The suprachiasmatic nucleus in the hypothalamus is the master circadian clock in mammals,coordinating physiological processes with the 24-hour day–night cycle.Comprising various cell types,the suprachiasmatic nucleus...The suprachiasmatic nucleus in the hypothalamus is the master circadian clock in mammals,coordinating physiological processes with the 24-hour day–night cycle.Comprising various cell types,the suprachiasmatic nucleus(SCN)integrates environmental signals to maintain complex and robust circadian rhythms.Understanding the complexity and synchrony within SCN neurons is essential for effective circadian clock function.Synchrony involves coordinated neuronal firing for robust rhythms,while complexity reflects diverse activity patterns and interactions,indicating adaptability.Interestingly,the SCN retains circadian rhythms in vitro,demonstrating intrinsic rhythmicity.This study introduces the multiscale structural complexity method to analyze changes in SCN neuronal activity and complexity at macro and micro levels,based on Bagrov et al.’s approach.By examining structural complexity and local complexities across scales,we aim to understand how tetrodotoxin,a neurotoxin that inhibits action potentials,affects SCN neurons.Our method captures critical scales in neuronal interactions that traditional methods may overlook.Validation with the Goodwin model confirms the reliability of our observations.By integrating experimental data with theoretical models,this study provides new insights into the effects of tetrodotoxin(TTX)on neuronal complexities,contributing to the understanding of circadian rhythms.展开更多
Using complex network methods,we construct undirected and directed heatwave networks to systematically analyze heatwave events over China from 1961 to 2023,exploring their spatiotemporal evolution patterns in differen...Using complex network methods,we construct undirected and directed heatwave networks to systematically analyze heatwave events over China from 1961 to 2023,exploring their spatiotemporal evolution patterns in different regions.The findings reveal a significant increase in heatwaves since the 2000s,with the average occurrence rising from approximately 3 to 5 times,and their duration increasing from 15 to around 30 days,nearly doubling.An increasing trend of“early onset and late withdrawal”of heatwaves has become more pronounced each year.In particular,eastern regions experience heatwaves that typically start earlier and tend to persist into September,exhibiting greater interannual variability compared to western areas.The middle and lower reaches of the Yangtze River and Xinjiang are identified as high-frequency heatwave areas.Complex network analysis reveals the dynamics of heatwave propagation,with degree centrality and synchronization distance indicating that the middle and lower reaches of the Yangtze River,Northeast China,and Xinjiang are key nodes in heatwave spread.Additionally,network divergence analysis shows that Xinjiang acts as a“source”area for heatwaves,exporting heat to surrounding regions,while the central region functions as a major“sink,”receiving more heatwave events.Further analysis from 1994 to 2023 indicates that heatwave events exhibit stronger network centrality and more complex synchronization patterns.These results suggest that complex networks provide a refined framework for depicting the spatiotemporal dynamics of heatwave propagation,offering new avenues for studying their occurrence and development patterns.展开更多
Transition metal-based nanomaterials have emerged as promising electrocatalysts for oxygen evolution reaction(OER).Considerable research efforts have shown that self-reconstruction occurs on these nanomaterials under ...Transition metal-based nanomaterials have emerged as promising electrocatalysts for oxygen evolution reaction(OER).Considerable research efforts have shown that self-reconstruction occurs on these nanomaterials under operating conditions of OER process.However,most of them undergo incomplete reconstruction with limited thickness of reconstruction layer,leading to low component utilization and arduous exploration of real catalytic mechanism.Herein,we identify the dynamic behaviors in complete reconstruction of Co-based complexes during OER.The hollow phytic acid(PA)cross-linked CoFe-based complex nanoboxes with porous nanowalls are designed because of their good electrolyte penetration and mass transport ability,in favor of the fast and complete reconstruction.A series of experiment characterizations demonstrate that the reconstruction process includes the fast substitution of PA by OH-to form Co(Fe)(OH)xand subsequent potential-driven oxidation to Co(Fe)OOH.The obtained CoFeOOH delivers a low overpotential of 290 mV at a current density of 10 mA cm^(-2)and a long-term stability.The experiment results together with theory calculations reveal that the Fe incorporation can result in the electron rearrangement of reconstructed CoFeOOH and optimization of their electronic structure,accounting for the enhanced OER activity.The work provides new insights into complete reconstruction of metal-based complexes during OER and offers guidelines for rational design of high-performance electrocatalysts.展开更多
For non-stationary complex dynamic systems,a standardized algorithm is developed to compute time correlation functions,addressing the limitations of traditional methods reliant on the stationary assumption.The propose...For non-stationary complex dynamic systems,a standardized algorithm is developed to compute time correlation functions,addressing the limitations of traditional methods reliant on the stationary assumption.The proposed algorithm integrates two-point and multi-point time correlation functions into a unified framework.Further,it is verified by a practical application in complex financial systems,demonstrating its potential in various complex dynamic systems.展开更多
Independent cascade(IC)models,by simulating how one node can activate another,are important tools for studying the dynamics of information spreading in complex networks.However,traditional algorithms for the IC model ...Independent cascade(IC)models,by simulating how one node can activate another,are important tools for studying the dynamics of information spreading in complex networks.However,traditional algorithms for the IC model implementation face significant efficiency bottlenecks when dealing with large-scale networks and multi-round simulations.To settle this problem,this study introduces a GPU-based parallel independent cascade(GPIC)algorithm,featuring an optimized representation of the network data structure and parallel task scheduling strategies.Specifically,for this GPIC algorithm,we propose a network data structure tailored for GPU processing,thereby enhancing the computational efficiency and the scalability of the IC model.In addition,we design a parallel framework that utilizes the full potential of GPU's parallel processing capabilities,thereby augmenting the computational efficiency.The results from our simulation experiments demonstrate that GPIC not only preserves accuracy but also significantly boosts efficiency,achieving a speedup factor of 129 when compared to the baseline IC method.Our experiments also reveal that when using GPIC for the independent cascade simulation,100-200 simulation rounds are sufficient for higher-cost studies,while high precision studies benefit from 500 rounds to ensure reliable results,providing empirical guidance for applying this new algorithm to practical research.展开更多
This paper study the finite time internal synchronization and the external synchronization(hybrid synchronization)for duplex heterogeneous complex networks by time-varying intermittent control.There few study hybrid s...This paper study the finite time internal synchronization and the external synchronization(hybrid synchronization)for duplex heterogeneous complex networks by time-varying intermittent control.There few study hybrid synchronization of heterogeneous duplex complex networks.Therefore,we study the finite time hybrid synchronization of heterogeneous duplex networks,which employs the time-varying intermittent control to drive the duplex heterogeneous complex networks to achieve hybrid synchronization in finite time.To be specific,the switch frequency of the controllers can be changed with time by devise Lyapunov function and boundary function,the internal synchronization and external synchronization are achieved simultaneously in finite time.Finally,numerical examples are presented to illustrate the validness of theoretical results.展开更多
Viral infectious diseases,characterized by their intricate nature and wide-ranging diversity,pose substantial challenges in the domain of data management.The vast volume of data generated by these diseases,spanning fr...Viral infectious diseases,characterized by their intricate nature and wide-ranging diversity,pose substantial challenges in the domain of data management.The vast volume of data generated by these diseases,spanning from the molecular mechanisms within cells to large-scale epidemiological patterns,has surpassed the capabilities of traditional analytical methods.In the era of artificial intelligence(AI)and big data,there is an urgent necessity for the optimization of these analytical methods to more effectively handle and utilize the information.Despite the rapid accumulation of data associated with viral infections,the lack of a comprehensive framework for integrating,selecting,and analyzing these datasets has left numerous researchers uncertain about which data to select,how to access it,and how to utilize it most effectively in their research.This review endeavors to fill these gaps by exploring the multifaceted nature of viral infectious diseases and summarizing relevant data across multiple levels,from the molecular details of pathogens to broad epidemiological trends.The scope extends from the micro-scale to the macro-scale,encompassing pathogens,hosts,and vectors.In addition to data summarization,this review thoroughly investigates various dataset sources.It also traces the historical evolution of data collection in the field of viral infectious diseases,highlighting the progress achieved over time.Simultaneously,it evaluates the current limitations that impede data utilization.Furthermore,we propose strategies to surmount these challenges,focusing on the development and application of advanced computational techniques,AI-driven models,and enhanced data integration practices.By providing a comprehensive synthesis of existing knowledge,this review is designed to guide future research and contribute to more informed approaches in the surveillance,prevention,and control of viral infectious diseases,particularly within the context of the expanding big-data landscape.展开更多
The title complex, [ [ Co （Py） 2 （H20） 2 （ NO3 ）2 ] ] n （ 1 ） was synthesized by liquid/liquid diffusion method at room temperature. The complex crystallizes in monoclinic, space group P2 （1）/C, with a = 0.8...The title complex, [ [ Co （Py） 2 （H20） 2 （ NO3 ）2 ] ] n （ 1 ） was synthesized by liquid/liquid diffusion method at room temperature. The complex crystallizes in monoclinic, space group P2 （1）/C, with a = 0.8775（6）nm, b=1.171 5（8）nm, c=0.7518（5）nm, V=0.739 3（9）nm3, C10H14CoN4O8, Mr= 377.18, Dc=1.694g/cm^3, μ=1.210mm^-1, F（000）=386, Z=2, the final R=0.0229 and wR= 0.066 1 for 3 137 observed reflections （I〉2σ（I））. In the structure of 1, the center atom of cobalt revealed a centrosymmetric, six-coordinate structure, with two Py ligands, two monodentate nitrate groups and two water molecules. It is notable that a series of hydrogen bonds （O-H…O） formed two kinds of rings exist in the structure, which linked neighboring six-coordinate polymer into a two-dimensional H-bonding network, and then assembled into a three-dimensional supramolecular architecture through electrostatic and hydrophobic interaction. In the structure, supramolecular sheet was observed, which contains alte .rnative organic and inorganic layers.展开更多
Sustainable agriculture plays a crucial role in meeting the growing global demand for food while minimizing adverse environmental impacts from the overuse of synthetic pesticides and conventional fertilizers.In this c...Sustainable agriculture plays a crucial role in meeting the growing global demand for food while minimizing adverse environmental impacts from the overuse of synthetic pesticides and conventional fertilizers.In this context,renewable biopolymers being more sustainable offer a viable solution to improve agricultural sustainability and production.Nano/micro-structural supramolecular biopolymers are among these innovative biopolymers that are much sought after for their unique features.These biomaterials have complex hierarchical structures,great stability,adjustable mechanical strength,stimuli-responsiveness,and self-healing attributes.Functional molecules may be added to their flexible structure,for enabling novel agricultural uses.This overview scrutinizes how nano/micro-structural supramolecular biopolymers may radically alter farming practices and solve lingering problems in agricultural sector namely improve agricultural production,soil health,and resource efficiency.Controlled bioactive ingredient released from biopolymers allows the tailored administration of agrochemicals,bioactive agents,and biostimulators as they enhance nutrient absorption,moisture retention,and root growth.Nano/micro-structural supramolecular biopolymers may protect crops by appending antimicrobials and biosensing entities while their eco-friendliness supports sustainable agriculture.Despite their potential,further studies are warranted to understand and optimize their usage in agricultural domain.This effort seeks to bridge the knowledge gap by investigating their applications,challenges,and future prospects in the agricultural sector.Through experimental investigations and theoretical modeling,this overview aims to provide valuable insights into the practical implementation and optimization of supramolecular biopolymers in sustainable agriculture,ultimately contributing to the development of innovative and eco-friendly solutions to enhance agricultural productivity while minimizing environmental impact.展开更多
A new pore type,nano-scale organo-clay complex pore-fracture was first discovered based on argon ion polishing-field emission scanning electron microscopy,energy dispersive spectroscopy and three-dimensional reconstru...A new pore type,nano-scale organo-clay complex pore-fracture was first discovered based on argon ion polishing-field emission scanning electron microscopy,energy dispersive spectroscopy and three-dimensional reconstruction by focused ion-scanning electron in combination with analysis of TOC,R_(o)values,X-ray diffraction etc.in the Cretaceous Qingshankou Formation shale in the Songliao Basin,NE China.Such pore characteristics and evolution study show that:(1)Organo-clay complex pore-fractures are developed in the shale matrix and in the form of spongy and reticular aggregates.Different from circular or oval organic pores discovered in other shales,a single organo-clay complex pore is square,rectangular,rhombic or slaty,with the pore diameter generally less than 200 nm.(2)With thermal maturity increasing,the elements(C,Si,Al,O,Mg,Fe,etc.)in organo-clay complex change accordingly,showing that organic matter shrinkage due to hydrocarbon generation and clay mineral transformation both affect organo-clay complex pore-fracture formation.(3)At high thermal maturity,the Qingshankou Formation shale is dominated by nano-scale organo-clay complex pore-fractures with the percentage reaching more than 70%of total pore space.The spatial connectivity of organo-clay complex pore-fractures is significantly better than that of organic pores.It is suggested that organo-complex pore-fractures are the main pore space of laminar shale at high thermal maturity and are the main oil and gas accumulation space in the core area of continental shale oil.The discovery of nano-scale organo-clay complex pore-fractures changes the conventional view that inorganic pores are the main reservoir space and has scientific significance for the study of shale oil formation and accumulation laws.展开更多
Camouflaged people are extremely expert in actively concealing themselves by effectively utilizing cover and the surrounding environment. Despite advancements in optical detection capabilities through imaging systems,...Camouflaged people are extremely expert in actively concealing themselves by effectively utilizing cover and the surrounding environment. Despite advancements in optical detection capabilities through imaging systems, including spectral, polarization, and infrared technologies, there is still a lack of effective real-time method for accurately detecting small-size and high-efficient camouflaged people in complex real-world scenes. Here, this study proposes a snapshot multispectral image-based camouflaged detection model, multispectral YOLO(MS-YOLO), which utilizes the SPD-Conv and Sim AM modules to effectively represent targets and suppress background interference by exploiting the spatial-spectral target information. Besides, the study constructs the first real-shot multispectral camouflaged people dataset(MSCPD), which encompasses diverse scenes, target scales, and attitudes. To minimize information redundancy, MS-YOLO selects an optimal subset of 12 bands with strong feature representation and minimal inter-band correlation as input. Through experiments on the MSCPD, MS-YOLO achieves a mean Average Precision of 94.31% and real-time detection at 65 frames per second, which confirms the effectiveness and efficiency of our method in detecting camouflaged people in various typical desert and forest scenes. Our approach offers valuable support to improve the perception capabilities of unmanned aerial vehicles in detecting enemy forces and rescuing personnel in battlefield.展开更多
In recent years,there has been a growing interest in graph convolutional networks(GCN).However,existing GCN and variants are predominantly based on simple graph or hypergraph structures,which restricts their ability t...In recent years,there has been a growing interest in graph convolutional networks(GCN).However,existing GCN and variants are predominantly based on simple graph or hypergraph structures,which restricts their ability to handle complex data correlations in practical applications.These limitations stem from the difficulty in establishing multiple hierarchies and acquiring adaptive weights for each of them.To address this issue,this paper introduces the latest concept of complex hypergraphs and constructs a versatile high-order multi-level data correlation model.This model is realized by establishing a three-tier structure of complexes-hypergraphs-vertices.Specifically,we start by establishing hyperedge clusters on a foundational network,utilizing a second-order hypergraph structure to depict potential correlations.For this second-order structure,truncation methods are used to assess and generate a three-layer composite structure.During the construction of the composite structure,an adaptive learning strategy is implemented to merge correlations across different levels.We evaluate this model on several popular datasets and compare it with recent state-of-the-art methods.The comprehensive assessment results demonstrate that the proposed model surpasses the existing methods,particularly in modeling implicit data correlations(the classification accuracy of nodes on five public datasets Cora,Citeseer,Pubmed,Github Web ML,and Facebook are 86.1±0.33,79.2±0.35,83.1±0.46,83.8±0.23,and 80.1±0.37,respectively).This indicates that our approach possesses advantages in handling datasets with implicit multi-level structures.展开更多
A gel based on polyacrylamide,exhibiting delayed crosslinking characteristics,emerges as the preferred solution for mitigating degradation under conditions of high temperature and extended shear in ultralong wellbores...A gel based on polyacrylamide,exhibiting delayed crosslinking characteristics,emerges as the preferred solution for mitigating degradation under conditions of high temperature and extended shear in ultralong wellbores.High viscosity/viscoelasticity of the fracturing fluid was required to maintain excellent proppant suspension properties before gelling.Taking into account both the cost and the potential damage to reservoirs,polymers with lower concentrations and molecular weights are generally preferred.In this work,the supramolecular action was integrated into the polymer,resulting in significant increases in the viscosity and viscoelasticity of the synthesized supramolecular polymer system.The double network gel,which is formed by the combination of the supramolecular polymer system and a small quantity of Zr-crosslinker,effectively resists temperature while minimizing permeability damage to the reservoir.The results indicate that the supramolecular polymer system with a molecular weight of(268—380)×10^(4)g/mol can achieve the same viscosity and viscoelasticity at 0.4 wt%due to the supramolecular interaction between polymers,compared to the 0.6 wt%traditional polymer(hydrolyzed polyacrylamide,molecular weight of 1078×10^(4)g/mol).The supramolecular polymer system possessed excellent proppant suspension properties with a 0.55 cm/min sedimentation rate at 0.4 wt%,whereas the0.6 wt%traditional polymer had a rate of 0.57 cm/min.In comparison to the traditional gel with a Zrcrosslinker concentration of 0.6 wt%and an elastic modulus of 7.77 Pa,the double network gel with a higher elastic modulus(9.00 Pa)could be formed only at 0.1 wt%Zr-crosslinker,which greatly reduced the amount of residue of the fluid after gel-breaking.The viscosity of the double network gel was66 m Pa s after 2 h shearing,whereas the traditional gel only reached 27 m Pa s.展开更多
Magnetic reconnection processes in three-dimensional(3D)complex field configurations have been investigated in different magneto-plasma systems in space,laboratory,and astrophysical systems.Two-dimensional(2D)features...Magnetic reconnection processes in three-dimensional(3D)complex field configurations have been investigated in different magneto-plasma systems in space,laboratory,and astrophysical systems.Two-dimensional(2D)features of magnetic reconnection have been well developed and applied successfully to systems with symmetrical property,such as toroidal fusion plasmas and laboratory experiments with an axial symmetry.But in asymmetric systems,the 3D features are inevitably different from those in the 2D case.Magnetic reconnection structures in multiple celestial body systems,particularly star-planet-Moon systems,bring fresh insights to the understanding of the 3D geometry of reconnection.Thus,we take magnetic reconnection in an ancient solar-lunar terrestrial magneto-plasma system as an example by using its crucial parameters approximately estimated already and also some specific applications in pathways for energy and matter transports among Earth,ancient Moon,and the interplanetary magnetic field(IMF).Then,magnetic reconnection of the ancient lunar-terrestrial magnetospheres with the IMF is investigated numerically in this work.In a 3D simulation for the Earth-Moon-IMF system,topological features of complex magnetic reconnection configurations and dynamical characteristics of magnetic reconnection processes are studied.It is found that a coupled lunar-terrestrial magnetosphere is formed,and under various IMF orientations,multiple X-points emerge at distinct locations,showing three typical magnetic reconnection structures in such a geometry,i.e.,the X-line,the triple current sheets,and the A-B null pairs.The results can conduce to further understanding of reconnection physics in 3D for plasmas in complex magnetic configurations,and also a possible mechanism for energy and matters transport in evolutions of similar astrophysical systems.展开更多
As the demand for high-quality services proliferates,an innovative network architecture,the fully-decoupled RAN(FD-RAN),has emerged for more flexible spectrum resource utilization and lower network costs.However,with ...As the demand for high-quality services proliferates,an innovative network architecture,the fully-decoupled RAN(FD-RAN),has emerged for more flexible spectrum resource utilization and lower network costs.However,with the decoupling of uplink base stations and downlink base stations in FDRAN,the traditional transmission mechanism,which relies on real-time channel feedback,is not suitable as the receiver is not able to feedback accurate and timely channel state information to the transmitter.This paper proposes a novel transmission scheme without relying on physical layer channel feedback.Specifically,we design a radio map based complex-valued precoding network(RMCPNet)model,which outputs the base station precoding based on user location.RMCPNet comprises multiple subnets,with each subnet responsible for extracting unique modal features from diverse input modalities.Furthermore,the multimodal embeddings derived from these distinct subnets are integrated within the information fusion layer,culminating in a unified representation.We also develop a specific RMCPNet training algorithm that employs the negative spectral efficiency as the loss function.We evaluate the performance of the proposed scheme on the public DeepMIMO dataset and show that RMCPNet can achieve 16%and 76%performance improvements over the conventional real-valued neural network and statistical codebook approach,respectively.展开更多
Tree interactions are essential for the structure,dynamics,and function of forest ecosystems,but variations in the architecture of life-stage interaction networks(LSINs)across forests is unclear.Here,we constructed 16...Tree interactions are essential for the structure,dynamics,and function of forest ecosystems,but variations in the architecture of life-stage interaction networks(LSINs)across forests is unclear.Here,we constructed 16 LSINs in the mountainous forests of northwest Hebei,China based on crown overlap from four mixed forests with two dominant tree species.Our results show that LSINs decrease the complexity of stand densities and basal areas due to the interaction cluster differentiation.In addition,we found that mature trees and saplings play different roles,the first acting as“hub”life stages with high connectivity and the second,as“bridges”controlling information flow with high centrality.Across the forests,life stages with higher importance showed better parameter stability within LSINs.These results reveal that the structure of tree interactions among life stages is highly related to stand variables.Our efforts contribute to the understanding of LSIN complexity and provide a basis for further research on tree interactions in complex forest communities.展开更多
Under investigation in this paper is a complex modified Korteweg–de Vries(KdV) equation, which describes the propagation of short pulses in optical fibers. Bilinear forms and multi-soliton solutions are obtained thro...Under investigation in this paper is a complex modified Korteweg–de Vries(KdV) equation, which describes the propagation of short pulses in optical fibers. Bilinear forms and multi-soliton solutions are obtained through the Hirota method and symbolic computation. Breather-like and bound-state solitons are constructed in which the signs of the imaginary parts of the complex wave numbers and the initial separations of the two parallel solitons are important factors for the interaction patterns. The periodic structures and position-induced phase shift of some solutions are introduced.展开更多
Complex plasma fluctuation processes have been extensively studied in many aspects,especially lattice waves in strongly coupled plasma crystals,which are of great significance for understanding fundamental physical ph...Complex plasma fluctuation processes have been extensively studied in many aspects,especially lattice waves in strongly coupled plasma crystals,which are of great significance for understanding fundamental physical phenomena.A challenge of experimental investigations in two-dimensional strongly coupled complex plasma crystals is to keep the main body and foreign particles of different masses on the same horizontal plane.To solve the problem,we have proposed a potential well formed by two negatively biased grids to bind the negatively charged particles in a two-dimensional(2D)plane,thus achieving a 2D plasma crystal in the microgravity environment.The study of such phenomena in complex plasma crystals under microgravity environment then becomes possible.In this paper,we focus on the continuum spectrum,including both phonon and optic branches of the impurity mode in a 2D system in microgravity environments.The results show the dispersion relation of the longitudinal and transverse impurity oscillation modes and their properties.Considering the macroscopic visibility of complex mesoscopic particle lattices,theoretical and experimental studies on this kind of complex plasma systems will help us further understand the physical nature of a wide range of condensed matters.展开更多
The dissemination of information across various locations is an ubiquitous occurrence,however,prevalent methodologies for multi-source identification frequently overlook the fact that sources may initiate disseminatio...The dissemination of information across various locations is an ubiquitous occurrence,however,prevalent methodologies for multi-source identification frequently overlook the fact that sources may initiate dissemination at distinct initial moments.Although there are many research results of multi-source identification,the challenge of locating sources with varying initiation times using a limited subset of observational nodes remains unresolved.In this study,we provide the backward spread tree theorem and source centrality theorem,and develop a backward spread centrality algorithm to identify all the information sources that trigger the spread at different start times.The proposed algorithm does not require prior knowledge of the number of sources,however,it can estimate both the initial spread moment and the spread duration.The core concept of this algorithm involves inferring suspected sources through source centrality theorem and locating the source from the suspected sources with linear programming.Extensive experiments from synthetic and real network simulation corroborate the superiority of our method in terms of both efficacy and efficiency.Furthermore,we find that our method maintains robustness irrespective of the number of sources and the average degree of network.Compared with classical and state-of-the art source identification methods,our method generally improves the AUROC value by 0.1 to 0.2.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12275179,11875042,and 12150410309)the Natural Science Foundation of Shanghai(Grant No.21ZR1443900).
文摘The suprachiasmatic nucleus in the hypothalamus is the master circadian clock in mammals,coordinating physiological processes with the 24-hour day–night cycle.Comprising various cell types,the suprachiasmatic nucleus(SCN)integrates environmental signals to maintain complex and robust circadian rhythms.Understanding the complexity and synchrony within SCN neurons is essential for effective circadian clock function.Synchrony involves coordinated neuronal firing for robust rhythms,while complexity reflects diverse activity patterns and interactions,indicating adaptability.Interestingly,the SCN retains circadian rhythms in vitro,demonstrating intrinsic rhythmicity.This study introduces the multiscale structural complexity method to analyze changes in SCN neuronal activity and complexity at macro and micro levels,based on Bagrov et al.’s approach.By examining structural complexity and local complexities across scales,we aim to understand how tetrodotoxin,a neurotoxin that inhibits action potentials,affects SCN neurons.Our method captures critical scales in neuronal interactions that traditional methods may overlook.Validation with the Goodwin model confirms the reliability of our observations.By integrating experimental data with theoretical models,this study provides new insights into the effects of tetrodotoxin(TTX)on neuronal complexities,contributing to the understanding of circadian rhythms.
基金Project supported by the National Key Research and Development Program of China(Grant Nos.2022YFE0136000 and 2024YFC3013100)the Joint Meteorological Fund(Grant No.U2342211)+1 种基金the Joint Research Project for Meteorological Capacity Improvement(Grant No.22NLTSZ004)the National Meteorological Information Center(Grant No.NMICJY202301)。
文摘Using complex network methods,we construct undirected and directed heatwave networks to systematically analyze heatwave events over China from 1961 to 2023,exploring their spatiotemporal evolution patterns in different regions.The findings reveal a significant increase in heatwaves since the 2000s,with the average occurrence rising from approximately 3 to 5 times,and their duration increasing from 15 to around 30 days,nearly doubling.An increasing trend of“early onset and late withdrawal”of heatwaves has become more pronounced each year.In particular,eastern regions experience heatwaves that typically start earlier and tend to persist into September,exhibiting greater interannual variability compared to western areas.The middle and lower reaches of the Yangtze River and Xinjiang are identified as high-frequency heatwave areas.Complex network analysis reveals the dynamics of heatwave propagation,with degree centrality and synchronization distance indicating that the middle and lower reaches of the Yangtze River,Northeast China,and Xinjiang are key nodes in heatwave spread.Additionally,network divergence analysis shows that Xinjiang acts as a“source”area for heatwaves,exporting heat to surrounding regions,while the central region functions as a major“sink,”receiving more heatwave events.Further analysis from 1994 to 2023 indicates that heatwave events exhibit stronger network centrality and more complex synchronization patterns.These results suggest that complex networks provide a refined framework for depicting the spatiotemporal dynamics of heatwave propagation,offering new avenues for studying their occurrence and development patterns.
基金National Natural Science Foundation of China(22478310,U21A20286 and 22206054)。
文摘Transition metal-based nanomaterials have emerged as promising electrocatalysts for oxygen evolution reaction(OER).Considerable research efforts have shown that self-reconstruction occurs on these nanomaterials under operating conditions of OER process.However,most of them undergo incomplete reconstruction with limited thickness of reconstruction layer,leading to low component utilization and arduous exploration of real catalytic mechanism.Herein,we identify the dynamic behaviors in complete reconstruction of Co-based complexes during OER.The hollow phytic acid(PA)cross-linked CoFe-based complex nanoboxes with porous nanowalls are designed because of their good electrolyte penetration and mass transport ability,in favor of the fast and complete reconstruction.A series of experiment characterizations demonstrate that the reconstruction process includes the fast substitution of PA by OH-to form Co(Fe)(OH)xand subsequent potential-driven oxidation to Co(Fe)OOH.The obtained CoFeOOH delivers a low overpotential of 290 mV at a current density of 10 mA cm^(-2)and a long-term stability.The experiment results together with theory calculations reveal that the Fe incorporation can result in the electron rearrangement of reconstructed CoFeOOH and optimization of their electronic structure,accounting for the enhanced OER activity.The work provides new insights into complete reconstruction of metal-based complexes during OER and offers guidelines for rational design of high-performance electrocatalysts.
基金Project supported by the Postdoctoral Fellowship Program of China Postdoctoral Science Foundation(Grant No.GZC20231050)the National Natural Science Foundation of China(Grant Nos.12175193 and 11905183)the 13th Five-year plan for Education Science Funding of Guangdong Province(Grant No.2021GXJK349)。
文摘For non-stationary complex dynamic systems,a standardized algorithm is developed to compute time correlation functions,addressing the limitations of traditional methods reliant on the stationary assumption.The proposed algorithm integrates two-point and multi-point time correlation functions into a unified framework.Further,it is verified by a practical application in complex financial systems,demonstrating its potential in various complex dynamic systems.
基金support from the National Natural Science Foundation of China(Grant No.T2293771)the STI 2030-Major Projects(Grant No.2022ZD0211400)the Sichuan Province Outstanding Young Scientists Foundation(Grant No.2023NSFSC1919)。
文摘Independent cascade(IC)models,by simulating how one node can activate another,are important tools for studying the dynamics of information spreading in complex networks.However,traditional algorithms for the IC model implementation face significant efficiency bottlenecks when dealing with large-scale networks and multi-round simulations.To settle this problem,this study introduces a GPU-based parallel independent cascade(GPIC)algorithm,featuring an optimized representation of the network data structure and parallel task scheduling strategies.Specifically,for this GPIC algorithm,we propose a network data structure tailored for GPU processing,thereby enhancing the computational efficiency and the scalability of the IC model.In addition,we design a parallel framework that utilizes the full potential of GPU's parallel processing capabilities,thereby augmenting the computational efficiency.The results from our simulation experiments demonstrate that GPIC not only preserves accuracy but also significantly boosts efficiency,achieving a speedup factor of 129 when compared to the baseline IC method.Our experiments also reveal that when using GPIC for the independent cascade simulation,100-200 simulation rounds are sufficient for higher-cost studies,while high precision studies benefit from 500 rounds to ensure reliable results,providing empirical guidance for applying this new algorithm to practical research.
基金Project supported by Jilin Provincial Science and Technology Development Plan(Grant No.20220101137JC).
文摘This paper study the finite time internal synchronization and the external synchronization(hybrid synchronization)for duplex heterogeneous complex networks by time-varying intermittent control.There few study hybrid synchronization of heterogeneous duplex complex networks.Therefore,we study the finite time hybrid synchronization of heterogeneous duplex networks,which employs the time-varying intermittent control to drive the duplex heterogeneous complex networks to achieve hybrid synchronization in finite time.To be specific,the switch frequency of the controllers can be changed with time by devise Lyapunov function and boundary function,the internal synchronization and external synchronization are achieved simultaneously in finite time.Finally,numerical examples are presented to illustrate the validness of theoretical results.
基金supported by the National Natural Science Foundation of China(32370703)the CAMS Innovation Fund for Medical Sciences(CIFMS)(2022-I2M-1-021,2021-I2M-1-061)the Major Project of Guangzhou National Labora-tory(GZNL2024A01015).
文摘Viral infectious diseases,characterized by their intricate nature and wide-ranging diversity,pose substantial challenges in the domain of data management.The vast volume of data generated by these diseases,spanning from the molecular mechanisms within cells to large-scale epidemiological patterns,has surpassed the capabilities of traditional analytical methods.In the era of artificial intelligence(AI)and big data,there is an urgent necessity for the optimization of these analytical methods to more effectively handle and utilize the information.Despite the rapid accumulation of data associated with viral infections,the lack of a comprehensive framework for integrating,selecting,and analyzing these datasets has left numerous researchers uncertain about which data to select,how to access it,and how to utilize it most effectively in their research.This review endeavors to fill these gaps by exploring the multifaceted nature of viral infectious diseases and summarizing relevant data across multiple levels,from the molecular details of pathogens to broad epidemiological trends.The scope extends from the micro-scale to the macro-scale,encompassing pathogens,hosts,and vectors.In addition to data summarization,this review thoroughly investigates various dataset sources.It also traces the historical evolution of data collection in the field of viral infectious diseases,highlighting the progress achieved over time.Simultaneously,it evaluates the current limitations that impede data utilization.Furthermore,we propose strategies to surmount these challenges,focusing on the development and application of advanced computational techniques,AI-driven models,and enhanced data integration practices.By providing a comprehensive synthesis of existing knowledge,this review is designed to guide future research and contribute to more informed approaches in the surveillance,prevention,and control of viral infectious diseases,particularly within the context of the expanding big-data landscape.
基金Sponsored by the National Natural Science Foundation of China(20571011,20771014)
文摘The title complex, [ [ Co （Py） 2 （H20） 2 （ NO3 ）2 ] ] n （ 1 ） was synthesized by liquid/liquid diffusion method at room temperature. The complex crystallizes in monoclinic, space group P2 （1）/C, with a = 0.8775（6）nm, b=1.171 5（8）nm, c=0.7518（5）nm, V=0.739 3（9）nm3, C10H14CoN4O8, Mr= 377.18, Dc=1.694g/cm^3, μ=1.210mm^-1, F（000）=386, Z=2, the final R=0.0229 and wR= 0.066 1 for 3 137 observed reflections （I〉2σ（I））. In the structure of 1, the center atom of cobalt revealed a centrosymmetric, six-coordinate structure, with two Py ligands, two monodentate nitrate groups and two water molecules. It is notable that a series of hydrogen bonds （O-H…O） formed two kinds of rings exist in the structure, which linked neighboring six-coordinate polymer into a two-dimensional H-bonding network, and then assembled into a three-dimensional supramolecular architecture through electrostatic and hydrophobic interaction. In the structure, supramolecular sheet was observed, which contains alte .rnative organic and inorganic layers.
基金support provided by the UKRI via Grant No.EP/T024607/1Royal Society via grant number IES\R2\222208.
文摘Sustainable agriculture plays a crucial role in meeting the growing global demand for food while minimizing adverse environmental impacts from the overuse of synthetic pesticides and conventional fertilizers.In this context,renewable biopolymers being more sustainable offer a viable solution to improve agricultural sustainability and production.Nano/micro-structural supramolecular biopolymers are among these innovative biopolymers that are much sought after for their unique features.These biomaterials have complex hierarchical structures,great stability,adjustable mechanical strength,stimuli-responsiveness,and self-healing attributes.Functional molecules may be added to their flexible structure,for enabling novel agricultural uses.This overview scrutinizes how nano/micro-structural supramolecular biopolymers may radically alter farming practices and solve lingering problems in agricultural sector namely improve agricultural production,soil health,and resource efficiency.Controlled bioactive ingredient released from biopolymers allows the tailored administration of agrochemicals,bioactive agents,and biostimulators as they enhance nutrient absorption,moisture retention,and root growth.Nano/micro-structural supramolecular biopolymers may protect crops by appending antimicrobials and biosensing entities while their eco-friendliness supports sustainable agriculture.Despite their potential,further studies are warranted to understand and optimize their usage in agricultural domain.This effort seeks to bridge the knowledge gap by investigating their applications,challenges,and future prospects in the agricultural sector.Through experimental investigations and theoretical modeling,this overview aims to provide valuable insights into the practical implementation and optimization of supramolecular biopolymers in sustainable agriculture,ultimately contributing to the development of innovative and eco-friendly solutions to enhance agricultural productivity while minimizing environmental impact.
基金Supported by Central Government Guided Local Science and Technology Innovation Fund Program(ZY20B13)。
文摘A new pore type,nano-scale organo-clay complex pore-fracture was first discovered based on argon ion polishing-field emission scanning electron microscopy,energy dispersive spectroscopy and three-dimensional reconstruction by focused ion-scanning electron in combination with analysis of TOC,R_(o)values,X-ray diffraction etc.in the Cretaceous Qingshankou Formation shale in the Songliao Basin,NE China.Such pore characteristics and evolution study show that:(1)Organo-clay complex pore-fractures are developed in the shale matrix and in the form of spongy and reticular aggregates.Different from circular or oval organic pores discovered in other shales,a single organo-clay complex pore is square,rectangular,rhombic or slaty,with the pore diameter generally less than 200 nm.(2)With thermal maturity increasing,the elements(C,Si,Al,O,Mg,Fe,etc.)in organo-clay complex change accordingly,showing that organic matter shrinkage due to hydrocarbon generation and clay mineral transformation both affect organo-clay complex pore-fracture formation.(3)At high thermal maturity,the Qingshankou Formation shale is dominated by nano-scale organo-clay complex pore-fractures with the percentage reaching more than 70%of total pore space.The spatial connectivity of organo-clay complex pore-fractures is significantly better than that of organic pores.It is suggested that organo-complex pore-fractures are the main pore space of laminar shale at high thermal maturity and are the main oil and gas accumulation space in the core area of continental shale oil.The discovery of nano-scale organo-clay complex pore-fractures changes the conventional view that inorganic pores are the main reservoir space and has scientific significance for the study of shale oil formation and accumulation laws.
基金support by the National Natural Science Foundation of China (Grant No. 62005049)Natural Science Foundation of Fujian Province (Grant Nos. 2020J01451, 2022J05113)Education and Scientific Research Program for Young and Middleaged Teachers in Fujian Province (Grant No. JAT210035)。
文摘Camouflaged people are extremely expert in actively concealing themselves by effectively utilizing cover and the surrounding environment. Despite advancements in optical detection capabilities through imaging systems, including spectral, polarization, and infrared technologies, there is still a lack of effective real-time method for accurately detecting small-size and high-efficient camouflaged people in complex real-world scenes. Here, this study proposes a snapshot multispectral image-based camouflaged detection model, multispectral YOLO(MS-YOLO), which utilizes the SPD-Conv and Sim AM modules to effectively represent targets and suppress background interference by exploiting the spatial-spectral target information. Besides, the study constructs the first real-shot multispectral camouflaged people dataset(MSCPD), which encompasses diverse scenes, target scales, and attitudes. To minimize information redundancy, MS-YOLO selects an optimal subset of 12 bands with strong feature representation and minimal inter-band correlation as input. Through experiments on the MSCPD, MS-YOLO achieves a mean Average Precision of 94.31% and real-time detection at 65 frames per second, which confirms the effectiveness and efficiency of our method in detecting camouflaged people in various typical desert and forest scenes. Our approach offers valuable support to improve the perception capabilities of unmanned aerial vehicles in detecting enemy forces and rescuing personnel in battlefield.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12275179 and 11875042)the Natural Science Foundation of Shanghai Municipality,China(Grant No.21ZR1443900)。
文摘In recent years,there has been a growing interest in graph convolutional networks(GCN).However,existing GCN and variants are predominantly based on simple graph or hypergraph structures,which restricts their ability to handle complex data correlations in practical applications.These limitations stem from the difficulty in establishing multiple hierarchies and acquiring adaptive weights for each of them.To address this issue,this paper introduces the latest concept of complex hypergraphs and constructs a versatile high-order multi-level data correlation model.This model is realized by establishing a three-tier structure of complexes-hypergraphs-vertices.Specifically,we start by establishing hyperedge clusters on a foundational network,utilizing a second-order hypergraph structure to depict potential correlations.For this second-order structure,truncation methods are used to assess and generate a three-layer composite structure.During the construction of the composite structure,an adaptive learning strategy is implemented to merge correlations across different levels.We evaluate this model on several popular datasets and compare it with recent state-of-the-art methods.The comprehensive assessment results demonstrate that the proposed model surpasses the existing methods,particularly in modeling implicit data correlations(the classification accuracy of nodes on five public datasets Cora,Citeseer,Pubmed,Github Web ML,and Facebook are 86.1±0.33,79.2±0.35,83.1±0.46,83.8±0.23,and 80.1±0.37,respectively).This indicates that our approach possesses advantages in handling datasets with implicit multi-level structures.
基金financially supported by the National Natural Science Foundation of China(Nos.52120105007 and 52374062)the Innovation Fund Project for Graduate Students of China University of Petroleum(East China)supported by“the Fundamental Research Funds for the Central Universities”(23CX04047A)。
文摘A gel based on polyacrylamide,exhibiting delayed crosslinking characteristics,emerges as the preferred solution for mitigating degradation under conditions of high temperature and extended shear in ultralong wellbores.High viscosity/viscoelasticity of the fracturing fluid was required to maintain excellent proppant suspension properties before gelling.Taking into account both the cost and the potential damage to reservoirs,polymers with lower concentrations and molecular weights are generally preferred.In this work,the supramolecular action was integrated into the polymer,resulting in significant increases in the viscosity and viscoelasticity of the synthesized supramolecular polymer system.The double network gel,which is formed by the combination of the supramolecular polymer system and a small quantity of Zr-crosslinker,effectively resists temperature while minimizing permeability damage to the reservoir.The results indicate that the supramolecular polymer system with a molecular weight of(268—380)×10^(4)g/mol can achieve the same viscosity and viscoelasticity at 0.4 wt%due to the supramolecular interaction between polymers,compared to the 0.6 wt%traditional polymer(hydrolyzed polyacrylamide,molecular weight of 1078×10^(4)g/mol).The supramolecular polymer system possessed excellent proppant suspension properties with a 0.55 cm/min sedimentation rate at 0.4 wt%,whereas the0.6 wt%traditional polymer had a rate of 0.57 cm/min.In comparison to the traditional gel with a Zrcrosslinker concentration of 0.6 wt%and an elastic modulus of 7.77 Pa,the double network gel with a higher elastic modulus(9.00 Pa)could be formed only at 0.1 wt%Zr-crosslinker,which greatly reduced the amount of residue of the fluid after gel-breaking.The viscosity of the double network gel was66 m Pa s after 2 h shearing,whereas the traditional gel only reached 27 m Pa s.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11975087,42261134533,and 42011530086)the National Magnetic Confinement Fusion Energy Research and Development Program of China(Grant No.2022YFE03190400)the Heilongjiang Touyan Innovation Team Program,China.
文摘Magnetic reconnection processes in three-dimensional(3D)complex field configurations have been investigated in different magneto-plasma systems in space,laboratory,and astrophysical systems.Two-dimensional(2D)features of magnetic reconnection have been well developed and applied successfully to systems with symmetrical property,such as toroidal fusion plasmas and laboratory experiments with an axial symmetry.But in asymmetric systems,the 3D features are inevitably different from those in the 2D case.Magnetic reconnection structures in multiple celestial body systems,particularly star-planet-Moon systems,bring fresh insights to the understanding of the 3D geometry of reconnection.Thus,we take magnetic reconnection in an ancient solar-lunar terrestrial magneto-plasma system as an example by using its crucial parameters approximately estimated already and also some specific applications in pathways for energy and matter transports among Earth,ancient Moon,and the interplanetary magnetic field(IMF).Then,magnetic reconnection of the ancient lunar-terrestrial magnetospheres with the IMF is investigated numerically in this work.In a 3D simulation for the Earth-Moon-IMF system,topological features of complex magnetic reconnection configurations and dynamical characteristics of magnetic reconnection processes are studied.It is found that a coupled lunar-terrestrial magnetosphere is formed,and under various IMF orientations,multiple X-points emerge at distinct locations,showing three typical magnetic reconnection structures in such a geometry,i.e.,the X-line,the triple current sheets,and the A-B null pairs.The results can conduce to further understanding of reconnection physics in 3D for plasmas in complex magnetic configurations,and also a possible mechanism for energy and matters transport in evolutions of similar astrophysical systems.
基金supported in part by the National Natural Science Foundation Original Exploration Project of China under Grant 62250004the National Natural Science Foundation of China under Grant 62271244+1 种基金the Natural Science Fund for Distinguished Young Scholars of Jiangsu Province under Grant BK20220067the Natural Sciences and Engineering Research Council of Canada (NSERC)
文摘As the demand for high-quality services proliferates,an innovative network architecture,the fully-decoupled RAN(FD-RAN),has emerged for more flexible spectrum resource utilization and lower network costs.However,with the decoupling of uplink base stations and downlink base stations in FDRAN,the traditional transmission mechanism,which relies on real-time channel feedback,is not suitable as the receiver is not able to feedback accurate and timely channel state information to the transmitter.This paper proposes a novel transmission scheme without relying on physical layer channel feedback.Specifically,we design a radio map based complex-valued precoding network(RMCPNet)model,which outputs the base station precoding based on user location.RMCPNet comprises multiple subnets,with each subnet responsible for extracting unique modal features from diverse input modalities.Furthermore,the multimodal embeddings derived from these distinct subnets are integrated within the information fusion layer,culminating in a unified representation.We also develop a specific RMCPNet training algorithm that employs the negative spectral efficiency as the loss function.We evaluate the performance of the proposed scheme on the public DeepMIMO dataset and show that RMCPNet can achieve 16%and 76%performance improvements over the conventional real-valued neural network and statistical codebook approach,respectively.
基金This study was supported by the National Water Pollution Control and Treatment Science and Technology Major Project(2017ZX07101-002).
文摘Tree interactions are essential for the structure,dynamics,and function of forest ecosystems,but variations in the architecture of life-stage interaction networks(LSINs)across forests is unclear.Here,we constructed 16 LSINs in the mountainous forests of northwest Hebei,China based on crown overlap from four mixed forests with two dominant tree species.Our results show that LSINs decrease the complexity of stand densities and basal areas due to the interaction cluster differentiation.In addition,we found that mature trees and saplings play different roles,the first acting as“hub”life stages with high connectivity and the second,as“bridges”controlling information flow with high centrality.Across the forests,life stages with higher importance showed better parameter stability within LSINs.These results reveal that the structure of tree interactions among life stages is highly related to stand variables.Our efforts contribute to the understanding of LSIN complexity and provide a basis for further research on tree interactions in complex forest communities.
基金Project supported by the National Natural Science Foundation of China (Grant No. 12161061)the Fundamental Research Funds for the Inner Mongolia University of Finance and Economics (Grant No. NCYWT23036)+2 种基金the Young Innovative and Entrepreneurial Talents of the Inner Mongolia Grassland Talents Project in 2022,Autonomous Region “Five Major Tasks” Research Special Project for the Inner Mongolia University of Finance and Economics in 2024 (Grant No. NCXWD2422)High Quality Research Achievement Cultivation Fund for the Inner Mongolia University of Finance and Economics in 2024 (Grant No. GZCG2426)the Talent Development Fund of Inner Mongolia Autonomous Region, China。
文摘Under investigation in this paper is a complex modified Korteweg–de Vries(KdV) equation, which describes the propagation of short pulses in optical fibers. Bilinear forms and multi-soliton solutions are obtained through the Hirota method and symbolic computation. Breather-like and bound-state solitons are constructed in which the signs of the imaginary parts of the complex wave numbers and the initial separations of the two parallel solitons are important factors for the interaction patterns. The periodic structures and position-induced phase shift of some solutions are introduced.
基金supported by“Undergraduate Innovation and Entrepreneurship Training Program”at Harbin Institute of Technology。
文摘Complex plasma fluctuation processes have been extensively studied in many aspects,especially lattice waves in strongly coupled plasma crystals,which are of great significance for understanding fundamental physical phenomena.A challenge of experimental investigations in two-dimensional strongly coupled complex plasma crystals is to keep the main body and foreign particles of different masses on the same horizontal plane.To solve the problem,we have proposed a potential well formed by two negatively biased grids to bind the negatively charged particles in a two-dimensional(2D)plane,thus achieving a 2D plasma crystal in the microgravity environment.The study of such phenomena in complex plasma crystals under microgravity environment then becomes possible.In this paper,we focus on the continuum spectrum,including both phonon and optic branches of the impurity mode in a 2D system in microgravity environments.The results show the dispersion relation of the longitudinal and transverse impurity oscillation modes and their properties.Considering the macroscopic visibility of complex mesoscopic particle lattices,theoretical and experimental studies on this kind of complex plasma systems will help us further understand the physical nature of a wide range of condensed matters.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.62103375,62006106,61877055,and 62171413)the Philosophy and Social Science Planning Project of Zhejinag Province,China(Grant No.22NDJC009Z)+1 种基金the Education Ministry Humanities and Social Science Foundation of China(Grant No.19YJCZH056)the Natural Science Foundation of Zhejiang Province,China(Grant Nos.LY23F030003,LY22F030006,and LQ21F020005).
文摘The dissemination of information across various locations is an ubiquitous occurrence,however,prevalent methodologies for multi-source identification frequently overlook the fact that sources may initiate dissemination at distinct initial moments.Although there are many research results of multi-source identification,the challenge of locating sources with varying initiation times using a limited subset of observational nodes remains unresolved.In this study,we provide the backward spread tree theorem and source centrality theorem,and develop a backward spread centrality algorithm to identify all the information sources that trigger the spread at different start times.The proposed algorithm does not require prior knowledge of the number of sources,however,it can estimate both the initial spread moment and the spread duration.The core concept of this algorithm involves inferring suspected sources through source centrality theorem and locating the source from the suspected sources with linear programming.Extensive experiments from synthetic and real network simulation corroborate the superiority of our method in terms of both efficacy and efficiency.Furthermore,we find that our method maintains robustness irrespective of the number of sources and the average degree of network.Compared with classical and state-of-the art source identification methods,our method generally improves the AUROC value by 0.1 to 0.2.
