Classification of knowledge graph completeness measurement techniques

At present,although knowledge graphs have been widely used in various fields such as recommendation systems,question and answer systems,and intelligent search,there are always quality problems such as knowledge omissions and errors.Quality assessment and control,as an important means to ensure the quality of knowledge,can make the applications based on knowledge graphs more complete and more accurate by reasonably assessing the knowledge graphs and fixing and improving the quality problems at the same time.Therefore,as an indispensable part of the knowledge graph construction process,the results of quality assessment and control determine the usefulness of the knowledge graph.Among them,the assessment and enhancement of completeness,as an important part of the assessment and control phase,determine whether the knowledge graph can fully reflect objective phenomena and reveal potential connections among entities.In this paper,we review specific techniques of completeness assessment and classify completeness assessment techniques in terms of closed world assumptions,open world assumptions,and partial completeness assumptions.The purpose of this paper is to further promote the development of knowledge graph quality control and to lay the foundation for subsequent research on the completeness assessment of knowledge graphs by reviewing and classifying completeness assessment techniques.

Multi-Material Topology Optimization of 2D Structures Using Convolutional Neural Networks

In recent years,there has been significant research on the application of deep learning(DL)in topology optimization(TO)to accelerate structural design.However,these methods have primarily focused on solving binary TO problems,and effective solutions for multi-material topology optimization(MMTO)which requires a lot of computing resources are still lacking.Therefore,this paper proposes the framework of multiphase topology optimization using deep learning to accelerate MMTO design.The framework employs convolutional neural network(CNN)to construct a surrogate model for solving MMTO,and the obtained surrogate model can rapidly generate multi-material structure topologies in negligible time without any iterations.The performance evaluation results show that the proposed method not only outputs multi-material topologies with clear material boundary but also reduces the calculation cost with high prediction accuracy.Additionally,in order to find a more reasonable modeling method for MMTO,this paper studies the characteristics of surrogate modeling as regression task and classification task.Through the training of 297 models,our findings show that the regression task yields slightly better results than the classification task in most cases.Furthermore,The results indicate that the prediction accuracy is primarily influenced by factors such as the TO problem,material category,and data scale.Conversely,factors such as the domain size and the material property have minimal impact on the accuracy.

Plastic deformation behavior of a Cu-10Ta alloy under strong impact loading

In this work,a Cu-10Ta alloy with a copper to tantalum mass ratio of 9:1 is prepared using powder metallurgy technology.Physical properties of the alloy,including density,microstructure,melting point,and constant-volume specific heat,are tested.Via the split Hopkinson pressure bar(SHPB)and flyerplate impact experiments,the relationship between equivalent stress and equivalent plastic strain of the material is studied at temperatures of 298-823 K and under strain rates of 1×10^(-3)-5.2×10^(3)s^(-1),and the Hugoniot relationship at impact pressures of 1.46-17.25 GPa and impact velocities of 108-942 m/s is obtained.Evolution of the Cu-10Ta microstructure that occurs during high-strain-rate impact is analyzed.Results indicate that the Cu-10Ta alloy possesses good thermal stability,and at ambient temperatures of up to 50%its melting point,stress softening of less than 15%of the initial strength is observed.A modified J-C constitutive model is employed to accurately predict the variation of yield strength with strain rate.Under strong impact,the copper phase is identified as the primary source of plastic deformation in the Cu-10Ta alloy,while significant deformation of the high-strength tantalum particles is less pronounced.Furthermore,the longitudinal wave speed D is found to correlate linearly with the particle velocity u upon strong impact.Analysis reveals that the sound speed and spallation strength of the alloy increase with increasing impact pressure.

The Anti-Penetration Performance and Mechanism of Metal Materials:A Review

This article reviews the anti-penetration principles and strengthening mechanisms of metal materials,ranging from macroscopic failure modes to microscopic structural characteristics,and further summarizes the micro-macro correlation in the anti-penetration process.Finally,it outlines the constitutive models and numerical simulation studies utilized in the field of impact and penetration.From the macro perspective,nine frequent penetration failure modes of metal materials are summarized,with a focus on the analysis of the cratering,compression shear,penetration,and plugging stages of the penetration process.The reasons for the formation of adiabatic shear bands(ASBs)in metal materials with different crystal structures are elaborated,and the formation mechanism of the equiaxed grains in the ASB is explored.Both the strength and the toughness of metal materials are related to the materials’crystal structures and microstructures.The toughness is mainly influenced by the deformation mechanism,while the strength is explained by the strengthening mechanism.Therefore,the mechanical properties of metal materials depend on their microstructures,which are subject to the manufacturing process and material composition.Regarding numerical simulation,the advantages and disadvantages of different constitutive models and simulation methods are summarized based on the application characteristics of metal materials in high-speed penetration practice.In summary,this article provides a systematic overview of the macroscopic and microscopic characteristics of metal materials,along with their mechanisms and correlation during the anti-penetration and impact-resistance processes,thereby making an important contribution to the scientific understanding of anti-penetration performance and its optimization in metal materials.

An Intelligent Framework for Resilience Recovery of FANETs with Spatio-Temporal Aggregation and Multi-Head Attention Mechanism

Due to the time-varying topology and possible disturbances in a conflict environment,it is still challenging to maintain the mission performance of flying Ad hoc networks(FANET),which limits the application of Unmanned Aerial Vehicle(UAV)swarms in harsh environments.This paper proposes an intelligent framework to quickly recover the cooperative coveragemission by aggregating the historical spatio-temporal network with the attention mechanism.The mission resilience metric is introduced in conjunction with connectivity and coverage status information to simplify the optimization model.A spatio-temporal node pooling method is proposed to ensure all node location features can be updated after destruction by capturing the temporal network structure.Combined with the corresponding Laplacian matrix as the hyperparameter,a recovery algorithm based on the multi-head attention graph network is designed to achieve rapid recovery.Simulation results showed that the proposed framework can facilitate rapid recovery of the connectivity and coverage more effectively compared to the existing studies.The results demonstrate that the average connectivity and coverage results is improved by 17.92%and 16.96%,respectively compared with the state-of-the-art model.Furthermore,by the ablation study,the contributions of each different improvement are compared.The proposed model can be used to support resilient network design for real-time mission execution.

How to implement a knowledge graph completeness assessment with the guidance of user requirements

In the context of big data, many large-scale knowledge graphs have emerged to effectively organize the explosive growth of web data on the Internet. To select suitable knowledge graphs for use from many knowledge graphs, quality assessment is particularly important. As an important thing of quality assessment, completeness assessment generally refers to the ratio of the current data volume to the total data volume.When evaluating the completeness of a knowledge graph, it is often necessary to refine the completeness dimension by setting different completeness metrics to produce more complete and understandable evaluation results for the knowledge graph.However, lack of awareness of requirements is the most problematic quality issue. In the actual evaluation process, the existing completeness metrics need to consider the actual application. Therefore, to accurately recommend suitable knowledge graphs to many users, it is particularly important to develop relevant measurement metrics and formulate measurement schemes for completeness. In this paper, we will first clarify the concept of completeness, establish each metric of completeness, and finally design a measurement proposal for the completeness of knowledge graphs.

Design and implementation of code acquisition using sparse Fourier transform

Code acquisition is the kernel operation for signal synchronization in the spread-spectrum receiver.To reduce the computational complexity and latency of code acquisition,this paper proposes an efficient scheme employing sparse Fourier transform(SFT)and the relevant hardware architecture for field programmable gate array(FPGA)and application-specific integrated circuit(ASIC)implementation.Efforts are made at both the algorithmic level and the implementation level to enable merged searching of code phase and Doppler frequency without incurring massive hardware expenditure.Compared with the existing code acquisition approaches,it is shown from theoretical analysis and experimental results that the proposed design can shorten processing latency and reduce hardware complexity without degrading the acquisition probability.

The metabolic profiling of Chinese yam fermented by Saccharomyces boulardii and the biological activities of its ethanol extract in vitro

Chinese yam(Dioscorea opposita Thunb.),as one of the medicinal and edible homologous plants,is rich in various nutrients and functional factors.In this study,Chinese yam fermented by Saccharomyces boulardii was performed to investigate its bioactive components and metabolic profile.And then,the main bioactive components and biological activities of fermented Chinese yam ethanol extract(FCYE)were evaluated.Results showed that there were 49 up-regulated metabolites and 52 down-regulated metabolites in fermented Chinese yam compared to unfermented Chinese yam.Besides,corresponding metabolic pathways analysis initially revealed that the distribution of bioactive substances was concentrated on alcoholsoluble small molecular substances.Ulteriorly,the total polyphenol content and the total flavonoid content in FCYE were significantly increased,and the corresponding antioxidant and immunomodulatory activities in vitro were also significantly enhanced.Our study provided a new reference for the comprehensive utilization of Chinese yam and laid a theoretical foundation for the development and application of natural probiotic-fermented products.

Development and Therapeutic Applications of Precise Gene Editing Technology

The advent of gene editing represents one of the most transformative breakthroughs in life science,making genome manipulation more accessible than ever before.While traditional CRISPR/Cas-based gene editing,which involves double-strand DNA breaks(DSBs),excels at gene disruption,it is less effective for accurate gene modification.The limitation arises because DSBs are primarily repaired via non-homologous end joining(NHEJ),which tends to introduce indels at the break site.While homology directed repair(HDR)can achieve precise editing when a donor DNA template is provided,the reliance on DSBs often results in unintended genome damage.HDR is restricted to specific cell cycle phases,limiting its application.Currently,gene editing has evolved to unprecedented levels of precision without relying on DSB and HDR.The development of innovative systems,such as base editing,prime editing,and CRISPR-associated transposases(CASTs),now allow for precise editing ranging from single nucleotides to large DNA fragments.Base editors(BEs)enable the direct conversion of one nucleotide to another,and prime editors(PEs)further expand gene editing capabilities by allowing for the insertion,deletion,or alteration of small DNA fragments.The CAST system,a recent innovation,allows for the precise insertion of large DNA fragments at specific genomic locations.In recent years,the optimization of these precise gene editing tools has led to significant improvements in editing efficiency,specificity,and versatility,with advancements such as the creation of base editors for nucleotide transversions,enhanced prime editing systems for more efficient and precise modifications,and refined CAST systems for targeted large DNA insertions,expanding the range of applications for these tools.Concurrently,these advances are complemented by significant improvements in in vivo delivery methods,which have paved the way for therapeutic application of precise gene editing tools.Effective delivery systems are critical for the success of gene therapies,and recent developments in both viral and non-viral vectors have improved the efficiency and safety of gene editing.For instance,adeno-associated viruses(AAVs)are widely used due to their high transfection efficiency and low immunogenicity,though challenges such as limited cargo capacity and potential for immune responses remain.Non-viral delivery systems,including lipid nanoparticles(LNPs),offer an alternative with lower immunogenicity and higher payload capacity,although their transfection efficiency can be lower.The therapeutic potential of these precise gene editing technologies is vast,particularly in treating genetic disorders.Preclinical studies have demonstrated the effectiveness of base editing in correcting genetic mutations responsible for diseases such as cardiomyopathy,liver disease,and hereditary hearing loss.These technologies promise to treat symptoms and potentially cure the underlying genetic causes of these conditions.Meanwhile,challenges remain,such as optimizing the safety and specificity of gene editing tools,improving delivery systems,and overcoming off-target effects,all of which are critical for their successful application in clinical settings.In summary,the continuous evolution of precise gene editing technologies,combined with advancements in delivery systems,is driving the field toward new therapeutic applications that can potentially transform the treatment of genetic disorders by targeting their root causes.

Discrete Element Modelling of Damage Evolution of Concrete Considering Meso-Structure of ITZ

The mechanical properties of interfacial transition zones(ITZs)have traditionally been simplified by reducing the stiffness of cement in previous simulation methods.A novel approach based on the discrete element method(DEM)has been developed for modeling concrete.This new approach efficiently simulates the meso-structure of ITZs,accurately capturing their heterogeneous properties.Validation against established uniaxial compression experiments confirms the precision of thismodel.The proposedmodel canmodel the process of damage evolution containing cracks initiation,propagation and penetration.Under increasing loads,cracks within ITZs progressively accumulate,culminating in macroscopic fractures that traverse themortarmatrix,forming the complex,serpentine path of cracks.This study reveals four distinct displacement patterns:tensile compliant,tensile opposite,mixed tensile-shear,and shear opposite patterns,each indicative of different stages in concrete’s damage evolution.The widening angle of these patterns delineates the progression of cracks,with the tensile compliant pattern signaling the initial crack appearance and the shear opposite pattern indicating the concrete model’s ultimate failure.

Damage effect and mechanisms of cyclophosphamide to human neuroblastoma SH-SY5Y cells

OBJECTIVE To investigate the damage effect and mechanisms of cyclophosphamide(CTX)and its active metabolite derivative 4-hydroperoxycyclophosphamide(4-HC)to human neuroblas⁃toma SH-SY5Y cells.METHODS SH-SY5Y cells were treated with CTX[0(cell control),0.01,0.1,1,5,10,20,40 and 80 mmol·L^(-1)]and 4-HC[0(cell control),0.01,0.1,1,5,10,20,40 and 80μmol·L^(-1)]for 48 h.Cell confluence and morphology were observed by the IncuCyte ZOOM system.Cell viability was assessed by CCK-8 assay.Lactate dehydrogenase(LDH)release was measured by LDH assay kit.SH-SY5Y cells were treated with CTX(0,1,5,10 and 20 mmol·L^(-1))and 4-HC(0,1,5,10 and 20μmol·L^(-1))for 48 h before cell proliferation was analyzed by 5-ethynyl-2′-deoxyuridine(EdU)staining assay.Immunofluorescence was employed to assess the levels of the DNA double-strand break markerγ-H2AX and to evaluate changes in mitochondrial membrane potential.SH-SY5Y cells were treated with CTX(0,1,5 and 10 mmol·L^(-1))and 4-HC(0,1,5 and 10μmol·L^(-1))for 48 h,and the alterations in glycolysis and oxidative phosphorylation levels were analyzed using the Seahorse XFe96 Analyzer.RESULTS Compared with the cell control group,cell confluence and cell viability were significantly reduced in the CTX and 4-HC groups(P<0.01),and the half-maximal inhibitory concentrations(IC50)for CTX and 4-HC were 4.44 mmol·L^(-1) and 4.78μmol·L^(-1),respectively.The release rate of LDH was signif⁃icantly increased while the percentage of EdU+cells was significantly reduced in the CTX and 4-HC groups(P<0.01).The percentage ofγ-H2AX+cells was significantly increased and mitochondrial membrane potential significantly decreased in the CTX and 4-HC group(P<0.05).Treatment with CTX and 4-HC resulted in reduced levels of maximum glycolytic capacity,glycolytic reserve,maximal respi⁃ration,and ATP production(P<0.05).CONCLUSION CTX and 4-HC exert significant cytotoxic effects on SH-SY5Y cells by disrupting cell membrane structure,impeding cell proliferation,and reducing cell viability.The mechanisms underlying these effects may involve intracellular DNA damage,disturbance of energy metabolism and mitochondrial dysfunction.

Average Secrecy Capacity of the Reconfigurable Intelligent Surface-Assisted Integrated Satellite Unmanned Aerial Vehicle Relay Networks

Integrated satellite unmanned aerial vehicle relay networks(ISUAVRNs)have become a prominent topic in recent years.This paper investigates the average secrecy capacity(ASC)for reconfigurable intelligent surface(RIS)-enabled ISUAVRNs.Especially,an eve is considered to intercept the legitimate information from the considered secrecy system.Besides,we get detailed expressions for the ASC of the regarded secrecy system with the aid of the reconfigurable intelligent.Furthermore,to gain insightful results of the major parameters on the ASC in high signalto-noise ratio regime,the approximate investigations are further gotten,which give an efficient method to value the secrecy analysis.At last,some representative computer results are obtained to prove the theoretical findings.

Uncertainty-Aware Physical Simulation of Neural Radiance Fields for Fluids

This paper presents a novel framework aimed at quantifying uncertainties associated with the 3D reconstruction of smoke from2Dimages.This approach reconstructs color and density fields from 2D images using Neural Radiance Field(NeRF)and improves image quality using frequency regularization.The NeRF model is obtained via joint training ofmultiple artificial neural networks,whereby the expectation and standard deviation of density fields and RGB values can be evaluated for each pixel.In addition,customized physics-informed neural network(PINN)with residual blocks and two-layer activation functions are utilized to input the density fields of the NeRF into Navier-Stokes equations and convection-diffusion equations to reconstruct the velocity field.The velocity uncertainties are also evaluated through ensemble learning.The effectiveness of the proposed algorithm is demonstrated through numerical examples.The presentmethod is an important step towards downstream tasks such as reliability analysis and robust optimization in engineering design.

Sensitivity Analysis of Electromagnetic Scattering from Dielectric Targets with Polynomial Chaos Expansion and Method of Moments

In this paper,an adaptive polynomial chaos expansion method(PCE)based on the method of moments(MoM)is proposed to construct surrogate models for electromagnetic scattering and further sensitivity analysis.The MoM is applied to accurately solve the electric field integral equation(EFIE)of electromagnetic scattering from homogeneous dielectric targets.Within the bistatic radar cross section(RCS)as the research object,the adaptive PCE algorithm is devoted to selecting the appropriate order to construct the multivariate surrogate model.The corresponding sensitivity results are given by the further derivative operation,which is compared with those of the finite difference method(FDM).Several examples are provided to demonstrate the effectiveness of the proposed algorithm for sensitivity analysis of electromagnetic scattering from homogeneous dielectric targets.

Chinese Society of Clinical Oncology Breast Cancer(CSCO BC)Guidelines in 2024:International Contributions from China

The Chinese Society of Clinical Oncology Breast Cancer(CSCO BC)guidelines have been widely implemented in China since the first release in 2017.The Guideline Working Committee has also published multiple versions in English,Arabic,and other languages to facilitate communications with international experts.

Relationships between distribution characteristics of ceramic fragments and anti-penetration performance of ceramic composite bulletproof insert plates

Through quantitative statistics and morphological characterization of ceramic fragments for ceramic composite bulletproof insert plates(CCBIPs),distribution characteristics of ceramic fragments within a specific size range were analyzed for different Armor Piercing Incendiary(API)and shot times.To quantitatively evaluate the effect of energy absorption for ceramic plates,a model of energy absorption during penetration for CCBIPs was established based on statistics of the size distribution of ceramic fragments(SDCF).Variation in the SDCF and its influence on energy absorption for CCBIPs were investigated.The results indicate that the distribution feature of ceramic fragments in the range of 0.25-2.25 mm is Gaussian distribution.Compared with Type 56 of API(56-API),ceramic fragments formed by 53-API with higher kinetic energy possess more quantity and more concentrated distribution,whose average equivalence size decreases by 6.5%,corresponding to increasing by 83.9%of estimated energy absorption.Besides,the ability of CCBIPs to resist the third shot is significantly weakened,whose estimated energy absorption decreases by 58.8%compared with the first shot.More concentrated distribution and fewer fragments are formed after the third shot,the average equivalence size of ceramic fragments increases by 6.9%,which may attribute to the micro-cracks induced by the previous two shots.

Mission reliability modeling and evaluation for reconfigurable unmanned weapon system-of-systems based on effective operation loop

The concept of unmanned weapon system-of-systems(UWSoS)involves a collection of various unmanned systems to achieve or accomplish a specific goal or mission.The mission reliability of UWSoS is represented by its ability to finish a required mission above the baselines of a given mission.However,issues with heterogeneity,cooperation between systems,and the emergence of UWSoS cannot be effectively solved by traditional system reliability methods.This study proposes an effective operation-loop-based mission reliability evaluation method for UWSoS by analyzing dynamic reconfiguration.First,we present a new connotation of an effective operation loop by considering the allocation of operational entities and physical resource constraints.Then,we propose an effective operationloop-based mission reliability model for a heterogeneous UWSoS according to the mission baseline.Moreover,a mission reliability evaluation algorithm is proposed under random external shocks and topology reconfiguration,revealing the evolution law of the effective operation loop and mission reliability.Finally,a typical 60-unmanned-aerial-vehicle-swarm is taken as an example to demonstrate the proposed models and methods.The mission reliability is achieved by considering external shocks,which can serve as a reference for evaluating and improving the effectiveness of UWSoS.

Magneto-hydrodynamic simulation study of direct current multi-contact circuit breaker for equalizing breaking arc

This work is based on a direct current(DC)natural current commutation topology,which uses load-carrying branch contacts carrying rated current and multiple sets of series arcing branch contacts in parallel to achieve circuit breaking.The proposed topology can meet the new requirements of higher voltage DC switches in aviation,aerospace,energy and other fields.First,a magneto-hydrodynamic arc model is built using COMSOL Multiphysics,and the different arc breaking characteristics of the arcing branch contacts in different gas environments are simulated.Then,a voltage uniformity coefficient is used to measure the voltage sharing effect in the process of dynamic interruption.In order to solve the dispersion of arcing contact action,a structural control method is adopted to improve the voltage uniformity coefficient.The uniform voltage distribution can improve the breaking capacity and electrical life of the series connection structure.

Mesoscopic modelling of UHPCC material under dynamic tensile loadings

This paper presents a new 3D mesoscopic model of ultra-high performance cement-based composite(UHPCC)to investigate its dynamic tensile behavior.In this model,the UHPCC is regarded as a two-phase material composed of cementitious matrix and randomly distributed fibers.The model is established using the commercial software LS-DYNA and involves generating the randomly distributed fiber elements with considerations of diameter,length,orientation and volume fraction,and then fully constraining them with the matrix.In particular,to capture the slipping effect between fibers and matrix that has a strong influence on the dynamic tensile behavior,the fibers are modelled by a fictitious material represented by the load-slip relation.The strain-rate effect of slipping force neglected in most of previous studies is considered by calibrating constitutive parameters of the fictitious material under different strain-rates based on the single fiber pullout tests.Finally,the 3D mesoscopic model is validated against three sets of tension-dominated experiments covered a wide range of loading intensity.Numerical predictions demonstrate that strain-rate effect of slipping force must be considered,and the neglect of it may lead to a great underestimation of the dynamic tensile strength of UHPCC material and would unavoidably underestimate the blast resistance of UHPCC components.

Silicon dioxide nanoparticles inhibit the effects of cold exposure on metabolism and inflammatory responses in brown adipocytes

Objective:Nanoparticles(NPs)in haze are potentially hazardous to health,which is more severe in the winter.Brown adipose tissue(BAT)plays important roles in obesity,insulin resistance,and diabetes.Though the toxicology of NPs has been intensively studied,few studies have been reported on the antagonistic effects between Silicon dioxide(SiO_(2))NPs and cold exposure in brown adipocytes.Materials and methods:We evaluated changes by quantitative real-time reverse-transcriptase polymerase chain reaction(qRT-PCR)on metabolism genes,plasticity genes and the inflammatory responses genes in brown adipocytes in vitro.Results:The expression of adipogenic genes PRDM16,Dio2,PGC-1αand UCP1 was upregulated upon cold exposure(P<0.05),but downregulated by SiO_(2) NPs(P<0.05).The results demonstrated that there was antagonistic effect between SiO_(2) NPs and cold exposure on the plasticity genes and metabolism genes in brown adipocytes,where the main effects of SiO_(2) NPs or cold exposure on the plasticity genes and metabolism genes were significant(P<0.05).Moreover,the levels of interleukin(IL)-1β,IL-6 and tumor necrosis factor(TNF)-αwere upregulated by SiO_(2) NPs or cold exposure(P<0.05).The factorial analysis indicated that there was also antagonistic effect between SiO_(2) NPs and cold exposure on the toxic effects in brown adipocytes,in which the main effects of cold exposure and/or SiO_(2) NPs on the toxic effects were significant(P<0.05).Conclusion:SiO_(2) NPs inhibit the effect of cold exposure on metabolic genes and inflammatory responses genes in brown adipocytes.