This review focuses on the recent research progress in the multi-component assembly of luminescent rare earth hybrid materials, which is based on the luminescent rare earth compounds and two or more other building uni...This review focuses on the recent research progress in the multi-component assembly of luminescent rare earth hybrid materials, which is based on the luminescent rare earth compounds and two or more other building units, including the other photoactive species. It covers the multi-component luminescent rare earth hybrids which was assembled with different(a) organic-inorganic polymeric units,(b)nanoporous units,(c) nanoparticle composites or(d) other developing special units. Finally, future challenges and opportunities in this field are discussed. Herein it mainly focuses on the work of Yan's group in recent years.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
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
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
Traditional Chinese medicine decoction is a complex polydispersed phase system containing real solution,colloid solution,emulsion and suspension.The compound decoction of traditional Chinese medicine has complex compo...Traditional Chinese medicine decoction is a complex polydispersed phase system containing real solution,colloid solution,emulsion and suspension.The compound decoction of traditional Chinese medicine has complex components,including saponins,alkaloids,polysaccharides,flavonoids,amino acids and so on,which can be self-assembled to form gels,fibers,micelles,vesicles and so on.The self-assembled nano-phase not only neutralizes the single drug and reduces the toxicity and side effects,but also has its own pharmacological effects,which complement each other to achieve synergistic effect,so as to achieve the role of drug supplement,which is of research significance.The formation principle,solubilization and synergism principle and characterization method of multi-component self-assembly of traditional Chinese medicine compound decoction are discussed in this paper.展开更多
A mild and efficient photochemical multi-component tandem reaction of quinoxalin-2(1H)-ones, alkenes and sulfinic acids is reported. This tandem reaction could be conveniently carried out at room temperature by employ...A mild and efficient photochemical multi-component tandem reaction of quinoxalin-2(1H)-ones, alkenes and sulfinic acids is reported. This tandem reaction could be conveniently carried out at room temperature by employing 4Cz IPN as the metal-free photocatalyst and dioxygen(air) as the environmentally benign oxidant. A number of sulfonated quinoxalin-2(1H)-ones were obtained in satisfactory yields with favorable functional group tolerance. Radical trapping experiment and fluorescence quenching experiments were performed to elucidate this visible-light mediated radical reaction process.展开更多
Juglans sigillata is an economically valuable nut crop renowned for its nutritional richness,including essential nutrients,antioxidants,and healthy fats,which boost human cardial,brain and gut health.Despite its impor...Juglans sigillata is an economically valuable nut crop renowned for its nutritional richness,including essential nutrients,antioxidants,and healthy fats,which boost human cardial,brain and gut health.Despite its importance,the lack of a complete genome assembly has been a stumbling block in its biological breeding process.Therefore,we generated deep coverage ultralong Oxford Nanopore Technology(ONT)and PacBio HiFi reads to construct a telomere-to-telomere(T2T)genome assembly.The final assembly spans 537.27 Mb with no gaps,demonstrating a remarkable completeness of 98.1%.We utilized a combination of transcriptome data and homologous proteins to annotate the genome,identifying 36018 protein-coding genes.Furthermore,we profiled global cytosine DNA methylations using ONT sequencing data.Global methylome analysis revealed high methylation levels in transposable element(TE)-rich chromosomal regions juxtaposed with comparatively lower methylation in gene-rich areas.By integrating a detailed multi-omics data analysis,we obtained valuable insights into the mechanism underlying endopleura coloration.This investigation led to the identification of eight candidate genes(e.g.ANR)involved in anthocyanin biosynthesis pathways,which are crucial for the development of color in plants.The comprehensive genome assembly and the understanding of the genetic basis of important traits like endopleura coloration will open avenues for more efficient breeding programs and improved crop quality.展开更多
The application of photocatalytic technology in algae killing is limited by the non-floatability and difficulty in recycling of the photocatalysts.Loading photocatalyst on magnetic or floatable carriers is the most po...The application of photocatalytic technology in algae killing is limited by the non-floatability and difficulty in recycling of the photocatalysts.Loading photocatalyst on magnetic or floatable carriers is the most popular method for overcoming the above inadequacies.In this work,a CdZnS/TiO_(2) membrane photocatalyst with adjustable suspended depth(include floating)and flexible assembly is designed,which is less prone to dislodgement due to in situ synthesis and has a wider range of applicability than previously reported photocatalysts.The photocatalytic removal of Microcystis aeruginosa revealed that the suspended depth and distribution format of the CdZnS/TiO_(2) membrane photocatalysts have striking effects on the photocatalytic removal performance of Microcystis aeruginosa,the photocatalytic removal efficiency of CdZnS/TiO_(2)-2 membrane photocatalysts for Microcystis aeruginosa could reach to 98.6%in 60 min when the photocatalysts assembled in the form of 3×3 arrays suspended at a depth of 2 cm from the liquid surface.A tiny amount of TiO_(2) loading allows the formation of Z-Scheme heterojunction,resulting in accelerating the separation efficiency of photogenerated carriers,preserving the photogenerated electrons and holes with stronger reduction and oxidation ability and inhabiting the photo-corrosion of CdZnS.展开更多
Membrane electrode assembly(MEA)is widely considered to be the most promising type of electrolyzer for the practical application of electrochemical CO_(2) reduction reaction(CO_(2)RR).In MEAs,a square-shaped cross-sec...Membrane electrode assembly(MEA)is widely considered to be the most promising type of electrolyzer for the practical application of electrochemical CO_(2) reduction reaction(CO_(2)RR).In MEAs,a square-shaped cross-section in the flow channel is normally adopted,the configuration optimization of which could potentially enhance the performance of the electrolyzer.This paper describes the numerical simulation study on the impact of the flow-channel cross-section shapes in the MEA electrolyzer for CO_(2)RR.The results show that wide flow channels with low heights are beneficial to the CO_(2)RR by providing a uniform flow field of CO_(2),especially at high current densities.Moreover,the larger the electrolyzer,the more significant the effect is.This study provides a theoretical basis for the design of high-performance MEA electrolyzers for CO_(2)RR.展开更多
A unitized regenerative fuel cell(URFC)is a device that may function reversibly as either a fuel cell(FC)or water elec-trolysis(WE).An important component of this device is the Membrane electrode assembly(MEA).Therefo...A unitized regenerative fuel cell(URFC)is a device that may function reversibly as either a fuel cell(FC)or water elec-trolysis(WE).An important component of this device is the Membrane electrode assembly(MEA).Therefore,this study aimed to compare the performance outcomes of MEA using electrodes with single and three catalyst layers.This study measured Electrochemical Surface Area(ECSA),Electrochemical Impedance Spectroscopy(EIS),X-ray Diffraction analysis(XRD),and X-ray Fluorescence(XRF).Furthermore,the round-trip efficiency(RTE)of the MEA,as w ell as the performance in FC and WE mode,was measured.In comparison,The ECSA values of Pt-Ru/C and Pt/C with three catalyst layers were higher than the single catalyst layer.This result was supported by electrode characterization data for XRD and XRF.The respective electrical conductivity values of Pt-Ru/C and Pt/C with three catalyst layers are also higher than the single cata-lyst layer,and the performance of URFC using MEA with three catalyst layers has the highest value of RTE among the MEA performances of URFC,which is 100%at a current density of 4 mA·cm-2.展开更多
Assembly precision greatly influences the performance of complex high-end equipment.The traditional industrial assembly process and deviation transfer are implicit and uncertain,causing problems like poor component fi...Assembly precision greatly influences the performance of complex high-end equipment.The traditional industrial assembly process and deviation transfer are implicit and uncertain,causing problems like poor component fit and hard-to-trace assembly stress concentration.Assemblers can only check whether the dimensional tolerance of the component design is exceeded step by step in combination with prior knowledge.Inversion in industrial assembly optimizes assembly and design by comparing real and theoretical results and doing inversion analysis to reduce assembly deviation.The digital twin(DT)technology visualizes and predicts the assembly process by mapping real and virtual model parameters and states simultaneously,expanding parameter range for inversion analysis and improving inversion result accuracy.Problems in improving industrial assembly precision and the significance and research status of DT-driven parametric inversion of assembly tools,processes and object precision are summarized.It analyzes vital technologies for assembly precision inversion such as multi-attribute assembly process parameter sensing,virtual modeling of high-fidelity assembly systems,twin synchronization of assembly process data models,multi-physical field simulation,and performance twin model construction of the assembly process.Combined with human-cyber-physical system,augmented reality,and generative intelligence,the outlook of DT-driven assembly precision inversion is proposed,providing support for DT's use in industrial assembly and precision improvement.展开更多
As the demands for assembly quality and efficiency increase,robot-assisted assembly applications are becoming more widespread.Peg-in-hole assembly,as a typical form of assembly,has been widely researched by scholars.C...As the demands for assembly quality and efficiency increase,robot-assisted assembly applications are becoming more widespread.Peg-in-hole assembly,as a typical form of assembly,has been widely researched by scholars.Currently,robotic peg-in-hole assembly faces challenges such as complex analysis of part contact forces,difficulties in task modeling,and the failure of traditional strategies.Simply controlling the position of the robot's end effector cannot achieve high precision,high efficiency peg-in-hole assembly.Flexible assembly,especially intelligent flexible assembly,is becoming the future development trend.So there is a lack of comprehensive reviews on robotic flexible peg-in-hole assembly.This paper first outlines the basic components of peg-in-hole assembly and summarizes the two basic operational processes of peg-in-hole assembly,along with their related theoretical foundations.We then review and analyze the research on passive compliant assembly,active compliant assembly,and intelligent flexible assembly.Finally,it presents an outlook on the future development directions of robotic peg-in-hole assembly.展开更多
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
Molecular recognition of fullerene using various host compounds is well-known in literature.But most studies focus on host-vip complexation in solution using host compounds with a single binding cavity.Herein,we rep...Molecular recognition of fullerene using various host compounds is well-known in literature.But most studies focus on host-vip complexation in solution using host compounds with a single binding cavity.Herein,we report a series of highly preorganized janusarene derivatives with homoditopic binding sites.These novel janusarenes can bind and align various fullerenes such as C_(60),C_(70),C_(84),and Gd@C_(82)in a highly efficient manner.Robust shape complementary association and assembly are observed in solution,in the bulk solid state,in the liquid crystalline state,or on surface,and the assembled structures are characterized by nuclear magnetic resonance(NMR)titration,X-ray diffraction,polarized optical microscopy,and scanning tunneling microscopy.展开更多
In the realm of nonlinear integrable systems,the presence of decompositions facilitates the establishment of linear superposition solutions and the derivation of novel coupled systems exhibiting nonlinear integrabilit...In the realm of nonlinear integrable systems,the presence of decompositions facilitates the establishment of linear superposition solutions and the derivation of novel coupled systems exhibiting nonlinear integrability.By focusing on single-component decompositions within the potential BKP hierarchy,it has been observed that specific linear superpositions of decomposition solutions remain consistent with the underlying equations.Moreover,through the implementation of multi-component decompositions within the potential BKP hierarchy,successful endeavors have been undertaken to formulate linear superposition solutions and novel coupled Kd V-type systems that resist decoupling via alterations in dependent variables.展开更多
Multi-component transition group metal borides(MMB_(2))have become a research hotspot due to their new composition design concepts and superior properties compared with conventional ceramics.Most of the current method...Multi-component transition group metal borides(MMB_(2))have become a research hotspot due to their new composition design concepts and superior properties compared with conventional ceramics.Most of the current methods,however,are complicated and time-consuming,the mass production remains a chal-lenge.Herein,we proposed a new high-efficiency strategy for synthesis of MMB_(2)using molten aluminum as the medium for the first time.The prepared Al-containing multi-component borides(TiZrHfNbTa)B_(2)microcrystals had a homogeneous composition with a hexagonal AlB_(2)structure and ultra-high hardness value of∼35.3 GPa,which was much higher than data reported in the literature and the rule of mix-ture estimations.Furthermore,combined with the First-principles calculation results,we found that the Poisson’s ratio(v)values exhibit a clearly ascending trend from 0.17 at VEC=3.5 to 0.18 at VEC=3.4,then to 0.201 at VEC=3.2 with the increasing of Al content.This indicates that the intrinsic toughness of multi-component boride microcrystals is obviously enhanced by the trace-doped Al elements.Besides,the fabricated Al-containing multi-component boride microcrystals have superior oxidation activation en-ergy and structural stability.The enhanced oxidation resistance is mainly attributed to the formation of a protective Al2 O3 oxide layer and the lattice distortion,both of which lead to sluggish diffusion of O_(2).These findings propose a new unexplored avenue for the fabrication of MMB_(2)materials with supe-rior comprehensive performance including ultra-hardness and intrinsically improved thermo-mechanical properties.展开更多
Despite the gradual transformation of traditional manufacturing by the Human-Robot Collaboration Assembly(HRCA),challenges remain in the robot’s ability to understand and predict human assembly intentions.This study ...Despite the gradual transformation of traditional manufacturing by the Human-Robot Collaboration Assembly(HRCA),challenges remain in the robot’s ability to understand and predict human assembly intentions.This study aims to enhance the robot’s comprehension and prediction capabilities of operator assembly intentions by capturing and analyzing operator behavior and movements.We propose a video feature extraction method based on the Temporal Shift Module Network(TSM-ResNet50)to extract spatiotemporal features from assembly videos and differentiate various assembly actions using feature differences between video frames.Furthermore,we construct an action recognition and segmentation model based on the Refined-Multi-Scale Temporal Convolutional Network(Refined-MS-TCN)to identify assembly action intervals and accurately acquire action categories.Experiments on our self-built reducer assembly action dataset demonstrate that our network can classify assembly actions frame by frame,achieving an accuracy rate of 83%.Additionally,we develop a HiddenMarkovModel(HMM)integrated with assembly task constraints to predict operator assembly intentions based on the probability transition matrix and assembly task constraints.The experimental results show that our method for predicting operator assembly intentions can achieve an accuracy of 90.6%,which is a 13.3%improvement over the HMM without task constraints.展开更多
Intestinal drug-resistant pathogens,e.g.,Salmonella enterica subsp.enterica serovar Typhimurium(S.Tm)and enteropathogenic Escherichia coli(E.coli),frequently cause life-threatening infectious enteritis.Probiotic-based...Intestinal drug-resistant pathogens,e.g.,Salmonella enterica subsp.enterica serovar Typhimurium(S.Tm)and enteropathogenic Escherichia coli(E.coli),frequently cause life-threatening infectious enteritis.Probiotic-based therapy is a promising way to eliminate drug-resistant pathogens for treatment of infectious enteritis,but its colonizing and therapeutic efficacy after oral administration are limited.Here,we developed a facile therapeutic agent to treat infectious enteritis by co-assembly of the peptide nanodrug melittin-loaded MSN grafted by polysaccharide-binding protein(MMPB)with the famous probiotic bacteria Lactobacillus plantarum(Lac)and Bifidobacterium animalis subsp.lactis(Bif).The nanodrug was composed of the antimicrobial peptide melittin and mesoporous silica nanoparticles exposing the artificial polysaccharide-binding protein.Owing to presence of the artificial protein on the MMPB surface,the nanodrug strongly bound and cross-linked the probiotic cells,forming the Lac+Bif+MMPB co-assembly.During co-incubation with the kanamycin-resistant E.coli strain(Ecka),the co-assembly strongly reduced the viability of Ecka,leading to the increase in the ratio of probiotic to Ecka from 1.6 to 9.2.After oral administration of the co-assembly to themice pre-colonized by Ecka,Lac+Bif+MMPB almost eliminated the kanamycin-resistant gene in the intestine,and led to 2-3-fold higher levels of the probiotic cells than the nanodrug MMPB or the combined probiotics Lac+Bif.More importantly,in the mice suffering from enteritis caused by drug-resistant S.Tm,the co-assembly remarkably recovered the mouse body weight,reduced intestine colonization of S.Tm cells,and decreased the levels of pro-inflammatory cytokines in both serum and colons.This study realized the synthetic biology technique-mediated abiotic/biotic co-assembly for efficient treating infectious enteritis induced by drug-resistant pathogens.展开更多
Common bean(Phaseolus vulgaris L.)is a vital source of protein and essential nutrients for human consumption and plays a key role in sustainable agriculture due to its nitrogen-fixing ability(Nadeem et al.,2021).Kidne...Common bean(Phaseolus vulgaris L.)is a vital source of protein and essential nutrients for human consumption and plays a key role in sustainable agriculture due to its nitrogen-fixing ability(Nadeem et al.,2021).Kidney beans,a subcategory of dry common beans,are highly valued for their rich protein,dietary fiber,low fat content,and various trace elements(Garcia-Cordero et al.,2021).Despite the release of several de novo genome assemblies(Goodstein et al.,2012;Schmutz et al.,2014;Vlasova et al.,2016;Cortinovis et al.,2024),existing common bean genomes remain incomplete,particularly in complex regions such as centromeres and telomeres,limiting a comprehensive understanding of the genomic landscape.展开更多
基金Project supported by the National Natural Science Foundation of China(21571142)the Developing Science Fund of Tongji University,the Natural Science Foundation of Zhejiang Province(LQ14B010001)the Natural Science Foundation of Ningbo,China(2016A610105)
文摘This review focuses on the recent research progress in the multi-component assembly of luminescent rare earth hybrid materials, which is based on the luminescent rare earth compounds and two or more other building units, including the other photoactive species. It covers the multi-component luminescent rare earth hybrids which was assembled with different(a) organic-inorganic polymeric units,(b)nanoporous units,(c) nanoparticle composites or(d) other developing special units. Finally, future challenges and opportunities in this field are discussed. Herein it mainly focuses on the work of Yan's group in recent years.
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.
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This work was supported by General Program of National Natural Science Foundation of China(No.816736112017):General Project of Heilongjiang Provincial Science Foundation(No.H2016076)Harbin Special Fund for Scientific and Technological Innovation Talent Research(No.2017RAQXJ090)。
文摘Traditional Chinese medicine decoction is a complex polydispersed phase system containing real solution,colloid solution,emulsion and suspension.The compound decoction of traditional Chinese medicine has complex components,including saponins,alkaloids,polysaccharides,flavonoids,amino acids and so on,which can be self-assembled to form gels,fibers,micelles,vesicles and so on.The self-assembled nano-phase not only neutralizes the single drug and reduces the toxicity and side effects,but also has its own pharmacological effects,which complement each other to achieve synergistic effect,so as to achieve the role of drug supplement,which is of research significance.The formation principle,solubilization and synergism principle and characterization method of multi-component self-assembly of traditional Chinese medicine compound decoction are discussed in this paper.
基金supported by Youth Innovation and Technology Project of high School in Shandong Province (No. 2019KJC021)Natural Science Foundation of Qinghai Province of China (No. 2020-ZJ-915)。
文摘A mild and efficient photochemical multi-component tandem reaction of quinoxalin-2(1H)-ones, alkenes and sulfinic acids is reported. This tandem reaction could be conveniently carried out at room temperature by employing 4Cz IPN as the metal-free photocatalyst and dioxygen(air) as the environmentally benign oxidant. A number of sulfonated quinoxalin-2(1H)-ones were obtained in satisfactory yields with favorable functional group tolerance. Radical trapping experiment and fluorescence quenching experiments were performed to elucidate this visible-light mediated radical reaction process.
基金supported by the Yunnan Seed Laboratory,China(202205AR070001-15)the National Natural Science Foundation of China,China(Grant No.32160697)。
文摘Juglans sigillata is an economically valuable nut crop renowned for its nutritional richness,including essential nutrients,antioxidants,and healthy fats,which boost human cardial,brain and gut health.Despite its importance,the lack of a complete genome assembly has been a stumbling block in its biological breeding process.Therefore,we generated deep coverage ultralong Oxford Nanopore Technology(ONT)and PacBio HiFi reads to construct a telomere-to-telomere(T2T)genome assembly.The final assembly spans 537.27 Mb with no gaps,demonstrating a remarkable completeness of 98.1%.We utilized a combination of transcriptome data and homologous proteins to annotate the genome,identifying 36018 protein-coding genes.Furthermore,we profiled global cytosine DNA methylations using ONT sequencing data.Global methylome analysis revealed high methylation levels in transposable element(TE)-rich chromosomal regions juxtaposed with comparatively lower methylation in gene-rich areas.By integrating a detailed multi-omics data analysis,we obtained valuable insights into the mechanism underlying endopleura coloration.This investigation led to the identification of eight candidate genes(e.g.ANR)involved in anthocyanin biosynthesis pathways,which are crucial for the development of color in plants.The comprehensive genome assembly and the understanding of the genetic basis of important traits like endopleura coloration will open avenues for more efficient breeding programs and improved crop quality.
基金financially supported by the Natural Science Foundation of ShanDong(Nos.ZR2023QD152 and ZR2021MD002).
文摘The application of photocatalytic technology in algae killing is limited by the non-floatability and difficulty in recycling of the photocatalysts.Loading photocatalyst on magnetic or floatable carriers is the most popular method for overcoming the above inadequacies.In this work,a CdZnS/TiO_(2) membrane photocatalyst with adjustable suspended depth(include floating)and flexible assembly is designed,which is less prone to dislodgement due to in situ synthesis and has a wider range of applicability than previously reported photocatalysts.The photocatalytic removal of Microcystis aeruginosa revealed that the suspended depth and distribution format of the CdZnS/TiO_(2) membrane photocatalysts have striking effects on the photocatalytic removal performance of Microcystis aeruginosa,the photocatalytic removal efficiency of CdZnS/TiO_(2)-2 membrane photocatalysts for Microcystis aeruginosa could reach to 98.6%in 60 min when the photocatalysts assembled in the form of 3×3 arrays suspended at a depth of 2 cm from the liquid surface.A tiny amount of TiO_(2) loading allows the formation of Z-Scheme heterojunction,resulting in accelerating the separation efficiency of photogenerated carriers,preserving the photogenerated electrons and holes with stronger reduction and oxidation ability and inhabiting the photo-corrosion of CdZnS.
基金the National Key R&D Program of China(No.2021YFA1501503)the National Natural Science Foundation of China(Nos.22250008,22121004,22108197)+3 种基金the Haihe Laboratory of Sustainable Chemical Transformations(No.CYZC202107)the Natural Science Foundation of Tianjin City(No.21JCZXJC00060)the Program of Introducing Talents of Discipline to Universities(No.BP0618007)the Xplorer Prize for financial support。
文摘Membrane electrode assembly(MEA)is widely considered to be the most promising type of electrolyzer for the practical application of electrochemical CO_(2) reduction reaction(CO_(2)RR).In MEAs,a square-shaped cross-section in the flow channel is normally adopted,the configuration optimization of which could potentially enhance the performance of the electrolyzer.This paper describes the numerical simulation study on the impact of the flow-channel cross-section shapes in the MEA electrolyzer for CO_(2)RR.The results show that wide flow channels with low heights are beneficial to the CO_(2)RR by providing a uniform flow field of CO_(2),especially at high current densities.Moreover,the larger the electrolyzer,the more significant the effect is.This study provides a theoretical basis for the design of high-performance MEA electrolyzers for CO_(2)RR.
基金support from the Ministry of Higher Education Malaysia under grant HICOE-2023-005.
文摘A unitized regenerative fuel cell(URFC)is a device that may function reversibly as either a fuel cell(FC)or water elec-trolysis(WE).An important component of this device is the Membrane electrode assembly(MEA).Therefore,this study aimed to compare the performance outcomes of MEA using electrodes with single and three catalyst layers.This study measured Electrochemical Surface Area(ECSA),Electrochemical Impedance Spectroscopy(EIS),X-ray Diffraction analysis(XRD),and X-ray Fluorescence(XRF).Furthermore,the round-trip efficiency(RTE)of the MEA,as w ell as the performance in FC and WE mode,was measured.In comparison,The ECSA values of Pt-Ru/C and Pt/C with three catalyst layers were higher than the single catalyst layer.This result was supported by electrode characterization data for XRD and XRF.The respective electrical conductivity values of Pt-Ru/C and Pt/C with three catalyst layers are also higher than the single cata-lyst layer,and the performance of URFC using MEA with three catalyst layers has the highest value of RTE among the MEA performances of URFC,which is 100%at a current density of 4 mA·cm-2.
基金Supported by National Key Research and Development Program of China(Grant No.2022YFB3304200)National Natural Science Foundation of China(Grant No.52205288)+1 种基金China Postdoctoral Science Foundation(Grant Nos.2024T170795,2024M762815)Zhejiang Provincial Key Research and Development Program(Grant No.2024C01029)。
文摘Assembly precision greatly influences the performance of complex high-end equipment.The traditional industrial assembly process and deviation transfer are implicit and uncertain,causing problems like poor component fit and hard-to-trace assembly stress concentration.Assemblers can only check whether the dimensional tolerance of the component design is exceeded step by step in combination with prior knowledge.Inversion in industrial assembly optimizes assembly and design by comparing real and theoretical results and doing inversion analysis to reduce assembly deviation.The digital twin(DT)technology visualizes and predicts the assembly process by mapping real and virtual model parameters and states simultaneously,expanding parameter range for inversion analysis and improving inversion result accuracy.Problems in improving industrial assembly precision and the significance and research status of DT-driven parametric inversion of assembly tools,processes and object precision are summarized.It analyzes vital technologies for assembly precision inversion such as multi-attribute assembly process parameter sensing,virtual modeling of high-fidelity assembly systems,twin synchronization of assembly process data models,multi-physical field simulation,and performance twin model construction of the assembly process.Combined with human-cyber-physical system,augmented reality,and generative intelligence,the outlook of DT-driven assembly precision inversion is proposed,providing support for DT's use in industrial assembly and precision improvement.
基金Supported by National Natural Science Foundation of China(Grant Nos.52475509 and U22A20203)Beijing Municipal Natural Science Foundation(Grant No.L248005)Hebei Provincial Natural Science Foundation(Grant No.E2023105059)。
文摘As the demands for assembly quality and efficiency increase,robot-assisted assembly applications are becoming more widespread.Peg-in-hole assembly,as a typical form of assembly,has been widely researched by scholars.Currently,robotic peg-in-hole assembly faces challenges such as complex analysis of part contact forces,difficulties in task modeling,and the failure of traditional strategies.Simply controlling the position of the robot's end effector cannot achieve high precision,high efficiency peg-in-hole assembly.Flexible assembly,especially intelligent flexible assembly,is becoming the future development trend.So there is a lack of comprehensive reviews on robotic flexible peg-in-hole assembly.This paper first outlines the basic components of peg-in-hole assembly and summarizes the two basic operational processes of peg-in-hole assembly,along with their related theoretical foundations.We then review and analyze the research on passive compliant assembly,active compliant assembly,and intelligent flexible assembly.Finally,it presents an outlook on the future development directions of robotic peg-in-hole assembly.
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 Natural Science Foundation of China(Nos.22325111,2220312,21871298,91956118)Guangdong Basic Research Center of Excellence for Functional Molecular Engineeringthe Sun Yat-sen University。
文摘Molecular recognition of fullerene using various host compounds is well-known in literature.But most studies focus on host-vip complexation in solution using host compounds with a single binding cavity.Herein,we report a series of highly preorganized janusarene derivatives with homoditopic binding sites.These novel janusarenes can bind and align various fullerenes such as C_(60),C_(70),C_(84),and Gd@C_(82)in a highly efficient manner.Robust shape complementary association and assembly are observed in solution,in the bulk solid state,in the liquid crystalline state,or on surface,and the assembled structures are characterized by nuclear magnetic resonance(NMR)titration,X-ray diffraction,polarized optical microscopy,and scanning tunneling microscopy.
基金sponsored by the National Natural Science Foundations of China under Grant Nos.12301315,12235007,11975131the Zhejiang Provincial Natural Science Foundation of China under Grant No.LQ20A010009。
文摘In the realm of nonlinear integrable systems,the presence of decompositions facilitates the establishment of linear superposition solutions and the derivation of novel coupled systems exhibiting nonlinear integrability.By focusing on single-component decompositions within the potential BKP hierarchy,it has been observed that specific linear superpositions of decomposition solutions remain consistent with the underlying equations.Moreover,through the implementation of multi-component decompositions within the potential BKP hierarchy,successful endeavors have been undertaken to formulate linear superposition solutions and novel coupled Kd V-type systems that resist decoupling via alterations in dependent variables.
基金financially supported by the National Natural Science Foundation of China(Nos.52271033 and 52071179)the Key program of National Natural Science Foundation of China(No.51931003)+2 种基金Natural Science Foundation of Jiangsu Province,China(No.BK20221493)Jiangsu Province Leading Edge Technology Basic Research Major Project(No.BK20222014)Foundation of“Qinglan Project”for Colleges and Universities in Jiangsu Province.
文摘Multi-component transition group metal borides(MMB_(2))have become a research hotspot due to their new composition design concepts and superior properties compared with conventional ceramics.Most of the current methods,however,are complicated and time-consuming,the mass production remains a chal-lenge.Herein,we proposed a new high-efficiency strategy for synthesis of MMB_(2)using molten aluminum as the medium for the first time.The prepared Al-containing multi-component borides(TiZrHfNbTa)B_(2)microcrystals had a homogeneous composition with a hexagonal AlB_(2)structure and ultra-high hardness value of∼35.3 GPa,which was much higher than data reported in the literature and the rule of mix-ture estimations.Furthermore,combined with the First-principles calculation results,we found that the Poisson’s ratio(v)values exhibit a clearly ascending trend from 0.17 at VEC=3.5 to 0.18 at VEC=3.4,then to 0.201 at VEC=3.2 with the increasing of Al content.This indicates that the intrinsic toughness of multi-component boride microcrystals is obviously enhanced by the trace-doped Al elements.Besides,the fabricated Al-containing multi-component boride microcrystals have superior oxidation activation en-ergy and structural stability.The enhanced oxidation resistance is mainly attributed to the formation of a protective Al2 O3 oxide layer and the lattice distortion,both of which lead to sluggish diffusion of O_(2).These findings propose a new unexplored avenue for the fabrication of MMB_(2)materials with supe-rior comprehensive performance including ultra-hardness and intrinsically improved thermo-mechanical properties.
文摘Despite the gradual transformation of traditional manufacturing by the Human-Robot Collaboration Assembly(HRCA),challenges remain in the robot’s ability to understand and predict human assembly intentions.This study aims to enhance the robot’s comprehension and prediction capabilities of operator assembly intentions by capturing and analyzing operator behavior and movements.We propose a video feature extraction method based on the Temporal Shift Module Network(TSM-ResNet50)to extract spatiotemporal features from assembly videos and differentiate various assembly actions using feature differences between video frames.Furthermore,we construct an action recognition and segmentation model based on the Refined-Multi-Scale Temporal Convolutional Network(Refined-MS-TCN)to identify assembly action intervals and accurately acquire action categories.Experiments on our self-built reducer assembly action dataset demonstrate that our network can classify assembly actions frame by frame,achieving an accuracy rate of 83%.Additionally,we develop a HiddenMarkovModel(HMM)integrated with assembly task constraints to predict operator assembly intentions based on the probability transition matrix and assembly task constraints.The experimental results show that our method for predicting operator assembly intentions can achieve an accuracy of 90.6%,which is a 13.3%improvement over the HMM without task constraints.
基金supported by National Natural Science Foundation of China(32170102)Natural Science Foundation of Tianjin(25JCLMJC00400)the Fundamental Research Funds for the Central Universities(63253191).
文摘Intestinal drug-resistant pathogens,e.g.,Salmonella enterica subsp.enterica serovar Typhimurium(S.Tm)and enteropathogenic Escherichia coli(E.coli),frequently cause life-threatening infectious enteritis.Probiotic-based therapy is a promising way to eliminate drug-resistant pathogens for treatment of infectious enteritis,but its colonizing and therapeutic efficacy after oral administration are limited.Here,we developed a facile therapeutic agent to treat infectious enteritis by co-assembly of the peptide nanodrug melittin-loaded MSN grafted by polysaccharide-binding protein(MMPB)with the famous probiotic bacteria Lactobacillus plantarum(Lac)and Bifidobacterium animalis subsp.lactis(Bif).The nanodrug was composed of the antimicrobial peptide melittin and mesoporous silica nanoparticles exposing the artificial polysaccharide-binding protein.Owing to presence of the artificial protein on the MMPB surface,the nanodrug strongly bound and cross-linked the probiotic cells,forming the Lac+Bif+MMPB co-assembly.During co-incubation with the kanamycin-resistant E.coli strain(Ecka),the co-assembly strongly reduced the viability of Ecka,leading to the increase in the ratio of probiotic to Ecka from 1.6 to 9.2.After oral administration of the co-assembly to themice pre-colonized by Ecka,Lac+Bif+MMPB almost eliminated the kanamycin-resistant gene in the intestine,and led to 2-3-fold higher levels of the probiotic cells than the nanodrug MMPB or the combined probiotics Lac+Bif.More importantly,in the mice suffering from enteritis caused by drug-resistant S.Tm,the co-assembly remarkably recovered the mouse body weight,reduced intestine colonization of S.Tm cells,and decreased the levels of pro-inflammatory cytokines in both serum and colons.This study realized the synthetic biology technique-mediated abiotic/biotic co-assembly for efficient treating infectious enteritis induced by drug-resistant pathogens.
基金supported by the National Natural Science Foundation of China(32241045,32241046,32241038)the Major Special Science and Technology Projects in Shanxi Province(202101140601027)+3 种基金Shanxi Provincial Agricultural Key Technologies Breakthrough Project(NYGG01)Doctoral Research Starting Project at Shanxi Agricultural University(2024BQ77)the National Key Research and Development Program of China(2023YFD1202705/2023YFD120270503,2023YFD1202703/2023YFD1202703-4)Shanxi HouJi Laboratory Self-proposed Research Project(202304010930003/202304010930003-03).
文摘Common bean(Phaseolus vulgaris L.)is a vital source of protein and essential nutrients for human consumption and plays a key role in sustainable agriculture due to its nitrogen-fixing ability(Nadeem et al.,2021).Kidney beans,a subcategory of dry common beans,are highly valued for their rich protein,dietary fiber,low fat content,and various trace elements(Garcia-Cordero et al.,2021).Despite the release of several de novo genome assemblies(Goodstein et al.,2012;Schmutz et al.,2014;Vlasova et al.,2016;Cortinovis et al.,2024),existing common bean genomes remain incomplete,particularly in complex regions such as centromeres and telomeres,limiting a comprehensive understanding of the genomic landscape.
