As maternal parents, diploid （L202-2x） and autotetraploid （L202-4x） of Oryza sativa cv. L2O2 were crossed with O. officinalis. Embryo development and fertilization in these two crosses were comparatively studied. ...As maternal parents, diploid （L202-2x） and autotetraploid （L202-4x） of Oryza sativa cv. L2O2 were crossed with O. officinalis. Embryo development and fertilization in these two crosses were comparatively studied. There were no mature hybrid seeds obtained because all the hybridized spikelets died 30 days after pollination. The main reasons for no seed set were abnormal fertilization and development of the embryos and endosperms in the interspecific hybrids. There were doublefertilization, egg cell single-fertilization and non-fertilization in these crosses. Although 59.45% and 54.87% of hybrid embryos produced in the crosses of L202-2x/O. officinalis and L202-4x/O. officinalis, respectively, hybrid embryos ceased to develop or degenerated and plenty of free endosperm nuclei were in disaggregating state without developing cellular endosperms three days after pollination. Besides, some embryological differences in these two crosses were found, that is, the rate of double-fertilization and total rate of doubleand single-fertilization in L202-2x/O. officinalis were higher than those in L202-4x/O. officinalis. The embryo and endosperm of hybrids developed more slowly, and embryos and free endosperm nuclei were more severely degenerated in L202-4x/O. officinalis than in L202-2x/O. officinalis. Five days after pollination, a few of embryos in L202-2x/O. officinalis developed into pear-shaped ones, however, embryos in L202-4x/O. officinalis were all degenerated. Therefore, it is more difficult to obtain interspecific hybrids by wide crosses between autotetraploid of O. sativa and O. officinalis.展开更多
The identification and understanding of cryptic intraspecific evolutionary units(lineages) are crucial for planning effective conservation strategies aimed at preserving genetic diversity in endangered species.However...The identification and understanding of cryptic intraspecific evolutionary units(lineages) are crucial for planning effective conservation strategies aimed at preserving genetic diversity in endangered species.However, the factors driving the evolution and maintenance of these intraspecific lineages in most endangered species remain poorly understood. In this study, we conducted resequencing of 77 individuals from 22 natural populations of Davidia involucrata, a “living fossil” dove tree endemic to central and southwest China. Our analysis revealed the presence of three distinct local lineages within this endangered species, which emerged approximately 3.09 and 0.32 million years ago. These divergence events align well with the geographic and climatic oscillations that occurred across the distributional range.Additionally, we observed frequent hybridization events between the three lineages, resulting in the formation of hybrid populations in their adjacent as well as disjunct regions. These hybridizations likely arose from climate-driven population expansion and/or long-distance gene flow. Furthermore, we identified numerous environment-correlated gene variants across the total and many other genes that exhibited signals of positive evolution during the maintenance of two major local lineages. Our findings shed light on the highly dynamic evolution underlying the remarkably similar phenotype of this endangered species. Importantly, these results not only provide guidance for the development of conservation plans but also enhance our understanding of evolutionary past for this and other endangered species with similar histories.展开更多
Single-atom catalysts(SACs)are rapidly standing at the forefront of catalytic development due to their unique structures with significantly different catalytic activity,selectivity,and stability from conventional nano...Single-atom catalysts(SACs)are rapidly standing at the forefront of catalytic development due to their unique structures with significantly different catalytic activity,selectivity,and stability from conventional nanocatalysts.The electronic properties and catalytic performances of SACs hinge on the results of orbital hybridization of isolated central atoms with ligand atoms as well as of central atoms with bonding atoms provided by intermediates.Therefore,we conduct multifaceted explorations around orbital hybridizations in single-atom catalysis to elucidate the structure-activity relationships.Firstly,we introduce the basic theoretical knowledge related to orbital hybridizations,and summarize the main descriptors of orbital hybridizations,focusing on the discussion of the types of orbital hybridizations in singleatom catalysis.Then,we briefly sum up the application of orbital hybridizations in single-atom electrocatalysis and put forward important strategies for regulating orbital hybridizations in SACs to improve the catalytic performances.Finally,we present a personal perspective on the future challenges and opportunities of orbital hybridizations in single-atom catalysis.展开更多
In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honey...In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honeycomb cells,was created by constructing arrangement matrices to achieve structural lightweight.The machine learning(ML)framework consisted of a neural network(NN)forward regression model for predicting impact resistance and a multi-objective optimization algorithm for generating high-performance designs.The surrogate of the local design space was initially realized by establishing the NN in the small sample dataset,and the active learning strategy was used to continuously extended the local optimal design until the model converged in the global space.The results indicated that the active learning strategy significantly improved the inference capability of the NN model in unknown design domains.By guiding the iteration direction of the optimization algorithm,lightweight designs with high impact resistance were identified.The energy absorption capacity of the optimal design reached 94.98%of the EARE honeycomb,while the initial peak stress and mass decreased by 28.85%and 19.91%,respectively.Furthermore,Shapley Additive Explanations(SHAP)for global explanation of the NN indicated a strong correlation between the arrangement mode of HCS and its impact resistance.By reducing the stiffness of the cells at the top boundary of the structure,the initial impact damage sustained by the structure can be significantly improved.Overall,this study proposed a general lightweight design method for array structures under impact loads,which is beneficial for the widespread application of honeycomb-based protective structures.展开更多
Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may r...Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships.Networking structures are highly sensitive in social networks,requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks.In addition,they miss out on accurately identifying clusters.Since single-objective optimization cannot always generate accurate and comprehensive results,as multi-objective optimization can.Therefore,we utilized two objective functions that enable strong connections between communities and weak connections between them.In this study,we utilized the intra function,which has proven effective in state-of-the-art research studies.We proposed a new inter-function that has demonstrated its effectiveness by making the objective of detecting external connections between communities is to make them more distinct and sparse.Furthermore,we proposed a Multi-Objective community strength enhancement algorithm(MOCSE).The proposed algorithm is based on the framework of the Multi-Objective Evolutionary Algorithm with Decomposition(MOEA/D),integrated with a new heuristic mutation strategy,community strength enhancement(CSE).The results demonstrate that the model is effective in accurately identifying community structures while also being computationally efficient.The performance measures used to evaluate the MOEA/D algorithm in our work are normalized mutual information(NMI)and modularity(Q).It was tested using five state-of-the-art algorithms on social networks,comprising real datasets(Zachary,Dolphin,Football,Krebs,SFI,Jazz,and Netscience),as well as twenty synthetic datasets.These results provide the robustness and practical value of the proposed algorithm in multi-objective community identification.展开更多
Sluggish sulfur redox kinetics remain a critical bottleneck in the advancement of high-performance lithiumsulfur batteries(LSBs).Single-atom catalysts(SACs)offer a promising solution to this limitation,particularly wh...Sluggish sulfur redox kinetics remain a critical bottleneck in the advancement of high-performance lithiumsulfur batteries(LSBs).Single-atom catalysts(SACs)offer a promising solution to this limitation,particularly when their coordination structures are carefully engineered.Here,we develop a chromium-based SAC featuring a unique undercoordinated CrN_(3) configuration to boost sulfur electrochemistry.Compared with conventional CrN_(4),the CrN_(3) motif lowers 3d orbital occupancy and meanwhile activates the in-plane hybridizations with S 3p orbitals upon interaction with polysulfides,contributing to moderate adsorption strength and reduced energy barriers for bidirectional sulfur conversions.Additionally,the integration of the two-dimensional(2D)porous framework ensures abundant electrochemically active surfaces and efficiently exposed active sites.As a result,CrN_(3)-based cells demonstrate fast and durable sulfur redox reactions,enabling an ultralow capacity decay of 0.0075%per cycle over 1000 cycles and a high-rate capability of 651.9 mAh·g^(-1)at 5 C.The CrN_(3) catalyst retains robust catalytic efficiency under demanding conditions,delivering a high areal capacity of 5.53 mAh·cm^(-2) at high sulfur loading and lean electrolyte.This work establishes a compelling paradigm of SAC coordination engineering for designing advanced sulfur electrocatalysts for next-generation LSBs.展开更多
Oxaliplatin(OXA)has shown excellent potential in inducing immunogenic cell death and enhancing immunotherapy.However,the poor physicochemical properties of oxaliplatin make it difficult to achieve efficient synchronou...Oxaliplatin(OXA)has shown excellent potential in inducing immunogenic cell death and enhancing immunotherapy.However,the poor physicochemical properties of oxaliplatin make it difficult to achieve efficient synchronous delivery and synergistic immunotherapy with immune checkpoint inhibitors.To address this,we designed structurally optimized dual-wing butterfly prodrugs:oxaliplatin prodrug(POP)that enhances immunogenicity and reducible NLG919 homodimer(NSSN)that mitigates immunosuppression.Structural optimization of dual-wing butterfly prodrugs significantly enhanced lipid solubility compared to the parent drugs.It is worth noting that we assembled two dual-wing butterfly prodrugs,POP and NSSN,together into hybrid nanoassemblies(NAs),achieving advantages such as stable assembly,flexible dosing,and collaborative therapy.Dual-wing butterfly prodrug-driven hybrid NAs demonstrated enhanced antitumor efficacy and metastasis control in experimental models,with biocompatibility confirmed through biosafety evaluations.This work proposes a co-delivery strategy based on dual-wing butterfly prodrugs as a clinically translatable candidate.展开更多
In order to address environmental pollution and resource depletion caused by traditional power generation,this paper proposes an adaptive iterative dynamic-balance optimization algorithm that integrates the Improved D...In order to address environmental pollution and resource depletion caused by traditional power generation,this paper proposes an adaptive iterative dynamic-balance optimization algorithm that integrates the Improved Dung Beetle Optimizer(IDBO)with VariationalMode Decomposition(VMD).The IDBO-VMD method is designed to enhance the accuracy and efficiency of wind-speed time-series decomposition and to effectively smooth photovoltaic power fluctuations.This study innovatively improves the traditional variational mode decomposition(VMD)algorithm,and significantly improves the accuracy and adaptive ability of signal decomposition by IDBO selfoptimization of key parameters K and a.On this basis,Fourier transform technology is used to define the boundary point between high frequency and low frequency signals,and a targeted energy distribution strategy is proposed:high frequency fluctuations are allocated to supercapacitors to quickly respond to transient power fluctuations;Lowfrequency components are distributed to lead-carbon batteries,optimizing long-term energy storage and scheduling efficiency.This strategy effectively improves the response speed and stability of the energy storage system.The experimental results demonstrate that the IDBO-VMD algorithm markedly outperforms traditional methods in both decomposition accuracy and computational efficiency.Specifically,it effectively reduces the charge–discharge frequency of the battery,prolongs battery life,and optimizes the operating ranges of the state-of-charge(SOC)for both leadcarbon batteries and supercapacitors.In addition,the energy management strategy based on the algorithm not only improves the overall energy utilization efficiency of the system,but also shows excellent performance in the dynamic management and intelligent scheduling of renewable energy generation.展开更多
Carbon superstructures with multiscale hierarchies and functional attributes represent an appealing cathode candidate for zinc hybrid capacitors,but their tailor-made design to optimize the capacitive activity remains...Carbon superstructures with multiscale hierarchies and functional attributes represent an appealing cathode candidate for zinc hybrid capacitors,but their tailor-made design to optimize the capacitive activity remains a confusing topic.Here we develop a hydrogen-bond-oriented interfacial super-assembly strategy to custom-tailor nanosheet-intertwined spherical carbon superstructures(SCSs)for Zn-ion storage with double-high capacitive activity and durability.Tetrachlorobenzoquinone(H-bond acceptor)and dimethylbenzidine(H-bond donator)can interact to form organic nanosheet modules,which are sequentially assembled,orientally compacted and densified into well-orchestrated superstructures through multiple H-bonds(N-H···O).Featured with rich surface-active heterodiatomic motifs,more exposed nanoporous channels,and successive charge migration paths,SCSs cathode promises high accessibility of built-in zincophilic sites and rapid ion diffusion with low energy barriers(3.3Ωs-0.5).Consequently,the assembled Zn||SCSs capacitor harvests all-round improvement in Zn-ion storage metrics,including high energy density(166 Wh kg-1),high-rate performance(172 m Ah g^(-1)at 20 A g^(-1)),and long-lasting cycling lifespan(95.5%capacity retention after 500,000 cycles).An opposite chargecarrier storage mechanism is rationalized for SCSs cathode to maximize spatial capacitive charge storage,involving high-kinetics physical Zn^(2+)/CF_(3)SO_(3)-adsorption and chemical Zn^(2+)redox with carbonyl/pyridine groups.This work gives insights into H-bond-guided interfacial superassembly design of superstructural carbons toward advanced energy storage.展开更多
This systematic review aims to comprehensively examine and compare deep learning methods for brain tumor segmentation and classification using MRI and other imaging modalities,focusing on recent trends from 2022 to 20...This systematic review aims to comprehensively examine and compare deep learning methods for brain tumor segmentation and classification using MRI and other imaging modalities,focusing on recent trends from 2022 to 2025.The primary objective is to evaluate methodological advancements,model performance,dataset usage,and existing challenges in developing clinically robust AI systems.We included peer-reviewed journal articles and highimpact conference papers published between 2022 and 2025,written in English,that proposed or evaluated deep learning methods for brain tumor segmentation and/or classification.Excluded were non-open-access publications,books,and non-English articles.A structured search was conducted across Scopus,Google Scholar,Wiley,and Taylor&Francis,with the last search performed in August 2025.Risk of bias was not formally quantified but considered during full-text screening based on dataset diversity,validation methods,and availability of performance metrics.We used narrative synthesis and tabular benchmarking to compare performance metrics(e.g.,accuracy,Dice score)across model types(CNN,Transformer,Hybrid),imaging modalities,and datasets.A total of 49 studies were included(43 journal articles and 6 conference papers).These studies spanned over 9 public datasets(e.g.,BraTS,Figshare,REMBRANDT,MOLAB)and utilized a range of imaging modalities,predominantly MRI.Hybrid models,especially ResViT and UNetFormer,consistently achieved high performance,with classification accuracy exceeding 98%and segmentation Dice scores above 0.90 across multiple studies.Transformers and hybrid architectures showed increasing adoption post2023.Many studies lacked external validation and were evaluated only on a few benchmark datasets,raising concerns about generalizability and dataset bias.Few studies addressed clinical interpretability or uncertainty quantification.Despite promising results,particularly for hybrid deep learning models,widespread clinical adoption remains limited due to lack of validation,interpretability concerns,and real-world deployment barriers.展开更多
In underwater target search path planning,the accuracy of sonar models directly dictates the accurate assessment of search coverage.In contrast to physics-informed sonar models,traditional geometric sonar models fail ...In underwater target search path planning,the accuracy of sonar models directly dictates the accurate assessment of search coverage.In contrast to physics-informed sonar models,traditional geometric sonar models fail to accurately characterize the complex influence of marine environments.To overcome these challenges,we propose an acoustic physics-informed intelligent path planning framework for underwater target search,integrating three core modules:The acoustic-physical modeling module adopts 3D ray-tracing theory and the active sonar equation to construct a physics-driven sonar detection model,explicitly accounting for environmental factors that influence sonar performance across heterogeneous spaces.The hybrid parallel computing module adopts a message passing interface(MPI)/open multi-processing(Open MP)hybrid strategy for large-scale acoustic simulations,combining computational domain decomposition and physics-intensive task acceleration.The search path optimization module adopts the covariance matrix adaptation evolution algorithm to solve continuous optimization problems of heading angles,which ensures maximum search coverage for targets.Largescale experiments conducted in the Pacific and Atlantic Oceans demonstrate the framework's effectiveness:(1)Precise capture of sonar detection range variations from 5.45 km to 50 km in heterogeneous marine environments.(2)Significant speedup of 453.43×for acoustic physics modeling through hybrid parallelization.(3)Notable improvements of 7.23%in detection coverage and 15.86%reduction in optimization time compared to the optimal baseline method.The framework provides a robust solution for underwater search missions in complex marine environments.展开更多
Multi-label feature selection(MFS)is a crucial dimensionality reduction technique aimed at identifying informative features associated with multiple labels.However,traditional centralized methods face significant chal...Multi-label feature selection(MFS)is a crucial dimensionality reduction technique aimed at identifying informative features associated with multiple labels.However,traditional centralized methods face significant challenges in privacy-sensitive and distributed settings,often neglecting label dependencies and suffering from low computational efficiency.To address these issues,we introduce a novel framework,Fed-MFSDHBCPSO—federated MFS via dual-layer hybrid breeding cooperative particle swarm optimization algorithm with manifold and sparsity regularization(DHBCPSO-MSR).Leveraging the federated learning paradigm,Fed-MFSDHBCPSO allows clients to perform local feature selection(FS)using DHBCPSO-MSR.Locally selected feature subsets are encrypted with differential privacy(DP)and transmitted to a central server,where they are securely aggregated and refined through secure multi-party computation(SMPC)until global convergence is achieved.Within each client,DHBCPSO-MSR employs a dual-layer FS strategy.The inner layer constructs sample and label similarity graphs,generates Laplacian matrices to capture the manifold structure between samples and labels,and applies L2,1-norm regularization to sparsify the feature subset,yielding an optimized feature weight matrix.The outer layer uses a hybrid breeding cooperative particle swarm optimization algorithm to further refine the feature weight matrix and identify the optimal feature subset.The updated weight matrix is then fed back to the inner layer for further optimization.Comprehensive experiments on multiple real-world multi-label datasets demonstrate that Fed-MFSDHBCPSO consistently outperforms both centralized and federated baseline methods across several key evaluation metrics.展开更多
Co_(3)S_(4)electrocatalysts with mixed valences of Co ions and excellent structural stability possess favorable oxygen evolution reaction(OER)activity,yet challenges remain in fabricating rechargeable lithiumoxygen ba...Co_(3)S_(4)electrocatalysts with mixed valences of Co ions and excellent structural stability possess favorable oxygen evolution reaction(OER)activity,yet challenges remain in fabricating rechargeable lithiumoxygen batteries(LOBs)due to their poor OER performance,resulting from poor electrical conductivity and overly strong intermediate adsorption.In this work,fancy double heterojunctions on 1T/2H-MoS_(2)@Co_(3)S_(4)(1T/2H-MCS)were constructed derived from the charge donation from Co to Mo ions,thus inducing the phase transformation of Mo S_(2)from 2H to 1T.The unique features of these double heterojunctions endow the1T/2H-MCS with complementary catalysis during charging and discharging processes.It is worth noting that 1T-Mo S2@Co3S4could provide fast Co-S-Mo electron transport channels to promote ORR/OER kinetics,and 2H-MoS_(2)@Co_(3)S_(4)contributed to enabling moderate egorbital occupancy when adsorbed with oxygen-containing intermediates.On the basis,the Li_(2)O_(2)nucleation route was changed to solution and surface dual pathways,improving reversible deposition and decomposition kinetics.As a result,1T/2H-MCS cathodes exhibit an improved electrocatalytic performance compared with those of Co_(3)S_(4)and Mo S2cathodes.This innovative heterostructure design provides a reliable strategy to construct efficient transition metal sulfide catalysts by improving electrical conductivity and modulating adsorption toward oxygenated intermediates for LOBs.展开更多
Protonic ceramic fuel cells(PCFCs)have been recognized as promising power generation devices for future clean energy systems,owing to their relatively low activation energy for proton migration and high energy convers...Protonic ceramic fuel cells(PCFCs)have been recognized as promising power generation devices for future clean energy systems,owing to their relatively low activation energy for proton migration and high energy conversion efficiency.In certain application scenarios,the use of N_(2)O(a potent greenhouse gas),as an alternative oxidant to air,presents a feasible strategy.Herein,we report for the first time the operation of PCFCs employing N_(2)O as the oxidant.A hybrid Pr_(2)Ni_(0.6)Co_(0.4)O_(4-δ)(PNCO-214)catalyst is developed,comprising Ruddlesden-Popper(R-P)structured Pr_(4)Ni_(1.8)Co_(1.2)O_(10-δ)(PNCO-4310)and fluorite structured Pr_(6)O_(11)(PO-611),which synergistically exhibits exceptional catalytic activity toward both N_(2)O decomposition and the oxygen reduction reaction,achieving a conversion over 92% and an area specific resistance of 1.301Ω·cm^(2) at 600℃.Quasi-insitu temperature-dependent Fourier transform infrared(FTIR)and electrochemical impedance spectroscopy analyses reveal that abundant oxygen vacancies in PNCO-214 facilitate rapid adsorption and dissociation of N_(2)O into N_(2) and O_(2),while also promoting the surface exchange kinetics of proton/oxygen during oxygen reduction reaction(ORR).When applied in an anode-supported single cell with PNCO-214 cathode operating under N_(2)O,outstanding power density and low resistance are achieved,delivering 0.801 W·cm^(-2) and 0.245Ω·cm^(2) at 600℃.Satisfactory performance is also maintained even when the temperature is reduced to 500℃.Furthermore,the single cell demonstrates relatively good stability with negligible degradation over 130 h at 600℃ and 0.7 V.These findings underscore the potential of PNCO-214 as a highly effective cathode catalyst for enabling the use of N_(2)O as a viable oxidant in PCFCs for specific industrial applications.展开更多
The hybridization gap in strained-layer InAs/In_(x)Ga_(1−x) Sb quantum spin Hall insulators(QSHIs)is significantly enhanced compared to binary InAs/GaSb QSHI structures,where the typical indium composition,x,ranges be...The hybridization gap in strained-layer InAs/In_(x)Ga_(1−x) Sb quantum spin Hall insulators(QSHIs)is significantly enhanced compared to binary InAs/GaSb QSHI structures,where the typical indium composition,x,ranges between 0.2 and 0.4.This enhancement prompts a critical question:to what extent can quantum wells(QWs)be strained while still preserving the fundamental QSHI phase?In this study,we demonstrate the controlled molecular beam epitaxial growth of highly strained-layer QWs with an indium composition of x=0.5.These structures possess a substantial compressive strain within the In_(0.5)Ga_(0.5)Sb QW.Detailed crystal structure analyses confirm the exceptional quality of the resulting epitaxial films,indicating coherent lattice structures and the absence of visible dislocations.Transport measurements further reveal that the QSHI phase in InAs/In_(0.5)Ga_(0.5)Sb QWs is robust and protected by time-reversal symmetry.Notably,the edge states in these systems exhibit giant magnetoresistance when subjected to a modest perpendicular magnetic field.This behavior is in agreement with the𝑍2 topological property predicted by the Bernevig–Hughes–Zhang model,confirming the preservation of topologically protected edge transport in the presence of enhanced bulk strain.展开更多
To enhance power flow regulation in scenarios involving large-scale renewable energy transmission via high-voltage direct current(HVDC)links and multi-infeed DC systems in load-center regions,this paper proposes a hyb...To enhance power flow regulation in scenarios involving large-scale renewable energy transmission via high-voltage direct current(HVDC)links and multi-infeed DC systems in load-center regions,this paper proposes a hybrid modular multilevel converter–capacitor-commutated line-commutated converter(MMC-CLCC)HVDC transmission system and its corresponding control strategy.First,the system topology is constructed,and a submodule configuration method for the MMC—combining full-bridge submodules(FBSMs)and half-bridge submodules(HBSMs)—is proposed to enable direct power flow reversal.Second,a hierarchical control strategy is introduced,includingMMCvoltage control,CLCC current control,and a coordinationmechanism,along with the derivation of the hybrid system’s power flow reversal characteristics.Third,leveraging the CLCC’s fast current regulation and theMMC’s negative voltage control capability,a coordinated power flow reversal control strategy is developed.Finally,an 800 kV MMC-CLCC hybrid HVDC system is modeled in PSCAD/EMTDC to validate the power flow reversal performance under a high proportion of full-bridge submodule configuration.Results demonstrate that the proposed control strategy enables rapid(1-s transition)and smooth switching of bidirectional power flow without modifying the structure of primary equipment:the transient fluctuation ofDC voltage from the rated value(UdcN)to themaximumreverse voltage(-kUdcN)is less than 5%;the DC current strictly follows the preset characteristic curve with a deviation of≤3%;the active power reverses continuously,and the system maintains stable operation throughout the reversal process.展开更多
基金supported by the Guangdong Provincial Key Project of Natural Science Foundation, China (Grant No. 021037)Guangdong Province Natural Science Foundation, China (Grant No. 7301008)+1 种基金South China Agricultural University President Foundation, China (Grant No. 2007K036)The Confocal Laser Scanning Microscope was provided by the Testing Center of South China Agricultural University, Guangzhou, China
文摘As maternal parents, diploid （L202-2x） and autotetraploid （L202-4x） of Oryza sativa cv. L2O2 were crossed with O. officinalis. Embryo development and fertilization in these two crosses were comparatively studied. There were no mature hybrid seeds obtained because all the hybridized spikelets died 30 days after pollination. The main reasons for no seed set were abnormal fertilization and development of the embryos and endosperms in the interspecific hybrids. There were doublefertilization, egg cell single-fertilization and non-fertilization in these crosses. Although 59.45% and 54.87% of hybrid embryos produced in the crosses of L202-2x/O. officinalis and L202-4x/O. officinalis, respectively, hybrid embryos ceased to develop or degenerated and plenty of free endosperm nuclei were in disaggregating state without developing cellular endosperms three days after pollination. Besides, some embryological differences in these two crosses were found, that is, the rate of double-fertilization and total rate of doubleand single-fertilization in L202-2x/O. officinalis were higher than those in L202-4x/O. officinalis. The embryo and endosperm of hybrids developed more slowly, and embryos and free endosperm nuclei were more severely degenerated in L202-4x/O. officinalis than in L202-2x/O. officinalis. Five days after pollination, a few of embryos in L202-2x/O. officinalis developed into pear-shaped ones, however, embryos in L202-4x/O. officinalis were all degenerated. Therefore, it is more difficult to obtain interspecific hybrids by wide crosses between autotetraploid of O. sativa and O. officinalis.
基金supported by the Second Tibetan Plateau Scientific Expedition and Research program (No. 2019QZKK0502)Strategic Priority Research Program of Chinese Academy of Sciences (No. XDB31010300)+1 种基金Fundamental Research Funds for the Central UniversitiesInternational Collaboration 111 Program (BP0719040)。
文摘The identification and understanding of cryptic intraspecific evolutionary units(lineages) are crucial for planning effective conservation strategies aimed at preserving genetic diversity in endangered species.However, the factors driving the evolution and maintenance of these intraspecific lineages in most endangered species remain poorly understood. In this study, we conducted resequencing of 77 individuals from 22 natural populations of Davidia involucrata, a “living fossil” dove tree endemic to central and southwest China. Our analysis revealed the presence of three distinct local lineages within this endangered species, which emerged approximately 3.09 and 0.32 million years ago. These divergence events align well with the geographic and climatic oscillations that occurred across the distributional range.Additionally, we observed frequent hybridization events between the three lineages, resulting in the formation of hybrid populations in their adjacent as well as disjunct regions. These hybridizations likely arose from climate-driven population expansion and/or long-distance gene flow. Furthermore, we identified numerous environment-correlated gene variants across the total and many other genes that exhibited signals of positive evolution during the maintenance of two major local lineages. Our findings shed light on the highly dynamic evolution underlying the remarkably similar phenotype of this endangered species. Importantly, these results not only provide guidance for the development of conservation plans but also enhance our understanding of evolutionary past for this and other endangered species with similar histories.
基金supported by the Natural Science Foundation of Jilin Province(20220101051JC)the National Natural Science Foundation of China(22075099)。
文摘Single-atom catalysts(SACs)are rapidly standing at the forefront of catalytic development due to their unique structures with significantly different catalytic activity,selectivity,and stability from conventional nanocatalysts.The electronic properties and catalytic performances of SACs hinge on the results of orbital hybridization of isolated central atoms with ligand atoms as well as of central atoms with bonding atoms provided by intermediates.Therefore,we conduct multifaceted explorations around orbital hybridizations in single-atom catalysis to elucidate the structure-activity relationships.Firstly,we introduce the basic theoretical knowledge related to orbital hybridizations,and summarize the main descriptors of orbital hybridizations,focusing on the discussion of the types of orbital hybridizations in singleatom catalysis.Then,we briefly sum up the application of orbital hybridizations in single-atom electrocatalysis and put forward important strategies for regulating orbital hybridizations in SACs to improve the catalytic performances.Finally,we present a personal perspective on the future challenges and opportunities of orbital hybridizations in single-atom catalysis.
基金the financial supports from National Key R&D Program for Young Scientists of China(Grant No.2022YFC3080900)National Natural Science Foundation of China(Grant No.52374181)+1 种基金BIT Research and Innovation Promoting Project(Grant No.2024YCXZ017)supported by Science and Technology Innovation Program of Beijing institute of technology under Grant No.2022CX01025。
文摘In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honeycomb cells,was created by constructing arrangement matrices to achieve structural lightweight.The machine learning(ML)framework consisted of a neural network(NN)forward regression model for predicting impact resistance and a multi-objective optimization algorithm for generating high-performance designs.The surrogate of the local design space was initially realized by establishing the NN in the small sample dataset,and the active learning strategy was used to continuously extended the local optimal design until the model converged in the global space.The results indicated that the active learning strategy significantly improved the inference capability of the NN model in unknown design domains.By guiding the iteration direction of the optimization algorithm,lightweight designs with high impact resistance were identified.The energy absorption capacity of the optimal design reached 94.98%of the EARE honeycomb,while the initial peak stress and mass decreased by 28.85%and 19.91%,respectively.Furthermore,Shapley Additive Explanations(SHAP)for global explanation of the NN indicated a strong correlation between the arrangement mode of HCS and its impact resistance.By reducing the stiffness of the cells at the top boundary of the structure,the initial impact damage sustained by the structure can be significantly improved.Overall,this study proposed a general lightweight design method for array structures under impact loads,which is beneficial for the widespread application of honeycomb-based protective structures.
文摘Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships.Networking structures are highly sensitive in social networks,requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks.In addition,they miss out on accurately identifying clusters.Since single-objective optimization cannot always generate accurate and comprehensive results,as multi-objective optimization can.Therefore,we utilized two objective functions that enable strong connections between communities and weak connections between them.In this study,we utilized the intra function,which has proven effective in state-of-the-art research studies.We proposed a new inter-function that has demonstrated its effectiveness by making the objective of detecting external connections between communities is to make them more distinct and sparse.Furthermore,we proposed a Multi-Objective community strength enhancement algorithm(MOCSE).The proposed algorithm is based on the framework of the Multi-Objective Evolutionary Algorithm with Decomposition(MOEA/D),integrated with a new heuristic mutation strategy,community strength enhancement(CSE).The results demonstrate that the model is effective in accurately identifying community structures while also being computationally efficient.The performance measures used to evaluate the MOEA/D algorithm in our work are normalized mutual information(NMI)and modularity(Q).It was tested using five state-of-the-art algorithms on social networks,comprising real datasets(Zachary,Dolphin,Football,Krebs,SFI,Jazz,and Netscience),as well as twenty synthetic datasets.These results provide the robustness and practical value of the proposed algorithm in multi-objective community identification.
基金the National Natural Science Foundation of China(No.22379069)Fundamental Research Funds for the Central Universities(No.30922010304).
文摘Sluggish sulfur redox kinetics remain a critical bottleneck in the advancement of high-performance lithiumsulfur batteries(LSBs).Single-atom catalysts(SACs)offer a promising solution to this limitation,particularly when their coordination structures are carefully engineered.Here,we develop a chromium-based SAC featuring a unique undercoordinated CrN_(3) configuration to boost sulfur electrochemistry.Compared with conventional CrN_(4),the CrN_(3) motif lowers 3d orbital occupancy and meanwhile activates the in-plane hybridizations with S 3p orbitals upon interaction with polysulfides,contributing to moderate adsorption strength and reduced energy barriers for bidirectional sulfur conversions.Additionally,the integration of the two-dimensional(2D)porous framework ensures abundant electrochemically active surfaces and efficiently exposed active sites.As a result,CrN_(3)-based cells demonstrate fast and durable sulfur redox reactions,enabling an ultralow capacity decay of 0.0075%per cycle over 1000 cycles and a high-rate capability of 651.9 mAh·g^(-1)at 5 C.The CrN_(3) catalyst retains robust catalytic efficiency under demanding conditions,delivering a high areal capacity of 5.53 mAh·cm^(-2) at high sulfur loading and lean electrolyte.This work establishes a compelling paradigm of SAC coordination engineering for designing advanced sulfur electrocatalysts for next-generation LSBs.
基金financially supported by the National Natural Science Foundation of China(No.82204317)the Liaoning Revitalization Talents Program(No.XLYC2403107)+1 种基金the Excellent Youth Science Foundation of Liaoning Province(No.2024JH3/10200046)the Basic Scientific Research Project of Liaoning Provincial Department of Education(No.LJ212410163015).
文摘Oxaliplatin(OXA)has shown excellent potential in inducing immunogenic cell death and enhancing immunotherapy.However,the poor physicochemical properties of oxaliplatin make it difficult to achieve efficient synchronous delivery and synergistic immunotherapy with immune checkpoint inhibitors.To address this,we designed structurally optimized dual-wing butterfly prodrugs:oxaliplatin prodrug(POP)that enhances immunogenicity and reducible NLG919 homodimer(NSSN)that mitigates immunosuppression.Structural optimization of dual-wing butterfly prodrugs significantly enhanced lipid solubility compared to the parent drugs.It is worth noting that we assembled two dual-wing butterfly prodrugs,POP and NSSN,together into hybrid nanoassemblies(NAs),achieving advantages such as stable assembly,flexible dosing,and collaborative therapy.Dual-wing butterfly prodrug-driven hybrid NAs demonstrated enhanced antitumor efficacy and metastasis control in experimental models,with biocompatibility confirmed through biosafety evaluations.This work proposes a co-delivery strategy based on dual-wing butterfly prodrugs as a clinically translatable candidate.
基金funded by the Institute of Smart Energy,Huaiyin Institute of Technology,under Grant No.HIT-ISE-2024-07.
文摘In order to address environmental pollution and resource depletion caused by traditional power generation,this paper proposes an adaptive iterative dynamic-balance optimization algorithm that integrates the Improved Dung Beetle Optimizer(IDBO)with VariationalMode Decomposition(VMD).The IDBO-VMD method is designed to enhance the accuracy and efficiency of wind-speed time-series decomposition and to effectively smooth photovoltaic power fluctuations.This study innovatively improves the traditional variational mode decomposition(VMD)algorithm,and significantly improves the accuracy and adaptive ability of signal decomposition by IDBO selfoptimization of key parameters K and a.On this basis,Fourier transform technology is used to define the boundary point between high frequency and low frequency signals,and a targeted energy distribution strategy is proposed:high frequency fluctuations are allocated to supercapacitors to quickly respond to transient power fluctuations;Lowfrequency components are distributed to lead-carbon batteries,optimizing long-term energy storage and scheduling efficiency.This strategy effectively improves the response speed and stability of the energy storage system.The experimental results demonstrate that the IDBO-VMD algorithm markedly outperforms traditional methods in both decomposition accuracy and computational efficiency.Specifically,it effectively reduces the charge–discharge frequency of the battery,prolongs battery life,and optimizes the operating ranges of the state-of-charge(SOC)for both leadcarbon batteries and supercapacitors.In addition,the energy management strategy based on the algorithm not only improves the overall energy utilization efficiency of the system,but also shows excellent performance in the dynamic management and intelligent scheduling of renewable energy generation.
基金financially supported by the National Natural Science Foundation of China(Nos.22272118,22172111,and 22309134)the Science and Technology Commission of Shanghai Municipality,China(Nos.22ZR1464100,20ZR1460300,and 19DZ2271500)+2 种基金the China Postdoctoral Science Foundation(2022M712402),the Shanghai Rising-Star Program(23YF1449200)the Zhejiang Provincial Science and Technology Project(2022C01182)the Fundamental Research Funds for the Central Universities(2023-3-YB-07)。
文摘Carbon superstructures with multiscale hierarchies and functional attributes represent an appealing cathode candidate for zinc hybrid capacitors,but their tailor-made design to optimize the capacitive activity remains a confusing topic.Here we develop a hydrogen-bond-oriented interfacial super-assembly strategy to custom-tailor nanosheet-intertwined spherical carbon superstructures(SCSs)for Zn-ion storage with double-high capacitive activity and durability.Tetrachlorobenzoquinone(H-bond acceptor)and dimethylbenzidine(H-bond donator)can interact to form organic nanosheet modules,which are sequentially assembled,orientally compacted and densified into well-orchestrated superstructures through multiple H-bonds(N-H···O).Featured with rich surface-active heterodiatomic motifs,more exposed nanoporous channels,and successive charge migration paths,SCSs cathode promises high accessibility of built-in zincophilic sites and rapid ion diffusion with low energy barriers(3.3Ωs-0.5).Consequently,the assembled Zn||SCSs capacitor harvests all-round improvement in Zn-ion storage metrics,including high energy density(166 Wh kg-1),high-rate performance(172 m Ah g^(-1)at 20 A g^(-1)),and long-lasting cycling lifespan(95.5%capacity retention after 500,000 cycles).An opposite chargecarrier storage mechanism is rationalized for SCSs cathode to maximize spatial capacitive charge storage,involving high-kinetics physical Zn^(2+)/CF_(3)SO_(3)-adsorption and chemical Zn^(2+)redox with carbonyl/pyridine groups.This work gives insights into H-bond-guided interfacial superassembly design of superstructural carbons toward advanced energy storage.
文摘This systematic review aims to comprehensively examine and compare deep learning methods for brain tumor segmentation and classification using MRI and other imaging modalities,focusing on recent trends from 2022 to 2025.The primary objective is to evaluate methodological advancements,model performance,dataset usage,and existing challenges in developing clinically robust AI systems.We included peer-reviewed journal articles and highimpact conference papers published between 2022 and 2025,written in English,that proposed or evaluated deep learning methods for brain tumor segmentation and/or classification.Excluded were non-open-access publications,books,and non-English articles.A structured search was conducted across Scopus,Google Scholar,Wiley,and Taylor&Francis,with the last search performed in August 2025.Risk of bias was not formally quantified but considered during full-text screening based on dataset diversity,validation methods,and availability of performance metrics.We used narrative synthesis and tabular benchmarking to compare performance metrics(e.g.,accuracy,Dice score)across model types(CNN,Transformer,Hybrid),imaging modalities,and datasets.A total of 49 studies were included(43 journal articles and 6 conference papers).These studies spanned over 9 public datasets(e.g.,BraTS,Figshare,REMBRANDT,MOLAB)and utilized a range of imaging modalities,predominantly MRI.Hybrid models,especially ResViT and UNetFormer,consistently achieved high performance,with classification accuracy exceeding 98%and segmentation Dice scores above 0.90 across multiple studies.Transformers and hybrid architectures showed increasing adoption post2023.Many studies lacked external validation and were evaluated only on a few benchmark datasets,raising concerns about generalizability and dataset bias.Few studies addressed clinical interpretability or uncertainty quantification.Despite promising results,particularly for hybrid deep learning models,widespread clinical adoption remains limited due to lack of validation,interpretability concerns,and real-world deployment barriers.
基金supported by Natural Science Foundation of Hu'nan Province(2024JJ5409)。
文摘In underwater target search path planning,the accuracy of sonar models directly dictates the accurate assessment of search coverage.In contrast to physics-informed sonar models,traditional geometric sonar models fail to accurately characterize the complex influence of marine environments.To overcome these challenges,we propose an acoustic physics-informed intelligent path planning framework for underwater target search,integrating three core modules:The acoustic-physical modeling module adopts 3D ray-tracing theory and the active sonar equation to construct a physics-driven sonar detection model,explicitly accounting for environmental factors that influence sonar performance across heterogeneous spaces.The hybrid parallel computing module adopts a message passing interface(MPI)/open multi-processing(Open MP)hybrid strategy for large-scale acoustic simulations,combining computational domain decomposition and physics-intensive task acceleration.The search path optimization module adopts the covariance matrix adaptation evolution algorithm to solve continuous optimization problems of heading angles,which ensures maximum search coverage for targets.Largescale experiments conducted in the Pacific and Atlantic Oceans demonstrate the framework's effectiveness:(1)Precise capture of sonar detection range variations from 5.45 km to 50 km in heterogeneous marine environments.(2)Significant speedup of 453.43×for acoustic physics modeling through hybrid parallelization.(3)Notable improvements of 7.23%in detection coverage and 15.86%reduction in optimization time compared to the optimal baseline method.The framework provides a robust solution for underwater search missions in complex marine environments.
文摘Multi-label feature selection(MFS)is a crucial dimensionality reduction technique aimed at identifying informative features associated with multiple labels.However,traditional centralized methods face significant challenges in privacy-sensitive and distributed settings,often neglecting label dependencies and suffering from low computational efficiency.To address these issues,we introduce a novel framework,Fed-MFSDHBCPSO—federated MFS via dual-layer hybrid breeding cooperative particle swarm optimization algorithm with manifold and sparsity regularization(DHBCPSO-MSR).Leveraging the federated learning paradigm,Fed-MFSDHBCPSO allows clients to perform local feature selection(FS)using DHBCPSO-MSR.Locally selected feature subsets are encrypted with differential privacy(DP)and transmitted to a central server,where they are securely aggregated and refined through secure multi-party computation(SMPC)until global convergence is achieved.Within each client,DHBCPSO-MSR employs a dual-layer FS strategy.The inner layer constructs sample and label similarity graphs,generates Laplacian matrices to capture the manifold structure between samples and labels,and applies L2,1-norm regularization to sparsify the feature subset,yielding an optimized feature weight matrix.The outer layer uses a hybrid breeding cooperative particle swarm optimization algorithm to further refine the feature weight matrix and identify the optimal feature subset.The updated weight matrix is then fed back to the inner layer for further optimization.Comprehensive experiments on multiple real-world multi-label datasets demonstrate that Fed-MFSDHBCPSO consistently outperforms both centralized and federated baseline methods across several key evaluation metrics.
基金financially supported by the National Natural Science Foundation of China(U21A20311,U24A2040,52171141,52272117)the Natural Science Foundation of Shandong Province(ZR2022JQ19)+3 种基金the Key Technology Research Project of Shandong Province(2023CXGC010202)the Taishan Industrial Experts Program(TSCX202306142)the Core Facility Sharing Platform of Shandong Universitythe Foundation of Key Laboratory of Advanced Energy Materials Chemistry(Ministry of Education),Nankai University。
文摘Co_(3)S_(4)electrocatalysts with mixed valences of Co ions and excellent structural stability possess favorable oxygen evolution reaction(OER)activity,yet challenges remain in fabricating rechargeable lithiumoxygen batteries(LOBs)due to their poor OER performance,resulting from poor electrical conductivity and overly strong intermediate adsorption.In this work,fancy double heterojunctions on 1T/2H-MoS_(2)@Co_(3)S_(4)(1T/2H-MCS)were constructed derived from the charge donation from Co to Mo ions,thus inducing the phase transformation of Mo S_(2)from 2H to 1T.The unique features of these double heterojunctions endow the1T/2H-MCS with complementary catalysis during charging and discharging processes.It is worth noting that 1T-Mo S2@Co3S4could provide fast Co-S-Mo electron transport channels to promote ORR/OER kinetics,and 2H-MoS_(2)@Co_(3)S_(4)contributed to enabling moderate egorbital occupancy when adsorbed with oxygen-containing intermediates.On the basis,the Li_(2)O_(2)nucleation route was changed to solution and surface dual pathways,improving reversible deposition and decomposition kinetics.As a result,1T/2H-MCS cathodes exhibit an improved electrocatalytic performance compared with those of Co_(3)S_(4)and Mo S2cathodes.This innovative heterostructure design provides a reliable strategy to construct efficient transition metal sulfide catalysts by improving electrical conductivity and modulating adsorption toward oxygenated intermediates for LOBs.
基金financially supported by the National Key R&D Program of China(No.2024YFF0506300)National Natural Science Foundation of China(No.52336009)+5 种基金Key Research and Development Program of Shaanxi(No.2024CY2-GJHX-66)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515010429)Natural Science Basic Research Plan in Shaanxi Province of China(No.2024JC-YBQN-0475)Xidian University Specially Funded Project for Interdisciplinary Exploration(No.TZJH2024063)the Fundamental Research Funds for the Central Universities(No.QTZX23061)the Innovation Center of Nuclear Power Technology(No.HDLCXZX-2022-ZH-013).
文摘Protonic ceramic fuel cells(PCFCs)have been recognized as promising power generation devices for future clean energy systems,owing to their relatively low activation energy for proton migration and high energy conversion efficiency.In certain application scenarios,the use of N_(2)O(a potent greenhouse gas),as an alternative oxidant to air,presents a feasible strategy.Herein,we report for the first time the operation of PCFCs employing N_(2)O as the oxidant.A hybrid Pr_(2)Ni_(0.6)Co_(0.4)O_(4-δ)(PNCO-214)catalyst is developed,comprising Ruddlesden-Popper(R-P)structured Pr_(4)Ni_(1.8)Co_(1.2)O_(10-δ)(PNCO-4310)and fluorite structured Pr_(6)O_(11)(PO-611),which synergistically exhibits exceptional catalytic activity toward both N_(2)O decomposition and the oxygen reduction reaction,achieving a conversion over 92% and an area specific resistance of 1.301Ω·cm^(2) at 600℃.Quasi-insitu temperature-dependent Fourier transform infrared(FTIR)and electrochemical impedance spectroscopy analyses reveal that abundant oxygen vacancies in PNCO-214 facilitate rapid adsorption and dissociation of N_(2)O into N_(2) and O_(2),while also promoting the surface exchange kinetics of proton/oxygen during oxygen reduction reaction(ORR).When applied in an anode-supported single cell with PNCO-214 cathode operating under N_(2)O,outstanding power density and low resistance are achieved,delivering 0.801 W·cm^(-2) and 0.245Ω·cm^(2) at 600℃.Satisfactory performance is also maintained even when the temperature is reduced to 500℃.Furthermore,the single cell demonstrates relatively good stability with negligible degradation over 130 h at 600℃ and 0.7 V.These findings underscore the potential of PNCO-214 as a highly effective cathode catalyst for enabling the use of N_(2)O as a viable oxidant in PCFCs for specific industrial applications.
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences (Grant Nos.XDB28000000 and XDB0460000)the Quantum Science and Technology-National Science and Technology Major Project (Grant No.2021ZD0302600)the National Key Research and Development Program of China(Grant No.2024YFA1409002)。
文摘The hybridization gap in strained-layer InAs/In_(x)Ga_(1−x) Sb quantum spin Hall insulators(QSHIs)is significantly enhanced compared to binary InAs/GaSb QSHI structures,where the typical indium composition,x,ranges between 0.2 and 0.4.This enhancement prompts a critical question:to what extent can quantum wells(QWs)be strained while still preserving the fundamental QSHI phase?In this study,we demonstrate the controlled molecular beam epitaxial growth of highly strained-layer QWs with an indium composition of x=0.5.These structures possess a substantial compressive strain within the In_(0.5)Ga_(0.5)Sb QW.Detailed crystal structure analyses confirm the exceptional quality of the resulting epitaxial films,indicating coherent lattice structures and the absence of visible dislocations.Transport measurements further reveal that the QSHI phase in InAs/In_(0.5)Ga_(0.5)Sb QWs is robust and protected by time-reversal symmetry.Notably,the edge states in these systems exhibit giant magnetoresistance when subjected to a modest perpendicular magnetic field.This behavior is in agreement with the𝑍2 topological property predicted by the Bernevig–Hughes–Zhang model,confirming the preservation of topologically protected edge transport in the presence of enhanced bulk strain.
基金supported by Science and Technology Project of the headquarters of the State Grid Corporation of China(No.5500-202324492A-3-2-ZN).
文摘To enhance power flow regulation in scenarios involving large-scale renewable energy transmission via high-voltage direct current(HVDC)links and multi-infeed DC systems in load-center regions,this paper proposes a hybrid modular multilevel converter–capacitor-commutated line-commutated converter(MMC-CLCC)HVDC transmission system and its corresponding control strategy.First,the system topology is constructed,and a submodule configuration method for the MMC—combining full-bridge submodules(FBSMs)and half-bridge submodules(HBSMs)—is proposed to enable direct power flow reversal.Second,a hierarchical control strategy is introduced,includingMMCvoltage control,CLCC current control,and a coordinationmechanism,along with the derivation of the hybrid system’s power flow reversal characteristics.Third,leveraging the CLCC’s fast current regulation and theMMC’s negative voltage control capability,a coordinated power flow reversal control strategy is developed.Finally,an 800 kV MMC-CLCC hybrid HVDC system is modeled in PSCAD/EMTDC to validate the power flow reversal performance under a high proportion of full-bridge submodule configuration.Results demonstrate that the proposed control strategy enables rapid(1-s transition)and smooth switching of bidirectional power flow without modifying the structure of primary equipment:the transient fluctuation ofDC voltage from the rated value(UdcN)to themaximumreverse voltage(-kUdcN)is less than 5%;the DC current strictly follows the preset characteristic curve with a deviation of≤3%;the active power reverses continuously,and the system maintains stable operation throughout the reversal process.
