The assembly of a protein complex is very important for its biological function,which can be investigated by determining the order of assembly/disassembly of its protein subunits.Although static structures of many pro...The assembly of a protein complex is very important for its biological function,which can be investigated by determining the order of assembly/disassembly of its protein subunits.Although static structures of many protein com-plexes are available in the protein data bank,their assembly/disassembly orders of subunits are largely unknown.In addition to experimental techniques for studying subcomplexes in the assembly/disassembly of a protein complex,computational methods can be used to predict the assembly/disassembly order.Since sampling is a nontrivial issue in simulating the assembly/disassembly process,coarse-grained simulations are more efficient than atomic simulations are.In this work,we developed computational protocols for predicting the assembly/disassembly orders of protein complexes via coarse-grained simulations.The protocols were illustrated via two protein complexes,and the predicted assembly/disassembly orders were consistent with the available experimental data.展开更多
Fluorescence imaging has facilitated fluorescent probes to analyze the subcellular localization and dynamics of biological targets. In this paper, we reported a fluorogenic probe for bacteria imaging. The probe was an...Fluorescence imaging has facilitated fluorescent probes to analyze the subcellular localization and dynamics of biological targets. In this paper, we reported a fluorogenic probe for bacteria imaging. The probe was an imidazolium-derived pyrene compound, which self-assembled to form nano-particles and the pyrene fluorescence was quenched by the aggregation effects. When the self-assembly nanoparticles interacted with anionic bacteria surfaces, synergistic effects of electrostatic interaction and hydrophobic force caused competing binding between bacteria surfaces and imidazoliums. This binding resulted in the disassembly of the aggregates to give fluorescence turn-on signal. Meanwhile, the probe bound bacteria surfaces and displayed both pyrene-excimer and pyrene-monomer fluorescence, which gave ratiometric signal. Then, fluorescent labeling by the probe enabled the two-photo ratiometric imaging of bacteria.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
Two supramolecular organic frameworks(SOFs)have been constructed from the co-assembly of biimidazolium-derived octacationic components and cucurbit[8]uril in water.Dynamic light scattering and ^(1)H NMR experiments re...Two supramolecular organic frameworks(SOFs)have been constructed from the co-assembly of biimidazolium-derived octacationic components and cucurbit[8]uril in water.Dynamic light scattering and ^(1)H NMR experiments reveal that both SOFs can undergo reversible assembly and disassembly at room temperature.One of the SOFs displays unprecedently high maximum tolerated dose of 120 mg/kg with mice,which improves by 40%compared with the highest value of the reported SOFs.In vitro and in vivo tests show that the SOF can adsorb doxorubicin and overcome the resistance of multidrugresistant MDR A549/ADR tumor cells to realize intracellular delivery,leading to enhanced antitumor efficacy.Moreover,it can also completely inhibit the posttreatment phototoxicity of photofrin and fully neutralize the anticoagulation of both unfractionated heparin and low molecular weight heparins through efficient inclusion and elimination or sequestration mechanism.As the first examples that undergo roomtemperature reversible assembly and disassembly,the new SOFs in principle allow for quantitative analysis of the molecular components in the body that is prerequisite for preclinical evaluation in the future.展开更多
Odd-numbered and high-nuclearity coordination clusters are extremely rare,yet they represent an intriguing subclass lacking regular repeating building blocks and high structural symmetry for understanding self-assembl...Odd-numbered and high-nuclearity coordination clusters are extremely rare,yet they represent an intriguing subclass lacking regular repeating building blocks and high structural symmetry for understanding self-assembled multiatomic systems.Herein,the largest cobalt and polydentate ligand based cluster featuring odd-nuclearity,namely[Co_(19)(HL1)_(8)(L1)_(12)(L′)_(2)(Ac)_(4)]·10CH_(3)CH_(2)OH·6H_(2)O(1,H_(2)L1=1H-benzo[d]imidazole-2-yl)methanol,HL'=1H-benzo[d]imidazole),was obtained with in-situ ligand transformation from H_(2)L1 to L′.It features a hierarchical trilayer and void-cage inside structure,consisting of central disc-shaped[Co_(7)L_(10)]core with two[Co_(6)]rings on both sides.ESI-MS of crystal 1 yields a series of more than sixteen fragments,all featuring an integrated[Co_(19)]core,suggesting stability of the polynuclear cluster in solution.During increased in-source energy from 0 to 100 eV,all MS peaks shifted to a lower m/z range,but the[Co_(19)]core remained intact,excepting for the stepwise elimination of up to three Ac^(−)anions or three L1 linkers.PXRD tracking of the reaction sediments showed the formation of a key precursor of[Co_(4)L_(4)]cubane at 3 h,and its content decreased at 6 h and vanished at 12 h,followed by the appearance of crystals 1 by the generation of a clear solution at 18 h,suggesting an initial cluster assembly-disassembly process.ESI-MS spectra analysis of both reaction sediment and solution further identify the existence of other crucial higher-nuclearity reassembled fragments of[Co_(7)L_(10)]disk and its expansion of[Co_(13)L_(12)(L′)_(2)].A probable tandem assembly-disassembly-reassembly mechanism is put forward as[CoL_(2)]→[Co_(4)L_(4)]→[Co_(7)L_(10)]→[Co_(13)L_(12)(L′)_(2)]→[Co_(19)L_(2)0(L′)_(2)].Their evolution also indicated the ingenious synergy of coexisting organic,inorganic and in-situ generated ligands,along with diverse coordination geometries of metal ions,plays a directional role in forming odd-numbered and high-nuclearity coordination clusters.Magnetism analysis revealed antiferromagnetic coupling plays dominated role in the cluster.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
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
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
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
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
Wheat(Triticum aestivum)faces significant threats from diseases such as powdery mildew(Blumeria graminis)and Fusarium head blight(FHB;caused by Fusarium graminearum),which cause severe yield losses.Moreover,the antago...Wheat(Triticum aestivum)faces significant threats from diseases such as powdery mildew(Blumeria graminis)and Fusarium head blight(FHB;caused by Fusarium graminearum),which cause severe yield losses.Moreover,the antagonism between yield-related traits and disease resistance makes yield resistance coordination a major challenge in wheat breeding.The lack of genetic resources combining both disease resistance and high yield constrains the elucidation of underlying resistance-yield trade-off mechanisms,thereby hindering the development of high-yield and disease-resistant wheat cultivars.Remarkably,Yangmai 33(YM33),a notable wheat cultivar with resistance to both powdery mildew and FHB as well as high-yield performance,was recently developed.It offers a unique opportunity to dissect the genomic architecture underlying the coordination between disease resistance and yield.展开更多
The current research of configurable product disassemblability focuses on disassemblability evaluation and disassembly sequence planning. Little work has been done on quantitative analysis of configurable product disa...The current research of configurable product disassemblability focuses on disassemblability evaluation and disassembly sequence planning. Little work has been done on quantitative analysis of configurable product disassemblability. The disassemblability modeling technology for configurable product based on disassembly constraint relation weighted design structure matrix （DSM） is proposed. Major factors affecting the disassemblability of configurable product are analyzed, and the disassembling degrees between components in configurable product are obtained by calculating disassembly entropies such as joint type, joint quantity, disassembly path, disassembly accessibility and material compatibility. The disassembly constraint relation weighted DSM of configurable product is constructed and configuration modules are formed by matrix decomposition and tearing operations. The disassembly constraint relation in configuration modules is strong coupling, and the disassembly constraint relation between modules is weak coupling, and the disassemblability configuration model is constructed based on configuration module. Finally, taking a hydraulic forging press as an example, the decomposed weak coupling components are used as configuration modules alone, components with a strong coupling are aggregated into configuration modules, and the disassembly sequence of components inside configuration modules is optimized by tearing operation. A disassemblability configuration model of the hydraulic forging press is constructed. By researching the disassemblability modeling technology of product configuration design based on disassembly constraint relation weighted DSM, the disassembly property in maintenance, recycling and reuse of configurable product are optimized.展开更多
Disassembly sequence planning （DSP） plays a significant role in maintenance planning of the aircraft. It is used during the design stage for the analysis of maintainability of the aircraft. To solve product disassem...Disassembly sequence planning （DSP） plays a significant role in maintenance planning of the aircraft. It is used during the design stage for the analysis of maintainability of the aircraft. To solve product disassembly sequence planning problems efficiently, a product disassembly hybrid graph model, which describes the connection, non-connection and precedence relationships between the product parts, is established based on the characteristic of disassembly. Farther, the optimization model is provided to optimize disassembly sequence. And the solution methodology based on the genetic/simulated annealing algorithm with binaxy-tree algorithm is given. Finally, an example is analyzed in detail, and the result shows that the model is correct and efficient.展开更多
Due to the ability to combine the separately unique characteristics of assembled and disassembled nanoparticles(NPs), the stimuli-responsive self-assembly of NPs has attracted considerable interest in functional mater...Due to the ability to combine the separately unique characteristics of assembled and disassembled nanoparticles(NPs), the stimuli-responsive self-assembly of NPs has attracted considerable interest in functional material applications especially biomaterials. Here we demonstrate a facile and versatile approach to regulate the self-assembly process and transition pH of Au NPs by fine-tuning the co-modified pH-responsive compounds and poly(ethylene glycol)(PEG). Importantly the transition pH(ΔpH=0.4) of the system can be predetermined in the range of 8.2–5.8(assembled to disassembled) and 8.2–4.2(disassembled to assembled), which ideally covers the pH of normal tissue, tumor tissue milieu and organelles. The results of fluorescence imaging, Raman spectroscopy and photothermal conversion of the stimuli-responsive Au NPs shows the potential application for tumor specificity theranostics. In a nutshell this study provides a useful toolkit to design tumor-activatable self-assembled NPs with high specificity and universality.展开更多
Based on the bat algorithm(BA), this paper proposes a discrete BA(DBA) approach to optimize the disassembly sequence planning(DSP) problem, for the purpose of obtaining an optimum disassembly sequence(ODS) of a produc...Based on the bat algorithm(BA), this paper proposes a discrete BA(DBA) approach to optimize the disassembly sequence planning(DSP) problem, for the purpose of obtaining an optimum disassembly sequence(ODS) of a product with a high degree of automation and guiding maintenance operation. The BA for solving continuous problems is introduced, and combining with mathematical formulations, the BA is reformed to be the DBA for DSP problems. The fitness function model(FFM) is built to evaluate the quality of disassembly sequences. The optimization performance of the DBA is tested and verified by an application case, and the DBA is compared with the genetic algorithm(GA), particle swarm optimization(PSO) algorithm and differential mutation BA(DMBA). Numerical experiments show that the proposed DBA has a better optimization capability and provides more accurate solutions than the other three algorithms.展开更多
The recycling and remanufacturing of end-of-life products are significant for environmental protection and resource conservation.Disassembly is an essential process of remanufacturing end-of-life products.Effective di...The recycling and remanufacturing of end-of-life products are significant for environmental protection and resource conservation.Disassembly is an essential process of remanufacturing end-of-life products.Effective disassembly plans help improve disassembly efficiency and reduce disassembly costs.This paper studies a disassembly planning problem with operation attributes,in which an integrated decision of the disassembly sequence,disassembly directions,and disassembly tools are made.Besides,a mathematical model is formulated with the objective of minimizing the penalty cost caused by the changing of operation attributes.Then,a neighborhood modularization-based artificial bee colony algorithm is developed,which contains a modular optimized design.Finally,two case studies with different scales and complexities are used to verify the performance of the proposed approach,and experimental results show that the proposed algorithm outperforms the two existing methods within an acceptable computational time.展开更多
By taking advantage of recent advances in aptamer biology and nanotechnology, we developed a general approach for the design and fabrication of bioresponsive controlled delivery systems. It utilized the structure-swit...By taking advantage of recent advances in aptamer biology and nanotechnology, we developed a general approach for the design and fabrication of bioresponsive controlled delivery systems. It utilized the structure-switchable aptamer directed assembly and disassembly of gold nanoparticles from mesoporous silica supports, which enables the control of cargo release from the inside of the mesoporous nanoparticles specifically in the presence of target molecule.展开更多
It is well-recognized that obsolete or discarded products can cause serious environmental pollution if they are poorly be handled.They contain reusable resource that can be recycled and used to generate desired econom...It is well-recognized that obsolete or discarded products can cause serious environmental pollution if they are poorly be handled.They contain reusable resource that can be recycled and used to generate desired economic benefits.Therefore,performing their efficient disassembly is highly important in green manufacturing and sustainable economic development.Their typical examples are electronic appliances and electromechanical/mechanical products.This paper presents a survey on the state of the art of disassembly sequence planning.It can help new researchers or decision makers to search for the right solution for optimal disassembly planning.It reviews the disassembly theory and methods that are applied for the processing,repair,and maintenance of obsolete/discarded products.This paper discusses the recent progress of disassembly sequencing planning in four major aspects:product disassembly modeling methods,mathematical programming methods,artificial intelligence methods,and uncertainty handling.This survey should stimulate readers to be engaged in the research,development and applications of disassembly and remanufacturing methodologies in the Industry 4.0 era.展开更多
The cooperative work between human being and computer based on virtual reality (VR) is investigated to plan the disassembly sequences more efficiently. A three-layer model of human-computer cooperative virtual disasse...The cooperative work between human being and computer based on virtual reality (VR) is investigated to plan the disassembly sequences more efficiently. A three-layer model of human-computer cooperative virtual disassembly is built, and the corresponding human-computer system for stable virtual disassembly is developed. In this system, an immersive and interactive virtual disassembly environment has been created to provide planners with a more visual working scene. For cooperative disassembly, an intelligent module of stability analysis of disassembly operations is embedded into the human-computer system to assist planners to implement disassembly tasks better. The supporting matrix for stability analysis of disassembly operations is defined and the method of stability analysis is detailed. Based on the approach, the stability of any disassembly operation can be analyzed to instruct the manual virtual disassembly. At last, a disassembly case in the virtual environment is given to prove the validity of above ideas.展开更多
基金This work was supported by the National Key Research and Development Program of China(2021YFA1301504)the Chinese Academy of Sciences Strategic Priority Research Program(XDB37040202)the National Natural Science Foundation of China(91953101).
文摘The assembly of a protein complex is very important for its biological function,which can be investigated by determining the order of assembly/disassembly of its protein subunits.Although static structures of many protein com-plexes are available in the protein data bank,their assembly/disassembly orders of subunits are largely unknown.In addition to experimental techniques for studying subcomplexes in the assembly/disassembly of a protein complex,computational methods can be used to predict the assembly/disassembly order.Since sampling is a nontrivial issue in simulating the assembly/disassembly process,coarse-grained simulations are more efficient than atomic simulations are.In this work,we developed computational protocols for predicting the assembly/disassembly orders of protein complexes via coarse-grained simulations.The protocols were illustrated via two protein complexes,and the predicted assembly/disassembly orders were consistent with the available experimental data.
基金financially supported by the National Natural Science Foundation of China(Nos. 21878286, 21502189)DICP (Nos. DMT0201603, TMSR201601)
文摘Fluorescence imaging has facilitated fluorescent probes to analyze the subcellular localization and dynamics of biological targets. In this paper, we reported a fluorogenic probe for bacteria imaging. The probe was an imidazolium-derived pyrene compound, which self-assembled to form nano-particles and the pyrene fluorescence was quenched by the aggregation effects. When the self-assembly nanoparticles interacted with anionic bacteria surfaces, synergistic effects of electrostatic interaction and hydrophobic force caused competing binding between bacteria surfaces and imidazoliums. This binding resulted in the disassembly of the aggregates to give fluorescence turn-on signal. Meanwhile, the probe bound bacteria surfaces and displayed both pyrene-excimer and pyrene-monomer fluorescence, which gave ratiometric signal. Then, fluorescent labeling by the probe enabled the two-photo ratiometric imaging of bacteria.
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the National Natural Science Foundation of China(No.21921003 for Z.T.L.and 22201293 for S.B.Y.)Shanghai Sailing Program(No.22YF1458300 for S.B.Y.)for financial support。
文摘Two supramolecular organic frameworks(SOFs)have been constructed from the co-assembly of biimidazolium-derived octacationic components and cucurbit[8]uril in water.Dynamic light scattering and ^(1)H NMR experiments reveal that both SOFs can undergo reversible assembly and disassembly at room temperature.One of the SOFs displays unprecedently high maximum tolerated dose of 120 mg/kg with mice,which improves by 40%compared with the highest value of the reported SOFs.In vitro and in vivo tests show that the SOF can adsorb doxorubicin and overcome the resistance of multidrugresistant MDR A549/ADR tumor cells to realize intracellular delivery,leading to enhanced antitumor efficacy.Moreover,it can also completely inhibit the posttreatment phototoxicity of photofrin and fully neutralize the anticoagulation of both unfractionated heparin and low molecular weight heparins through efficient inclusion and elimination or sequestration mechanism.As the first examples that undergo roomtemperature reversible assembly and disassembly,the new SOFs in principle allow for quantitative analysis of the molecular components in the body that is prerequisite for preclinical evaluation in the future.
基金supported by the BAGUI Talent Program in Guangxi Province(No.2019AC26001)the National Natural Science Foundation of China(Nos.22171075,U23A2080,22371173).
文摘Odd-numbered and high-nuclearity coordination clusters are extremely rare,yet they represent an intriguing subclass lacking regular repeating building blocks and high structural symmetry for understanding self-assembled multiatomic systems.Herein,the largest cobalt and polydentate ligand based cluster featuring odd-nuclearity,namely[Co_(19)(HL1)_(8)(L1)_(12)(L′)_(2)(Ac)_(4)]·10CH_(3)CH_(2)OH·6H_(2)O(1,H_(2)L1=1H-benzo[d]imidazole-2-yl)methanol,HL'=1H-benzo[d]imidazole),was obtained with in-situ ligand transformation from H_(2)L1 to L′.It features a hierarchical trilayer and void-cage inside structure,consisting of central disc-shaped[Co_(7)L_(10)]core with two[Co_(6)]rings on both sides.ESI-MS of crystal 1 yields a series of more than sixteen fragments,all featuring an integrated[Co_(19)]core,suggesting stability of the polynuclear cluster in solution.During increased in-source energy from 0 to 100 eV,all MS peaks shifted to a lower m/z range,but the[Co_(19)]core remained intact,excepting for the stepwise elimination of up to three Ac^(−)anions or three L1 linkers.PXRD tracking of the reaction sediments showed the formation of a key precursor of[Co_(4)L_(4)]cubane at 3 h,and its content decreased at 6 h and vanished at 12 h,followed by the appearance of crystals 1 by the generation of a clear solution at 18 h,suggesting an initial cluster assembly-disassembly process.ESI-MS spectra analysis of both reaction sediment and solution further identify the existence of other crucial higher-nuclearity reassembled fragments of[Co_(7)L_(10)]disk and its expansion of[Co_(13)L_(12)(L′)_(2)].A probable tandem assembly-disassembly-reassembly mechanism is put forward as[CoL_(2)]→[Co_(4)L_(4)]→[Co_(7)L_(10)]→[Co_(13)L_(12)(L′)_(2)]→[Co_(19)L_(2)0(L′)_(2)].Their evolution also indicated the ingenious synergy of coexisting organic,inorganic and in-situ generated ligands,along with diverse coordination geometries of metal ions,plays a directional role in forming odd-numbered and high-nuclearity coordination clusters.Magnetism analysis revealed antiferromagnetic coupling plays dominated role in the cluster.
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.
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.
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.
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 Key R&D Program of China(2024YFD1201100)the research program from the Zhongshan Biological Breeding Laboratory(ZSBBL-KY2023-02)the National Natural Science Foundation of China(32341037).
文摘Wheat(Triticum aestivum)faces significant threats from diseases such as powdery mildew(Blumeria graminis)and Fusarium head blight(FHB;caused by Fusarium graminearum),which cause severe yield losses.Moreover,the antagonism between yield-related traits and disease resistance makes yield resistance coordination a major challenge in wheat breeding.The lack of genetic resources combining both disease resistance and high yield constrains the elucidation of underlying resistance-yield trade-off mechanisms,thereby hindering the development of high-yield and disease-resistant wheat cultivars.Remarkably,Yangmai 33(YM33),a notable wheat cultivar with resistance to both powdery mildew and FHB as well as high-yield performance,was recently developed.It offers a unique opportunity to dissect the genomic architecture underlying the coordination between disease resistance and yield.
基金Supported by National Natural Science Foundation of China(Grant No.51375437)Zhejiang Provincial Natural Science Foundation of China(Grant No.LY12E05019)
文摘The current research of configurable product disassemblability focuses on disassemblability evaluation and disassembly sequence planning. Little work has been done on quantitative analysis of configurable product disassemblability. The disassemblability modeling technology for configurable product based on disassembly constraint relation weighted design structure matrix （DSM） is proposed. Major factors affecting the disassemblability of configurable product are analyzed, and the disassembling degrees between components in configurable product are obtained by calculating disassembly entropies such as joint type, joint quantity, disassembly path, disassembly accessibility and material compatibility. The disassembly constraint relation weighted DSM of configurable product is constructed and configuration modules are formed by matrix decomposition and tearing operations. The disassembly constraint relation in configuration modules is strong coupling, and the disassembly constraint relation between modules is weak coupling, and the disassemblability configuration model is constructed based on configuration module. Finally, taking a hydraulic forging press as an example, the decomposed weak coupling components are used as configuration modules alone, components with a strong coupling are aggregated into configuration modules, and the disassembly sequence of components inside configuration modules is optimized by tearing operation. A disassemblability configuration model of the hydraulic forging press is constructed. By researching the disassemblability modeling technology of product configuration design based on disassembly constraint relation weighted DSM, the disassembly property in maintenance, recycling and reuse of configurable product are optimized.
基金supported by the National High Technology Research and Development Program of China(2006AA04Z427).
文摘Disassembly sequence planning （DSP） plays a significant role in maintenance planning of the aircraft. It is used during the design stage for the analysis of maintainability of the aircraft. To solve product disassembly sequence planning problems efficiently, a product disassembly hybrid graph model, which describes the connection, non-connection and precedence relationships between the product parts, is established based on the characteristic of disassembly. Farther, the optimization model is provided to optimize disassembly sequence. And the solution methodology based on the genetic/simulated annealing algorithm with binaxy-tree algorithm is given. Finally, an example is analyzed in detail, and the result shows that the model is correct and efficient.
基金supported by the National Natural Science Foundation of China(51433004,51773096)the Natural Science Foundation of Tianjin(17JCZDJC33500)and PCSIRT(IRT1257)
文摘Due to the ability to combine the separately unique characteristics of assembled and disassembled nanoparticles(NPs), the stimuli-responsive self-assembly of NPs has attracted considerable interest in functional material applications especially biomaterials. Here we demonstrate a facile and versatile approach to regulate the self-assembly process and transition pH of Au NPs by fine-tuning the co-modified pH-responsive compounds and poly(ethylene glycol)(PEG). Importantly the transition pH(ΔpH=0.4) of the system can be predetermined in the range of 8.2–5.8(assembled to disassembled) and 8.2–4.2(disassembled to assembled), which ideally covers the pH of normal tissue, tumor tissue milieu and organelles. The results of fluorescence imaging, Raman spectroscopy and photothermal conversion of the stimuli-responsive Au NPs shows the potential application for tumor specificity theranostics. In a nutshell this study provides a useful toolkit to design tumor-activatable self-assembled NPs with high specificity and universality.
文摘Based on the bat algorithm(BA), this paper proposes a discrete BA(DBA) approach to optimize the disassembly sequence planning(DSP) problem, for the purpose of obtaining an optimum disassembly sequence(ODS) of a product with a high degree of automation and guiding maintenance operation. The BA for solving continuous problems is introduced, and combining with mathematical formulations, the BA is reformed to be the DBA for DSP problems. The fitness function model(FFM) is built to evaluate the quality of disassembly sequences. The optimization performance of the DBA is tested and verified by an application case, and the DBA is compared with the genetic algorithm(GA), particle swarm optimization(PSO) algorithm and differential mutation BA(DMBA). Numerical experiments show that the proposed DBA has a better optimization capability and provides more accurate solutions than the other three algorithms.
基金National Natural Science Foundation of China(Grant Nos.52205526,52205529)Basic and Applied Basic Research Project of the Guangzhou Basic Research Program of China(Grant No.202201010284)+6 种基金National Foreign Expert Project of the Ministry of Science and Technology of China(Grant No.G2021199026L)National Key Research and Development Program of China(Grant Nos.2021YFB3301701,2021YFB3301702)Guangdong Provincial Graduate Education Innovation Program of China(Grant No.82620516)Guangzhou Municipal Innovation Leading Team Project of China(Grant No.201909010006)Guangdong Provincial"Quality Engineering"Construction Project of China(Grant No.210308)Guangdong Provincial Basic and Applied Basic Research Foundation of China(Grant No.2019A1515110399)Fundamental Research Funds for the Central Universities of China(Grant No.21620360).
文摘The recycling and remanufacturing of end-of-life products are significant for environmental protection and resource conservation.Disassembly is an essential process of remanufacturing end-of-life products.Effective disassembly plans help improve disassembly efficiency and reduce disassembly costs.This paper studies a disassembly planning problem with operation attributes,in which an integrated decision of the disassembly sequence,disassembly directions,and disassembly tools are made.Besides,a mathematical model is formulated with the objective of minimizing the penalty cost caused by the changing of operation attributes.Then,a neighborhood modularization-based artificial bee colony algorithm is developed,which contains a modular optimized design.Finally,two case studies with different scales and complexities are used to verify the performance of the proposed approach,and experimental results show that the proposed algorithm outperforms the two existing methods within an acceptable computational time.
基金supported by the Inner Mongolia Power(Group) Co., Ltd.,Technology Project (No. 2016-20)
文摘By taking advantage of recent advances in aptamer biology and nanotechnology, we developed a general approach for the design and fabrication of bioresponsive controlled delivery systems. It utilized the structure-switchable aptamer directed assembly and disassembly of gold nanoparticles from mesoporous silica supports, which enables the control of cargo release from the inside of the mesoporous nanoparticles specifically in the presence of target molecule.
基金the Research Foundation of China(L2019027)Liaoning Revitalization Talents Program(XLYC1907166)the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah(KEP-2-135-39)。
文摘It is well-recognized that obsolete or discarded products can cause serious environmental pollution if they are poorly be handled.They contain reusable resource that can be recycled and used to generate desired economic benefits.Therefore,performing their efficient disassembly is highly important in green manufacturing and sustainable economic development.Their typical examples are electronic appliances and electromechanical/mechanical products.This paper presents a survey on the state of the art of disassembly sequence planning.It can help new researchers or decision makers to search for the right solution for optimal disassembly planning.It reviews the disassembly theory and methods that are applied for the processing,repair,and maintenance of obsolete/discarded products.This paper discusses the recent progress of disassembly sequencing planning in four major aspects:product disassembly modeling methods,mathematical programming methods,artificial intelligence methods,and uncertainty handling.This survey should stimulate readers to be engaged in the research,development and applications of disassembly and remanufacturing methodologies in the Industry 4.0 era.
基金This project is supported by National Natural Science Foundation of China (No.59990470-2).
文摘The cooperative work between human being and computer based on virtual reality (VR) is investigated to plan the disassembly sequences more efficiently. A three-layer model of human-computer cooperative virtual disassembly is built, and the corresponding human-computer system for stable virtual disassembly is developed. In this system, an immersive and interactive virtual disassembly environment has been created to provide planners with a more visual working scene. For cooperative disassembly, an intelligent module of stability analysis of disassembly operations is embedded into the human-computer system to assist planners to implement disassembly tasks better. The supporting matrix for stability analysis of disassembly operations is defined and the method of stability analysis is detailed. Based on the approach, the stability of any disassembly operation can be analyzed to instruct the manual virtual disassembly. At last, a disassembly case in the virtual environment is given to prove the validity of above ideas.
