Microorganisms can colonize the surface of microplastics(MPs)to form a distinctive microbiome,known as a“plastisphere”which is regarded as an anthropogenic niche for microbial growth.However,bacterial community asse...Microorganisms can colonize the surface of microplastics(MPs)to form a distinctive microbiome,known as a“plastisphere”which is regarded as an anthropogenic niche for microbial growth.However,bacterial community assembly in virgin and aging MP plastispheres across different habitats is poorly understood.This study aims to assess the variations in bacterial community assembly across different niches and habitats with an in situ ex-periment,in which constructed forest wetland(FW),natural lake wetland(LW),and lotus pond wetland(LP)were habitats,and plastispheres of virgin and aging low-density polyethylene(LDPE)MPs,as well as surround-ing wetland soils were niches.Significant niche-related differences in bacterial communities were observed,with lower diversity and enrichment of potential plastic-degrading bacteria in the plastisphere than in the soil bacterial communities.Furthermore,habitat-related differences exerted a more pronounced influence on the beta-diversity patterns of the bacterial communities.The linear regression analyses indicated that the local species pool con-tributed more to bacterial community assembly in the LW wetland,whereas the relative abundance of species was the primary factor in the LP wetland.The null model analysis indicated that plastisphere bacterial communi-ties were predominantly driven by the stochastic process,with a more deterministic assembly observed in the LP wetland and soil bacterial communities.Additionally,the primary ecological process shaping plastisphere com-munities shifted from drift in the virgin LDPE to homogenising dispersal in the aging LDPE.This study provides new insights into the fate and ecological impacts of MPs in wetlands,thereby facilitating the effective regulations of plastic pollution.展开更多
Gold nanoclusters(AuNCs)are ultrasmall(<2 nm)aggregates of gold atoms that exhibit discrete electronic states,size-dependent photoluminescence,and exceptional biocompatibility,making them ideal candidates for thera...Gold nanoclusters(AuNCs)are ultrasmall(<2 nm)aggregates of gold atoms that exhibit discrete electronic states,size-dependent photoluminescence,and exceptional biocompatibility,making them ideal candidates for theranostic applications.Their tunable surface chemistry enables targeted delivery,while strong near-infrared emission and environmental responsiveness allow for sensitive detection and deep-tissue imaging.Recent advances have revealed that controlled assembly of AuNCs into higher-order architectures-guided by biological scaffolds such as nucleic acids,peptides,and proteins-can markedly enhance their optical and electronic properties through aggregation-induced emission(AiE)and stabilization of surface ligands.This review summarizes recent progress in the design and biomedical applications of AuNC assemblies generated using biomolecules as structure-directing scaffolds.Covalent and noncovalent interactions with biomolecules enable the formation of well-defined one-,two-,and three-dimensional structures with tunable morphologies and sizes.These assemblies display distinctive photophysical behaviors that have been exploited for biosensing,bioimaging,and therapeutic applications in both cellular and in vivo models.Compared with individual AuNCs,assembled systems offer improved uptake,prolonged circulation,and efficient clearance,while protecting labile cargos such as nucleic acids and proteins.Moreover,their ordered and defined architectures can be engineered for controlled drug release and synergistic photo-or radiotherapeutic effects.Despite these advances,fundamental understanding of how structural organization governs photophysical responses remains limited.Elucidating parameters such as intercluster spacing and loading density will be essential for optimizing performance.Overall,biologically guided AuNC assemblies represent a powerful platform for multifunctional biosensing and therapy,bridging nanoscale design with biological function.展开更多
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
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
How to substitute the human operator with a robot in various assembly tasks has to be taken into full con-sideration in intelligent manufacturing.Autonomous robotic assembly not only brings with high working effi-cien...How to substitute the human operator with a robot in various assembly tasks has to be taken into full con-sideration in intelligent manufacturing.Autonomous robotic assembly not only brings with high working effi-ciency,better product quality and low labor cost,but also helps relieve the increasingly severe problem of population aging.However,numerous existing challenges still prevent its wide applications when a robot is assigned to finish general tasks in unstructured environment.In order to provide a fundamental understanding of the various problems involved in robotic assembly,this paper carries out a review on its recent progress and challenges with 5 key technologies focused on:perception,end-effectors,control methods,learning methods and performance evaluation.Main works in these fields are reviewed and their characteristics are analyzed while typical assembly scenarios are covered.The challenges and future directions in robotic assembly are also dis-cussed on precise perception,robotic hand,error recovery and collaborative robot.In addition to providing a systematic summarization of the required key technologies,this work is aimed at motivating more potential researches in the community of robotics,artificial intelligence,and automation engineering.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
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
Lattice-type ultra-tall wind turbine towers are popular in China for their modular benefits in fabrication,transportation,and installation.Nonetheless,their conceptual design remains predominantly dependent on enginee...Lattice-type ultra-tall wind turbine towers are popular in China for their modular benefits in fabrication,transportation,and installation.Nonetheless,their conceptual design remains predominantly dependent on engineering experience,and a generally applicable approach is still absent.This study proposes a self-similar modular topology optimization framework for lattice-type wind turbine support structures and develops software for its application.A minimum weighted compliance formulation with a prescribed volume fraction is developed utilizing the variable density approach,wherein modular constraints and their corresponding sensitivity expressions are explicitly included.The method is applied to a reference wind turbine model to generate modular lattice configurations.The novel structural models are evaluated under three representative design load cases outlined in IEC 61400 by finite element analysis.Compared with the reference structure,the 12-layer self-similar modular design reduces the maximum deformation and von Mises stress by 39.5%and 51.1%,respectively,demonstrating a substantial stiffness improvement while preserving modularity.The suggested approach provides an efficient and practical tool for the conceptual design of modular lattice-type wind turbine towers.展开更多
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
IR64 is an elite Xian/indica variety developed by International Rice Research Institute(IRRl)in 1985,which has been the most widely grown variety and core breeding parent in South/Southeast Asia(Mackill and Khush,2018...IR64 is an elite Xian/indica variety developed by International Rice Research Institute(IRRl)in 1985,which has been the most widely grown variety and core breeding parent in South/Southeast Asia(Mackill and Khush,2018).IR64 has been utilized to develop stress-tolerant(such as drought-adapted and submergenceresistant)near-isogenic lines,underscoring its great potential in agricultural genomics(Tanaka et al.,2020).展开更多
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
Biological nitrogen fixation(BNF)is a crucial process that provides bioavailable nitrogen and supports primary production in freshwater lake ecosystems.However,the characteristics of diazotrophic community and nitroge...Biological nitrogen fixation(BNF)is a crucial process that provides bioavailable nitrogen and supports primary production in freshwater lake ecosystems.However,the characteristics of diazotrophic community and nitrogenase activity in freshwater lake sediments remain poorly understood.Here,we investigated the diazotrophic communities and nitrogenase activities in the sediments of three large river-connected freshwater lakes in eastern China using 15N-isotope tracing and nifH sequencing.The sediments in these lakes contained diverse nitrogenase genes that were phylogenetically grouped into Clusters I and III.The diazotrophic communities in the sedimentswere dominated by stochastic processes in Hongze Lake and Taihu Lake,which had heterogeneous habitats and shallower water depths,while in Poyang Lake,which had deeper water and a shorter hydraulic retention time,the assembly of the diazotrophic community in the sediments was dominated by homogeneous selection processes.Temperature and water depth were also found the key environmental factors affecting the sediment diazotrophic communities.Sediment nitrogenase activities varied in the three lakes and within distinct regions of an individual lake,ranging from 0 to 14.58 nmol/(kg·hr).Nitrogenase activity was significantly correlated with ferric iron,total phosphorus,and organic matter contents.Our results suggested that freshwater lake sediment contain high diversity of nitrogen-fixing microorganisms with potential metabolic diversity,and the community assembly patterns and nitrogenase activities varied with the lake habitat.展开更多
The flexible job shop scheduling problem(FJSP)is commonly encountered in practical manufacturing environments.A product is typically built by assembling multiple jobs during actual manufacturing.AGVs are normally used...The flexible job shop scheduling problem(FJSP)is commonly encountered in practical manufacturing environments.A product is typically built by assembling multiple jobs during actual manufacturing.AGVs are normally used to transport the jobs from the processing shop to the assembly shop,where they are assembled.Therefore,studying the integrated scheduling problem with its processing,transportation,and assembly stages is extremely beneficial and significant.This research studies the three-stage flexible job shop scheduling problem with assembly and AGV transportation(FJSP-T-A),which includes processing jobs,transporting them via AGVs,and assembling them.A mixed integer linear programming(MILP)model is established to obtain optimal solutions.As the MILP model is challenging for solving large-scale problems,a novel co-evolutionary algorithm(NCEA)with two different decoding methods is proposed.In NCEA,a restart operation is developed to improve the diversity of the population,and a multiple crossover strategy is designed to improve the quality of individuals.The validity of the MILP model is proven by analyzing its complexity.The effectiveness of the restart operator,multiple crossovers,and the proposed algorithm is demonstrated by calculating and analyzing the RPI values of each algorithm's results within the time limit and performing a paired t-test on the average values of each algorithm at the 95%confidence level.This paper studies FJSP-T-A by minimizing the makespan for the first time,and presents a MILP model and an NCEA with two different decoding methods.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
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
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
基金supported by Shanghai Municipal Natural Science Foundation,China(No.21ZR1446800)the National Natural Science Foundation of China(No.41877425)the Fundamental Research Funds for the Central Universities(No.226-2024-00052)。
文摘Microorganisms can colonize the surface of microplastics(MPs)to form a distinctive microbiome,known as a“plastisphere”which is regarded as an anthropogenic niche for microbial growth.However,bacterial community assembly in virgin and aging MP plastispheres across different habitats is poorly understood.This study aims to assess the variations in bacterial community assembly across different niches and habitats with an in situ ex-periment,in which constructed forest wetland(FW),natural lake wetland(LW),and lotus pond wetland(LP)were habitats,and plastispheres of virgin and aging low-density polyethylene(LDPE)MPs,as well as surround-ing wetland soils were niches.Significant niche-related differences in bacterial communities were observed,with lower diversity and enrichment of potential plastic-degrading bacteria in the plastisphere than in the soil bacterial communities.Furthermore,habitat-related differences exerted a more pronounced influence on the beta-diversity patterns of the bacterial communities.The linear regression analyses indicated that the local species pool con-tributed more to bacterial community assembly in the LW wetland,whereas the relative abundance of species was the primary factor in the LP wetland.The null model analysis indicated that plastisphere bacterial communi-ties were predominantly driven by the stochastic process,with a more deterministic assembly observed in the LP wetland and soil bacterial communities.Additionally,the primary ecological process shaping plastisphere com-munities shifted from drift in the virgin LDPE to homogenising dispersal in the aging LDPE.This study provides new insights into the fate and ecological impacts of MPs in wetlands,thereby facilitating the effective regulations of plastic pollution.
基金NR SEQUOIA(ANR-22-CE18-0006)Nan0Gold(ANR-22-CE29-0022)+3 种基金SAMURAI(ANR-24-CE19-2073-01)Wilive(ANR-24-CE09-2351-03)EUR CBH-EUR-GS(ANR-17-EURE 0003)for their financial supportthe French National Research Agency(Labex ARCANE,ANR-11-LABX-003 and CBH-EUR-GS,ANR-17-EURE-0003)that supported part of this study.
文摘Gold nanoclusters(AuNCs)are ultrasmall(<2 nm)aggregates of gold atoms that exhibit discrete electronic states,size-dependent photoluminescence,and exceptional biocompatibility,making them ideal candidates for theranostic applications.Their tunable surface chemistry enables targeted delivery,while strong near-infrared emission and environmental responsiveness allow for sensitive detection and deep-tissue imaging.Recent advances have revealed that controlled assembly of AuNCs into higher-order architectures-guided by biological scaffolds such as nucleic acids,peptides,and proteins-can markedly enhance their optical and electronic properties through aggregation-induced emission(AiE)and stabilization of surface ligands.This review summarizes recent progress in the design and biomedical applications of AuNC assemblies generated using biomolecules as structure-directing scaffolds.Covalent and noncovalent interactions with biomolecules enable the formation of well-defined one-,two-,and three-dimensional structures with tunable morphologies and sizes.These assemblies display distinctive photophysical behaviors that have been exploited for biosensing,bioimaging,and therapeutic applications in both cellular and in vivo models.Compared with individual AuNCs,assembled systems offer improved uptake,prolonged circulation,and efficient clearance,while protecting labile cargos such as nucleic acids and proteins.Moreover,their ordered and defined architectures can be engineered for controlled drug release and synergistic photo-or radiotherapeutic effects.Despite these advances,fundamental understanding of how structural organization governs photophysical responses remains limited.Elucidating parameters such as intercluster spacing and loading density will be essential for optimizing performance.Overall,biologically guided AuNC assemblies represent a powerful platform for multifunctional biosensing and therapy,bridging nanoscale design with biological function.
基金supported by National Natural Science Foundation of China(Grant 22407024)the Star-up Research Fund of Southeast University(RF1028624094)(X.W.)+7 种基金the China Postdoctoral Science Foundation(Grant 2025M772911)Natural Science Foundation of Jiangsu Province(Grants BK20251303)(X.L.)Postdoctoral Fellowship Program of CPSF(Grant GZC20251914)(X.L.)Jiangsu Funding Program for Excellent Postdoctoral Talent(Grant 2025ZB052)(X.L.)National Natural Science Foundation of China(Grant 22234002)(G.L.)National Key Research and Development Program of China(Grant 2023YFF0724100)(G.L.)Natural Science Foundation of Jiangsu Province(Grant BK20232007)(G.L.)Jiangsu ShuangChuang Team(Grant JSSCTD202409)(G.L.and X.W.).
文摘Targeted protein degradation(TPD)is an innovative strategy for selectively eliminating pathogenic proteins,enabling precise degradation of once-undruggable targets in cancer therapy.However,current TPD molecules are often limited by poor tumor targeting and the need for high doses.To overcome these limitations,assembly/disassembly-based TPD systems have been proposed to effectively degrade proteins of interest and enhance therapeutic efficacy.Herein,we summarize the recent advances in such TPD systems and categorize the strategies employed,including nanosphere morphology of assembled TPD systems,nanofiber morphology of assembled TPD systems,carrier-mediated TPD release systems,and stimulus-induced free TPD molecule formation nanosystems.Finally,we outline future directions and identify the remaining challenges in assembly/disassembly-based TPD systems.
基金Supported 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 National Natural Science Foundation of China(Grant No.52205009)Open Foundation of State Key Laboratory of Mechanical Transmission for Advanced Equipment of Chongqing University of China(Grant No.SKLMT-MSKFKT-202307)Taihu Lake Innovation Fund for the School of Future Technology of Southeast University of China.
文摘How to substitute the human operator with a robot in various assembly tasks has to be taken into full con-sideration in intelligent manufacturing.Autonomous robotic assembly not only brings with high working effi-ciency,better product quality and low labor cost,but also helps relieve the increasingly severe problem of population aging.However,numerous existing challenges still prevent its wide applications when a robot is assigned to finish general tasks in unstructured environment.In order to provide a fundamental understanding of the various problems involved in robotic assembly,this paper carries out a review on its recent progress and challenges with 5 key technologies focused on:perception,end-effectors,control methods,learning methods and performance evaluation.Main works in these fields are reviewed and their characteristics are analyzed while typical assembly scenarios are covered.The challenges and future directions in robotic assembly are also dis-cussed on precise perception,robotic hand,error recovery and collaborative robot.In addition to providing a systematic summarization of the required key technologies,this work is aimed at motivating more potential researches in the community of robotics,artificial intelligence,and automation engineering.
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.
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funded by the National Key Research and Development Program of China(No.2024YFE0208600)the National Natural Science Foundation of China(No.U24B2090).
文摘Lattice-type ultra-tall wind turbine towers are popular in China for their modular benefits in fabrication,transportation,and installation.Nonetheless,their conceptual design remains predominantly dependent on engineering experience,and a generally applicable approach is still absent.This study proposes a self-similar modular topology optimization framework for lattice-type wind turbine support structures and develops software for its application.A minimum weighted compliance formulation with a prescribed volume fraction is developed utilizing the variable density approach,wherein modular constraints and their corresponding sensitivity expressions are explicitly included.The method is applied to a reference wind turbine model to generate modular lattice configurations.The novel structural models are evaluated under three representative design load cases outlined in IEC 61400 by finite element analysis.Compared with the reference structure,the 12-layer self-similar modular design reduces the maximum deformation and von Mises stress by 39.5%and 51.1%,respectively,demonstrating a substantial stiffness improvement while preserving modularity.The suggested approach provides an efficient and practical tool for the conceptual design of modular lattice-type wind turbine towers.
基金supported by the National Key R&D Project of China(Nos.2022YFC2304205,2022YFC2304202)Key scientific research project of universities in Guangdong Province(No.2023KCXTD026)the Major Project of Guangzhou National Laboratory(No.GZNL2023A03002).
文摘Adjuvants enhance and prolong the immune response to therapeutic agents,such as drugs and vaccines.However,conventional adjuvants have limitations in terms of immune specificity and duration.Nanoadjuvants can leverage their nanoscale size to increase the capture efficacy of antigens by antigen-presenting cells and improve immunogen presentation for targeted delivery.Furthermore,noninvasive visualization of bifunctional nanoadjuvants with integrated efficacy and imaging postdelivery can provide insights into in vivo distribution and performance,aiding in the optimization and design of new dosage forms.This review systematically summarizes the structure,assembly,and function of nanoadjuvants alongside contrast agents.It delves into the impact of complex structures formed by nanoadjuvant-contrast agent interactions on antigen presentation,migration,imaging tracking,and visualization of immune cell recruitment.It also discusses how imaging can determine optimal immune intervals,vaccine safety,and toxicity while enabling diagnostic and therapeutic integration.Moreover,this paper discusses potential applications of novel adjuvants and promising imaging technologies that could have implications for future vaccine and drug development endeavors.
基金supported by the Natural Science Foundation of Anhui Province(2408085MC058 and 2308085QC91)National Natural Science Foundation of China(32301783and U21A20214)+5 种基金Innovation Program of the Chinese Academy of Agricultural Sciences(CAAS CSIAF-202303)Nanfan special project,CAAS(YYLH2309,YBXM2322,YYLH2401)Scientific Innovation 2030 Project(2022ZD0401703)CAAS Innovative Team Award,Science and Technology of Innovative research program of Anhui Province(202423m1005002)National Key Research and Development Program of China(2023YFD1200900)the Natural Science Foundation General Program of Hebei Province(C2024204242).
文摘IR64 is an elite Xian/indica variety developed by International Rice Research Institute(IRRl)in 1985,which has been the most widely grown variety and core breeding parent in South/Southeast Asia(Mackill and Khush,2018).IR64 has been utilized to develop stress-tolerant(such as drought-adapted and submergenceresistant)near-isogenic lines,underscoring its great potential in agricultural genomics(Tanaka et al.,2020).
文摘Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone to errors and lacks consistency,emphasizing the need for a reliable and automated inspection system.Leveraging both object detection and image segmentation approaches,this research proposes a vision-based solution for the detection of various kinds of tools in the toolkit using deep learning(DL)models.Two Intel RealSense D455f depth cameras were arranged in a top down configuration to capture both RGB and depth images of the toolkits.After applying multiple constraints and enhancing them through preprocessing and augmentation,a dataset consisting of 3300 annotated RGB-D photos was generated.Several DL models were selected through a comprehensive assessment of mean Average Precision(mAP),precision-recall equilibrium,inference latency(target≥30 FPS),and computational burden,resulting in a preference for YOLO and Region-based Convolutional Neural Networks(R-CNN)variants over ViT-based models due to the latter’s increased latency and resource requirements.YOLOV5,YOLOV8,YOLOV11,Faster R-CNN,and Mask R-CNN were trained on the annotated dataset and evaluated using key performance metrics(Recall,Accuracy,F1-score,and Precision).YOLOV11 demonstrated balanced excellence with 93.0%precision,89.9%recall,and a 90.6%F1-score in object detection,as well as 96.9%precision,95.3%recall,and a 96.5%F1-score in instance segmentation with an average inference time of 25 ms per frame(≈40 FPS),demonstrating real-time performance.Leveraging these results,a YOLOV11-based windows application was successfully deployed in a real-time assembly line environment,where it accurately processed live video streams to detect and segment tools within toolkits,demonstrating its practical effectiveness in industrial automation.The application is capable of precisely measuring socket dimensions by utilising edge detection techniques on YOLOv11 segmentation masks,in addition to detection and segmentation.This makes it possible to do specification-level quality control right on the assembly line,which improves the ability to examine things in real time.The implementation is a big step forward for intelligent manufacturing in the Industry 4.0 paradigm.It provides a scalable,efficient,and accurate way to do automated inspection and dimensional verification activities.
基金supported by the National Natural Science Foundation of China(Nos.51839011,42203079,and U2240208)the Carbon Peak/Neutralization Technology Innovation Project of Jiangsu Province,China(No.BK20220043)the Excellent Postdoctoral Project of Jiangsu Province,China(No.2022ZB452).
文摘Biological nitrogen fixation(BNF)is a crucial process that provides bioavailable nitrogen and supports primary production in freshwater lake ecosystems.However,the characteristics of diazotrophic community and nitrogenase activity in freshwater lake sediments remain poorly understood.Here,we investigated the diazotrophic communities and nitrogenase activities in the sediments of three large river-connected freshwater lakes in eastern China using 15N-isotope tracing and nifH sequencing.The sediments in these lakes contained diverse nitrogenase genes that were phylogenetically grouped into Clusters I and III.The diazotrophic communities in the sedimentswere dominated by stochastic processes in Hongze Lake and Taihu Lake,which had heterogeneous habitats and shallower water depths,while in Poyang Lake,which had deeper water and a shorter hydraulic retention time,the assembly of the diazotrophic community in the sediments was dominated by homogeneous selection processes.Temperature and water depth were also found the key environmental factors affecting the sediment diazotrophic communities.Sediment nitrogenase activities varied in the three lakes and within distinct regions of an individual lake,ranging from 0 to 14.58 nmol/(kg·hr).Nitrogenase activity was significantly correlated with ferric iron,total phosphorus,and organic matter contents.Our results suggested that freshwater lake sediment contain high diversity of nitrogen-fixing microorganisms with potential metabolic diversity,and the community assembly patterns and nitrogenase activities varied with the lake habitat.
基金Supported by National Natural Science Foundation of China(Grant Nos.52205529 and 62303204)the Youth Innovation Team Program of Shandong Higher Education Institution(Grant No.2023KJ206)the Guangyue Youth Scholar Innovation Talent Program support received from Liaocheng University(Grant No.LCUGYTD2022-03)。
文摘The flexible job shop scheduling problem(FJSP)is commonly encountered in practical manufacturing environments.A product is typically built by assembling multiple jobs during actual manufacturing.AGVs are normally used to transport the jobs from the processing shop to the assembly shop,where they are assembled.Therefore,studying the integrated scheduling problem with its processing,transportation,and assembly stages is extremely beneficial and significant.This research studies the three-stage flexible job shop scheduling problem with assembly and AGV transportation(FJSP-T-A),which includes processing jobs,transporting them via AGVs,and assembling them.A mixed integer linear programming(MILP)model is established to obtain optimal solutions.As the MILP model is challenging for solving large-scale problems,a novel co-evolutionary algorithm(NCEA)with two different decoding methods is proposed.In NCEA,a restart operation is developed to improve the diversity of the population,and a multiple crossover strategy is designed to improve the quality of individuals.The validity of the MILP model is proven by analyzing its complexity.The effectiveness of the restart operator,multiple crossovers,and the proposed algorithm is demonstrated by calculating and analyzing the RPI values of each algorithm's results within the time limit and performing a paired t-test on the average values of each algorithm at the 95%confidence level.This paper studies FJSP-T-A by minimizing the makespan for the first time,and presents a MILP model and an NCEA with two different decoding methods.
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.
