nitrogen fixation(BNF);however,the underlying mechanisms remain unclear,including the roles of soil keystone diazotroph taxa with varying niche breadths.A fiel...Legume-based intercropping enhances asymbiotic biological nitrogen fixation(BNF);however,the underlying mechanisms remain unclear,including the roles of soil keystone diazotroph taxa with varying niche breadths.A field experiment was conducted to evaluate soil BNF variations between rhizosphere and bulk soils in peanut/cotton intercropping systems and monocultures.BNF activities were measured by nitrogen fixation rates,nitrogenase activity,and nifH gene abundance.Phylogenetic null models,co-occurrence networks,and niche breadth analysis were applied to investigate the roles of diazotrophic keystone taxa and their ecological niches.Rhizosphere soils exhibited 7.8–125.5%higher BNF potentials than bulk soils,whereas intercropping systems showed 11.6–323.0%increases over monocultures for nitrogen fixation rate,nitrogenase activity,and nifH gene abundance(all P<0.05).Diazotrophic community composition and diversity differed significantly,with Proteobacteria(excluding Alphaproteobacteria)enriched in intercropping and rhizosphere soils,while Cyanobacteria and Firmicutes were less abundant.Deterministic processes,particularly heterogeneous selection,dominated community assembly in the rhizosphere(91.9%)and intercropping soils(86.3%).The co-occurrence networks consistently revealed more complex and interconnected communities in intercropping and rhizosphere soils that were dominated by opportunistic diazotrophs(78.8–85.9%),followed by specialists(10.2–18.5%)and generalists(1.38–3.80%).Keystone taxa,including opportunists such as Azoarcus,Azohydromonas,and Steroidobacter,and generalists like Pseudomonas and Azotobacter,correlated positively with microbial biomass carbon and nitrate nitrogen,contributing to enhanced BNF.Peanut/cotton intercropping enhances BNF by selectively enriching the keystone diazotrophic taxa with varying ecological roles,particularly opportunists and generalists.Such targeted intercropping strategies can optimize BNF,improve soil fertility,and promote sustainable agricultural production.展开更多
Lattice-type ultra-tall wind turbine towers are popular in China for their modular benefits in fabrication,transportation,and installation.Nonetheless,their conceptual design remains predominantly dependent on enginee...Lattice-type ultra-tall wind turbine towers are popular in China for their modular benefits in fabrication,transportation,and installation.Nonetheless,their conceptual design remains predominantly dependent on engineering experience,and a generally applicable approach is still absent.This study proposes a self-similar modular topology optimization framework for lattice-type wind turbine support structures and develops software for its application.A minimum weighted compliance formulation with a prescribed volume fraction is developed utilizing the variable density approach,wherein modular constraints and their corresponding sensitivity expressions are explicitly included.The method is applied to a reference wind turbine model to generate modular lattice configurations.The novel structural models are evaluated under three representative design load cases outlined in IEC 61400 by finite element analysis.Compared with the reference structure,the 12-layer self-similar modular design reduces the maximum deformation and von Mises stress by 39.5%and 51.1%,respectively,demonstrating a substantial stiffness improvement while preserving modularity.The suggested approach provides an efficient and practical tool for the conceptual design of modular lattice-type wind turbine towers.展开更多
Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Althoug...Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Although adversarial examples can strategically undermine the accuracy of BCSD models and protect critical code,existing techniques predominantly depend on inserting artificial instructions,which incur high computational costs and offer limited diversity of perturbations.To address these limitations,we propose AIMA,a novel gradient-guided assembly instruction relocation method.Our method decouples the detection model into tokenization,embedding,and encoding layers to enable efficient gradient computation.Since token IDs of instructions are discrete and nondifferentiable,we compute gradients in the continuous embedding space to evaluate the influence of each token.The most critical tokens are identified by calculating the L2 norm of their embedding gradients.We then establish a mapping between instructions and their corresponding tokens to aggregate token-level importance into instructionlevel significance.To maximize adversarial impact,a sliding window algorithm selects the most influential contiguous segments for relocation,ensuring optimal perturbation with minimal length.This approach efficiently locates critical code regions without expensive search operations.The selected segments are relocated outside their original function boundaries via a jump mechanism,which preserves runtime control flow and functionality while introducing“deletion”effects in the static instruction sequence.Extensive experiments show that AIMA reduces similarity scores by up to 35.8%in state-of-the-art BCSD models.When incorporated into training data,it also enhances model robustness,achieving a 5.9%improvement in AUROC.展开更多
The computer numerical control（CNC） system is suited to control varied types of flexible fixtures in aircraft component manufacturing and assembly. The mechanisms and control requirements of flexible fixtures are pr...The computer numerical control（CNC） system is suited to control varied types of flexible fixtures in aircraft component manufacturing and assembly. The mechanisms and control requirements of flexible fixtures are presented and analyzed. The hardware and software architecture and implementation of CNC system are pro- posed. The flexible fixture mechanism is described using configuration parameters. According to the parameters, the CNC system automatically generates the control feature and the human machine interface （HMI） operation function. The CNC system is implemented in a flexible fixture for skin-strlnger assembly, and results show the effectiveness of the system.展开更多
基金Sponsored by the National Natural Science Foundation of China(Grant No.52005003)the Science and Technology Planning Project of Wuhu City(Grant No.2022jc41)。
文摘To address the challenges of insufficient visualization in the industrial robot assembly operation system and the limitation of visualizing only geometric attributes of physical properties,a method is proposed for constructing an industrial robot assembly system based on virtual reality technology.Focusing on the shaft hole assembly,the mechanical characteristics of the industrial robot shaft hole assembly process are analyzed and a dynamic model is established for shaft hole assembly operations.The key elements of virtual assembly operations for industrial robots are summarized and a five-dimensional model is proposed for industrial robot virtual operations.Utilizing the Unity3D engine based on the 5-D model for industrial robot virtual operations,an industrial robot shaft hole assembly system is developed.This system enables virtual assembly operations,displays physical attributes,and provides valuable references for the research of virtual systems.
基金supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT)(Nos. 2021R1I1A1A01043176 and2021R1A2C1091301)the framework of international cooperation program managed by the National Research Foundation of Korea (No.2021K2A9A2A06037540)+3 种基金Korean Fund for Regenerative Medicine funded by Ministry of Science and ICTMinistry of Health and Welfare (No. 2021M3E5E5096420, Republic of Korea)Korea Medical Device Development Fund grant funded by the Korea government(the Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health&Welfare, Republic of Korea, the Ministry of Food and Drug Safety)(Project Number:202011B29)the GRRC program of the Gyeo nggi Province (Grant Number GRRC-KPU2021-A01, Multi-material Machining Innovative Technology Research Center)
文摘Porous titanium(Ti)scaffolds have been extensively utilized as bone substitute scaffolds due to their superior biocompatibility and excellent mechanical properties.However,naturally formed TiO2 on the surface limits fast osseointegration.Different biomolecules have been widely utilized to overcome this issue;however,homogeneous porous Ti scaffolds could not simultaneously deliver multiple biomolecules that have different release behaviors.In this study,functionally graded porous Ti scaffolds(FGPTs)with dense inner and porous outer parts were fabricated using a two-body combination and densification procedure.FGPTs with growth factor(BMP-2)and antibiotics(TCH)exhibited suitable mechanical properties as bone substituting material and presented good structural stability.The release of BMP-2 was considerably prolonged,whereas the release of TCH was comparable to that of homogenous porous titanium scaffolds(control group).The osteogenic differentiation obtained using FGPTs was maintained due to the prolonged release of BMP-2.The antimicrobial properties of these scaffolds were verified using S.aureus in terms of prior release time.In addition,various candidates for graded porous Ti scaffolds with altered pore characteristics were presented.
基金This work is Supported by the National Science Foundation under Grant 863 -512 -9820-04.
文摘Assembly errors have great influence on assembly quality in robotic assembly systems. Error analysis is directed to the propagations and accumula-tions of various errors and their effect on assembly success.Using the screw coordinates, assembly errors are represented as 'error twist', the extremely compact expression. According to the law of screw composition, relative position and orientation errors of mating parts are computed and the necessary condition of assembly success is concluded. A new simple method for measuring assembly errors is also proposed based on the transformation law of a screw.Because of the compact representation of error, the model presented for error analysis can be applied to various part- mating types and especially useful for error analysis of complexity assembly.
文摘Today＇s production systems are demanded to exhibit an increased flexibility and mutability in order to deal with dynamically changing conditions, objectives and an increasing number of product variants within industrial turbulent environments. Flexible automated systems are requested in order to improve dynamic production efficiency, e.g. robot-based hardware and PC-based controllers, but these usually induce a significantly higher production complexity, whereby the efforts for planning and programming, but also setups and reconfiguration, expand. In this paper a definition and some concepts of self-optimizing assembly systems are presented to describe possible ways to reduce the planning efforts in complex production systems. The concept of self-optimization in assembly systems will be derived from a theoretical approach and will be transferred to a specific application scenario---the automated assembly of a miniaturized solid state laser--where the challenges of unpredictable influences from e.g. component tolerances can be overcome by the help of self-optimization.
文摘Product assembly occupies an extremely important position in the whole production process of products. At present, due to the growing demand of consumers for personalized and customized products, the traditional manual assembly method is inefficient, and pure automatic assembly is difficult and costly, which is difficult to meet the production needs of enterprises. Therefore, the intelligent assembly system of human-computer integration arises at the historic moment and realizes high-quality and high-efficiency product assembly.
文摘Presents a multi robot cooperative assembly system (MRCAS) which is composed of an organizer computer, three industrial robots, PUMA 562 mounted on an omni directional vehicle, PUMA 760 and Adept I and organized into a hierarchical structure with the cooperation organization on the top and the coordination motion at the bottom to solve the main problem of coordination and cooperation among robots, and concludes with experimental results that MRCAS is reconfigurable and adaptable as the mission changes.
基金supported by National Natural Science Foundation of China(Grant 22407024)the Star-up Research Fund of Southeast University(RF1028624094)(X.W.)+7 种基金the China Postdoctoral Science Foundation(Grant 2025M772911)Natural Science Foundation of Jiangsu Province(Grants BK20251303)(X.L.)Postdoctoral Fellowship Program of CPSF(Grant GZC20251914)(X.L.)Jiangsu Funding Program for Excellent Postdoctoral Talent(Grant 2025ZB052)(X.L.)National Natural Science Foundation of China(Grant 22234002)(G.L.)National Key Research and Development Program of China(Grant 2023YFF0724100)(G.L.)Natural Science Foundation of Jiangsu Province(Grant BK20232007)(G.L.)Jiangsu ShuangChuang Team(Grant JSSCTD202409)(G.L.and X.W.).
文摘Targeted protein degradation(TPD)is an innovative strategy for selectively eliminating pathogenic proteins,enabling precise degradation of once-undruggable targets in cancer therapy.However,current TPD molecules are often limited by poor tumor targeting and the need for high doses.To overcome these limitations,assembly/disassembly-based TPD systems have been proposed to effectively degrade proteins of interest and enhance therapeutic efficacy.Herein,we summarize the recent advances in such TPD systems and categorize the strategies employed,including nanosphere morphology of assembled TPD systems,nanofiber morphology of assembled TPD systems,carrier-mediated TPD release systems,and stimulus-induced free TPD molecule formation nanosystems.Finally,we outline future directions and identify the remaining challenges in assembly/disassembly-based TPD systems.
基金supported in part by the National Natural Science Foundation of China(62003265)2023 Suzhou Innovation and Entrepreneurship Leading Talents Program (Young Innovative Leading Talents)(ZXL2023178)+2 种基金Natural Science Basic Research Program of Shaanxi (2025JC-YBMS-656)Tongxiang Institute of Artificial General Intelligence (TAGI2-A-2024-0006)the Deanship of Scientific Research (DSR) at King Abdulaziz University,Jeddah,Saudi Arabia (GPIP:908-135-2024)
文摘With the increasing concerns about energy consumption and environmental protection, minimizing energy consumption while ensuring desired productivity becomes more and more important in flexible assembly systems(FASs) design and operation. However, because of the complexity of deadlock-prone FASs, only a few researchers have addressed their scheduling problems. Besides, no existing literature in the field of scheduling of deadlock-prone FASs takes energy consumption minimization as the optimization criterion to our best knowledge. This paper presents an A^(*)-based hybrid heuristic search algorithm to minimize the total energy consumption of FASs with tool change processes. Based on a developed Petri net(PN) model, two energy functions are proposed to calculate the energy consumption of FASs. To achieve better performance, six new heuristic functions are designed to guide the search process by considering the features of FASs. Besides, two selection functions are proposed to evaluate the prospects of vertexes and choose the promising ones.Moreover, a dynamic window is applied in the algorithm to limit the search space, and a deadlock prevention policy is used to ensure feasible schedules. Experimental results show that the proposed algorithm can effectively find feasible schedules for FASs,and a well-designed heuristic function is likely to obtain schedules to meet industrial application requirements.
基金supported by Shanghai Municipal Natural Science Foundation,China(No.21ZR1446800)the National Natural Science Foundation of China(No.41877425)the Fundamental Research Funds for the Central Universities(No.226-2024-00052)。
文摘Microorganisms can colonize the surface of microplastics(MPs)to form a distinctive microbiome,known as a“plastisphere”which is regarded as an anthropogenic niche for microbial growth.However,bacterial community assembly in virgin and aging MP plastispheres across different habitats is poorly understood.This study aims to assess the variations in bacterial community assembly across different niches and habitats with an in situ ex-periment,in which constructed forest wetland(FW),natural lake wetland(LW),and lotus pond wetland(LP)were habitats,and plastispheres of virgin and aging low-density polyethylene(LDPE)MPs,as well as surround-ing wetland soils were niches.Significant niche-related differences in bacterial communities were observed,with lower diversity and enrichment of potential plastic-degrading bacteria in the plastisphere than in the soil bacterial communities.Furthermore,habitat-related differences exerted a more pronounced influence on the beta-diversity patterns of the bacterial communities.The linear regression analyses indicated that the local species pool con-tributed more to bacterial community assembly in the LW wetland,whereas the relative abundance of species was the primary factor in the LP wetland.The null model analysis indicated that plastisphere bacterial communi-ties were predominantly driven by the stochastic process,with a more deterministic assembly observed in the LP wetland and soil bacterial communities.Additionally,the primary ecological process shaping plastisphere com-munities shifted from drift in the virgin LDPE to homogenising dispersal in the aging LDPE.This study provides new insights into the fate and ecological impacts of MPs in wetlands,thereby facilitating the effective regulations of plastic pollution.
基金Supported by the National Natural Science Foundation of China(Nos.42141003,42176147)the National Key Research and Development Program of China(No.2022YFF0802204)the Xiamen Key Laboratory of Urban Sea Ecological Conservation and Restoration(USER)(Nos.USER2021-1,USER2021-5)。
文摘Ecological floating bed is an important biological remediation method for water pollution control.During the removal of excess nutrients and pollutants,changes in environmental factors affect the characteristics of microorganisms in aquatic ecosystems.To understand the influences of ecological floating beds on size-fractionated microorganisms,we investigated the community assembly and nitrogen metabolic characteristics of three size-fractionated microorganism groups in the ecological floating bed area,using 18S rDNA,16S rDNA metabarcoding,and metagenomic sequencing techniques.Firstly,we discovered substantial differences between size-fractionated groups in the diversity and compositions of both microeukaryotic and bacterial communities,as well as the influences of floating beds on specific groups.The floating beds appeared to provide more habitats for heterotrophs and symbiotes while potentially inhibiting the growth of certain phytoplankton(cyanobacteria).Secondly,we observed that microeukaryotic and bacterial communities were predominantly influenced by stochastic and deterministic processes,respectively,and they both exhibited distinct patterns across different size-fractionated groups.Notably,microeukaryotic community assembly demonstrated a greater sensitivity to ecological floating beds,as indicated by an increase in dispersal limitation processes.Finally,the nitrogen metabolism functional genes revealed that microbes associated with large-sized particles played a crucial role in dissimilatory nitrate reduction to ammonium(DNRA)and denitrification processes within the floating bed area,thereby facilitating the removal of excess nitrogen nutrients from the water.In contrast,freeliving microorganisms from small-sized groups were linked mainly to the genes involved in nitrogen assimilation and assimilatory nitrate reduction to ammonium(ANRA)processes.These findings help understand the impact of ecological floating beds on the diversity and functional characteristics of microorganism communities in different size-fractionated groups.
基金NR SEQUOIA(ANR-22-CE18-0006)Nan0Gold(ANR-22-CE29-0022)+3 种基金SAMURAI(ANR-24-CE19-2073-01)Wilive(ANR-24-CE09-2351-03)EUR CBH-EUR-GS(ANR-17-EURE 0003)for their financial supportthe French National Research Agency(Labex ARCANE,ANR-11-LABX-003 and CBH-EUR-GS,ANR-17-EURE-0003)that supported part of this study.
文摘Gold nanoclusters(AuNCs)are ultrasmall(<2 nm)aggregates of gold atoms that exhibit discrete electronic states,size-dependent photoluminescence,and exceptional biocompatibility,making them ideal candidates for theranostic applications.Their tunable surface chemistry enables targeted delivery,while strong near-infrared emission and environmental responsiveness allow for sensitive detection and deep-tissue imaging.Recent advances have revealed that controlled assembly of AuNCs into higher-order architectures-guided by biological scaffolds such as nucleic acids,peptides,and proteins-can markedly enhance their optical and electronic properties through aggregation-induced emission(AiE)and stabilization of surface ligands.This review summarizes recent progress in the design and biomedical applications of AuNC assemblies generated using biomolecules as structure-directing scaffolds.Covalent and noncovalent interactions with biomolecules enable the formation of well-defined one-,two-,and three-dimensional structures with tunable morphologies and sizes.These assemblies display distinctive photophysical behaviors that have been exploited for biosensing,bioimaging,and therapeutic applications in both cellular and in vivo models.Compared with individual AuNCs,assembled systems offer improved uptake,prolonged circulation,and efficient clearance,while protecting labile cargos such as nucleic acids and proteins.Moreover,their ordered and defined architectures can be engineered for controlled drug release and synergistic photo-or radiotherapeutic effects.Despite these advances,fundamental understanding of how structural organization governs photophysical responses remains limited.Elucidating parameters such as intercluster spacing and loading density will be essential for optimizing performance.Overall,biologically guided AuNC assemblies represent a powerful platform for multifunctional biosensing and therapy,bridging nanoscale design with biological function.
基金supported by the Natural Science Foundation of Anhui Province(2408085MC058 and 2308085QC91)National Natural Science Foundation of China(32301783and U21A20214)+5 种基金Innovation Program of the Chinese Academy of Agricultural Sciences(CAAS CSIAF-202303)Nanfan special project,CAAS(YYLH2309,YBXM2322,YYLH2401)Scientific Innovation 2030 Project(2022ZD0401703)CAAS Innovative Team Award,Science and Technology of Innovative research program of Anhui Province(202423m1005002)National Key Research and Development Program of China(2023YFD1200900)the Natural Science Foundation General Program of Hebei Province(C2024204242).
文摘IR64 is an elite Xian/indica variety developed by International Rice Research Institute(IRRl)in 1985,which has been the most widely grown variety and core breeding parent in South/Southeast Asia(Mackill and Khush,2018).IR64 has been utilized to develop stress-tolerant(such as drought-adapted and submergenceresistant)near-isogenic lines,underscoring its great potential in agricultural genomics(Tanaka et al.,2020).
基金financial y supported by the National Key Research and Development Program of China (2023YFD1900902)the Joint Funds of the Zhejiang Provincial Natural Science Foundation of China (LLSSZ24C030001)+1 种基金the Earmarked Fund for China Agriculture Research System (CARS-08-G-09)sponsored by the K.C.Wong Magna Fund of Ningbo University,China。
文摘Fungi play crucial roles in nutrient acquisition,plant growth promotion,and the enhancement of resistance to both abiotic and biotic stresses.However,studies on the fungal communities associated with peas (Pisum sativum L.) remain limited.In this study,we systematically investigated the ecological effects of host niches (soil,root,stem,leaf,and pod) and genotypes on the diversity and composition of fungal communities in peas using a multi-level approach that encompassed pattern recognition (β-diversity decomposition),mechanism validation (neutral community model testing),and dynamic tracking methods (migration pathway source-tracking).The results revealed that the dominant fungal phyla across niches and genotypes were Ascomycota,Basidiomycota,and Mortierellomycota,and the community structures of the soil–plant continuum were primarily determined by the pea niches rather than genotypes.β-diversity decomposition was largely attributed to species replacement rather than richness differences,indicating strong niche specificity and microbial replacement across microhabitats.Neutral model analysis revealed that stochastic processes influenced genotypeassociated communities,while deterministic processes played a dominant role in niche-based community assembly.Source-tracking analysis identified niche-to-niche fungal migration,with Erysiphe,Fusarium,Cephaliophora,Ascobolus,Alternaria,and Aspergillus as the key genera.Migration rates from exogenous to endogenous niches were low (1.3–61.5%),whereas those within exogenous (64.4–83.7%) or endogenous (73.9–96.4%) compartments were much higher,suggesting that the pea epidermis acts as a selective barrier that filters and enriches microbial communities prior to internal colonization.This study provides comprehensive insights into the mechanisms of host filtering,enrichment and microbial sourcing,which increases our understanding of the assembly rules of the pea-associated fungal microbiome.
文摘Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone to errors and lacks consistency,emphasizing the need for a reliable and automated inspection system.Leveraging both object detection and image segmentation approaches,this research proposes a vision-based solution for the detection of various kinds of tools in the toolkit using deep learning(DL)models.Two Intel RealSense D455f depth cameras were arranged in a top down configuration to capture both RGB and depth images of the toolkits.After applying multiple constraints and enhancing them through preprocessing and augmentation,a dataset consisting of 3300 annotated RGB-D photos was generated.Several DL models were selected through a comprehensive assessment of mean Average Precision(mAP),precision-recall equilibrium,inference latency(target≥30 FPS),and computational burden,resulting in a preference for YOLO and Region-based Convolutional Neural Networks(R-CNN)variants over ViT-based models due to the latter’s increased latency and resource requirements.YOLOV5,YOLOV8,YOLOV11,Faster R-CNN,and Mask R-CNN were trained on the annotated dataset and evaluated using key performance metrics(Recall,Accuracy,F1-score,and Precision).YOLOV11 demonstrated balanced excellence with 93.0%precision,89.9%recall,and a 90.6%F1-score in object detection,as well as 96.9%precision,95.3%recall,and a 96.5%F1-score in instance segmentation with an average inference time of 25 ms per frame(≈40 FPS),demonstrating real-time performance.Leveraging these results,a YOLOV11-based windows application was successfully deployed in a real-time assembly line environment,where it accurately processed live video streams to detect and segment tools within toolkits,demonstrating its practical effectiveness in industrial automation.The application is capable of precisely measuring socket dimensions by utilising edge detection techniques on YOLOv11 segmentation masks,in addition to detection and segmentation.This makes it possible to do specification-level quality control right on the assembly line,which improves the ability to examine things in real time.The implementation is a big step forward for intelligent manufacturing in the Industry 4.0 paradigm.It provides a scalable,efficient,and accurate way to do automated inspection and dimensional verification activities.
基金supported by the National Natural Science Foundation of China(Grant No.52475543)Natural Science Foundation of Henan(Grant No.252300421101)+1 种基金Henan Province University Science and Technology Innovation Talent Support Plan(Grant No.24HASTIT048)Science and Technology Innovation Team Project of Zhengzhou University of Light Industry(Grant No.23XNKJTD0101).
文摘Aircraft assembly is characterized by stringent precedence constraints,limited resource availability,spatial restrictions,and a high degree of manual intervention.These factors lead to considerable variability in operator workloads and significantly increase the complexity of scheduling.To address this challenge,this study investigates the Aircraft Pulsating Assembly Line Scheduling Problem(APALSP)under skilled operator allocation,with the objective of minimizing assembly completion time.A mathematical model considering skilled operator allocation is developed,and a Q-Learning improved Particle Swarm Optimization algorithm(QLPSO)is proposed.In the algorithm design,a reverse scheduling strategy is adopted to effectively manage large-scale precedence constraints.Moreover,a reverse sequence encoding method is introduced to generate operation sequences,while a time decoding mechanism is employed to determine completion times.The problem is further reformulated as a Markov Decision Process(MDP)with explicitly defined state and action spaces.Within QLPSO,the Q-learning mechanism adaptively adjusts inertia weights and learning factors,thereby achieving a balance between exploration capability and convergence performance.To validate the effectiveness of the proposed approach,extensive computational experiments are conducted on benchmark instances of different scales,including small,medium,large,and ultra-large cases.The results demonstrate that QLPSO consistently delivers stable and high-quality solutions across all scenarios.In ultra-large-scale instances,it improves the best solution by 25.2%compared with the Genetic Algorithm(GA)and enhances the average solution by 16.9%over the Q-learning algorithm,showing clear advantages over the comparative methods.These findings not only confirm the effectiveness of the proposed algorithm but also provide valuable theoretical references and practical guidance for the intelligent scheduling optimization of aircraft pulsating assembly lines.
基金supported by the National Key R&D Project of China(Nos.2022YFC2304205,2022YFC2304202)Key scientific research project of universities in Guangdong Province(No.2023KCXTD026)the Major Project of Guangzhou National Laboratory(No.GZNL2023A03002).
文摘Adjuvants enhance and prolong the immune response to therapeutic agents,such as drugs and vaccines.However,conventional adjuvants have limitations in terms of immune specificity and duration.Nanoadjuvants can leverage their nanoscale size to increase the capture efficacy of antigens by antigen-presenting cells and improve immunogen presentation for targeted delivery.Furthermore,noninvasive visualization of bifunctional nanoadjuvants with integrated efficacy and imaging postdelivery can provide insights into in vivo distribution and performance,aiding in the optimization and design of new dosage forms.This review systematically summarizes the structure,assembly,and function of nanoadjuvants alongside contrast agents.It delves into the impact of complex structures formed by nanoadjuvant-contrast agent interactions on antigen presentation,migration,imaging tracking,and visualization of immune cell recruitment.It also discusses how imaging can determine optimal immune intervals,vaccine safety,and toxicity while enabling diagnostic and therapeutic integration.Moreover,this paper discusses potential applications of novel adjuvants and promising imaging technologies that could have implications for future vaccine and drug development endeavors.
基金financially supported by the National Natural Science Foundation of China(32301962 and 31901127)the China Postdoctoral Science Foundation(2024M752947)+2 种基金the Postdoctoral Fellowship Program of China Postdoctoral Science Foundation(GZC20232437)the State Key Laboratory of Cotton Bio-breeding and Integrated Utilization Open Fund,China(CB2023C02)the Natural Science Foundation of Henan Province,China(252300420222)。
文摘Legume-based intercropping enhances asymbiotic biological nitrogen fixation(BNF);however,the underlying mechanisms remain unclear,including the roles of soil keystone diazotroph taxa with varying niche breadths.A field experiment was conducted to evaluate soil BNF variations between rhizosphere and bulk soils in peanut/cotton intercropping systems and monocultures.BNF activities were measured by nitrogen fixation rates,nitrogenase activity,and nifH gene abundance.Phylogenetic null models,co-occurrence networks,and niche breadth analysis were applied to investigate the roles of diazotrophic keystone taxa and their ecological niches.Rhizosphere soils exhibited 7.8–125.5%higher BNF potentials than bulk soils,whereas intercropping systems showed 11.6–323.0%increases over monocultures for nitrogen fixation rate,nitrogenase activity,and nifH gene abundance(all P<0.05).Diazotrophic community composition and diversity differed significantly,with Proteobacteria(excluding Alphaproteobacteria)enriched in intercropping and rhizosphere soils,while Cyanobacteria and Firmicutes were less abundant.Deterministic processes,particularly heterogeneous selection,dominated community assembly in the rhizosphere(91.9%)and intercropping soils(86.3%).The co-occurrence networks consistently revealed more complex and interconnected communities in intercropping and rhizosphere soils that were dominated by opportunistic diazotrophs(78.8–85.9%),followed by specialists(10.2–18.5%)and generalists(1.38–3.80%).Keystone taxa,including opportunists such as Azoarcus,Azohydromonas,and Steroidobacter,and generalists like Pseudomonas and Azotobacter,correlated positively with microbial biomass carbon and nitrate nitrogen,contributing to enhanced BNF.Peanut/cotton intercropping enhances BNF by selectively enriching the keystone diazotrophic taxa with varying ecological roles,particularly opportunists and generalists.Such targeted intercropping strategies can optimize BNF,improve soil fertility,and promote sustainable agricultural production.
基金funded by the National Key Research and Development Program of China(No.2024YFE0208600)the National Natural Science Foundation of China(No.U24B2090).
文摘Lattice-type ultra-tall wind turbine towers are popular in China for their modular benefits in fabrication,transportation,and installation.Nonetheless,their conceptual design remains predominantly dependent on engineering experience,and a generally applicable approach is still absent.This study proposes a self-similar modular topology optimization framework for lattice-type wind turbine support structures and develops software for its application.A minimum weighted compliance formulation with a prescribed volume fraction is developed utilizing the variable density approach,wherein modular constraints and their corresponding sensitivity expressions are explicitly included.The method is applied to a reference wind turbine model to generate modular lattice configurations.The novel structural models are evaluated under three representative design load cases outlined in IEC 61400 by finite element analysis.Compared with the reference structure,the 12-layer self-similar modular design reduces the maximum deformation and von Mises stress by 39.5%and 51.1%,respectively,demonstrating a substantial stiffness improvement while preserving modularity.The suggested approach provides an efficient and practical tool for the conceptual design of modular lattice-type wind turbine towers.
基金supported by Key Laboratory of Cyberspace Security,Ministry of Education,China。
文摘Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Although adversarial examples can strategically undermine the accuracy of BCSD models and protect critical code,existing techniques predominantly depend on inserting artificial instructions,which incur high computational costs and offer limited diversity of perturbations.To address these limitations,we propose AIMA,a novel gradient-guided assembly instruction relocation method.Our method decouples the detection model into tokenization,embedding,and encoding layers to enable efficient gradient computation.Since token IDs of instructions are discrete and nondifferentiable,we compute gradients in the continuous embedding space to evaluate the influence of each token.The most critical tokens are identified by calculating the L2 norm of their embedding gradients.We then establish a mapping between instructions and their corresponding tokens to aggregate token-level importance into instructionlevel significance.To maximize adversarial impact,a sliding window algorithm selects the most influential contiguous segments for relocation,ensuring optimal perturbation with minimal length.This approach efficiently locates critical code regions without expensive search operations.The selected segments are relocated outside their original function boundaries via a jump mechanism,which preserves runtime control flow and functionality while introducing“deletion”effects in the static instruction sequence.Extensive experiments show that AIMA reduces similarity scores by up to 35.8%in state-of-the-art BCSD models.When incorporated into training data,it also enhances model robustness,achieving a 5.9%improvement in AUROC.
文摘The computer numerical control（CNC） system is suited to control varied types of flexible fixtures in aircraft component manufacturing and assembly. The mechanisms and control requirements of flexible fixtures are presented and analyzed. The hardware and software architecture and implementation of CNC system are pro- posed. The flexible fixture mechanism is described using configuration parameters. According to the parameters, the CNC system automatically generates the control feature and the human machine interface （HMI） operation function. The CNC system is implemented in a flexible fixture for skin-strlnger assembly, and results show the effectiveness of the system.
