Multilayer complex dynamical networks,characterized by the intricate topological connections and diverse hierarchical structures,present significant challenges in determining complete structural configurations due to ...Multilayer complex dynamical networks,characterized by the intricate topological connections and diverse hierarchical structures,present significant challenges in determining complete structural configurations due to the unique functional attributes and interaction patterns inherent to different layers.This paper addresses the critical question of whether structural information from a known layer can be used to reconstruct the unknown intralayer structure of a target layer within general weighted output-coupling multilayer networks.Building upon the generalized synchronization principle,we propose an innovative reconstruction method that incorporates two essential components in the design of structure observers,the cross-layer coupling modulator and the structural divergence term.A key advantage of the proposed reconstruction method lies in its flexibility to freely designate both the unknown target layer and the known reference layer from the general weighted output-coupling multilayer network.The reduced dependency on full-state observability enables more deployment in engineering applications with partial measurements.Numerical simulations are conducted to validate the effectiveness of the proposed structure reconstruction method.展开更多
The emergence of precision electronic devices and wearable electronic products urgently requires high-performance multifunctional electromagnetic wave(EMW)absorbers to meet the applicability and versatility in various...The emergence of precision electronic devices and wearable electronic products urgently requires high-performance multifunctional electromagnetic wave(EMW)absorbers to meet the applicability and versatility in various applications.Herein,a dual-network(DN)gel was successfully prepared using acrylamide and sodium lignosulphonate as the basic units by simple chemical cross-linking and physical cross-linking methods.Specifically,the hydrogel forms two types of cross-linking networks through metal coordination and hydrogen bonding.Benefiting from the combined effects of dipole polarization and conductivity loss,the gel achieves an effective absorption bandwidth(EAB)of 6.74 GHz at a thickness of only 1.89 mm,demonstrating excellent EMW absorption performance.In addition,this unique structural configuration endows the EMW absorber with multifunctional features,such as remarkable tensile strength,good environmental compatibility,ultraviolet(UV)resistance,and excellent adhesion.Integrating multiple functional features into the EMW gels displays a broad application prospect in a variety of application scenarios.This research reveals the significance of DN structure design in the electromagnetic wave absorption(EWA)performance of gel-based materials,providing a substantial foundation for the multifunctional design of gel-based absorbers.展开更多
With the rapid growth of technologies requiring high-power energy storage,achieving long-term cyclic stability under ultra-high current density is a key challenge.Aqueous zinc-ion batteries(AZIBs)are promising candida...With the rapid growth of technologies requiring high-power energy storage,achieving long-term cyclic stability under ultra-high current density is a key challenge.Aqueous zinc-ion batteries(AZIBs)are promising candidates due to their intrinsic safety and low cost,but they suffer from severe interfacial instability at rates exceeding 10 mA cm^(-2),which drastically shortens their cycle life.Inspired by theoretical calculations,triglyme(TGDE)additive with strong electron-donating groups into Zn(OTf)_(2) electrolytes effectively disrupts the hydrogen-bond network among free water molecules,while the weak coordination of TGDE with Zn^(2+)promotes the entry of OTf-into the primary Zn^(2+)solvated sheath,thus decreasing the coordination number of water with Zn^(2+).As such,the hydrogen-bond network and the bulk solvated structure are reconstructed with better stability.Moreover,the strong adsorption of TGDE lying on the Zn(002)surface would induce Zn depositions along(002)together with the reduced exposed surface,further effectively inhibiting side reactions.Likewise,TGDE electrolyte induces the formation of such ZnF_(2)-ZnS dual-layer solid electrolyte interface(SEI)with superior chemical stability and ionic conductivity,thereby regulating Zn^(2+)flux with dendrite-free depositions.Based on this electrolyte,Zn‖Zn cells can be stably cycled for 1300 h at a limit of 10 mA cm^(-2) and 10 mAh cm^(-2).The assembled Zn‖V_(2)O_(5) full cells still maintain 99.9%capacity retention after 1000 cycles at 10 A g^(-1).This work provides a feasible approach for designing aqueous electrolytes to reconstruct the hydrogen-bond network and solvated structure,which can be extended to the applications of high-rate and high-temperature scenarios.展开更多
Alkali-free SiO_(2)-Al_(2)O_(3)-CaO-MgO with different SiO_(2)/Al_(2)O_(3)mass ratios was prepared by conventional melt quenching method.The glass network structure,thermodynamic properties and elastic modulus changes...Alkali-free SiO_(2)-Al_(2)O_(3)-CaO-MgO with different SiO_(2)/Al_(2)O_(3)mass ratios was prepared by conventional melt quenching method.The glass network structure,thermodynamic properties and elastic modulus changes with SiO_(2)and Al_(2)O_(3)ratios were investigated using various techniques.It is found that when SiO_(2)is replaced by Al_(2)O_(3),the Q^(4) to Q^(3) transition of silicon-oxygen network decreases while the aluminum-oxygen network increases,which result in the transformation of Si-O-Si bonds to Si-O-Al bonds and an increase in glass network connectivity even though the intermolecular bond strength decreases.The glass transition temperature(T_(g))increases continuously,while the thermal expansion coefficient increases and high-temperature viscosity first decreases and then increases.Meanwhile,the elastic modulus values increase from 93 to 102 GPa.This indicates that the elastic modulus is mainly affected by packing factor and dissociation energy,and elements with higher packing factors and dissociation energies supplant those with lower values,resulting in increased rigidity within the glass.展开更多
An efficient data-driven numerical framework is developed for transient heat conduction analysis in thin-walled structures.The proposed approach integrates spectral time discretization with neural network approximatio...An efficient data-driven numerical framework is developed for transient heat conduction analysis in thin-walled structures.The proposed approach integrates spectral time discretization with neural network approximation,forming a spectral-integrated neural network(SINN)scheme tailored for problems characterized by long-time evolution.Temporal derivatives are treated through a spectral integration strategy based on orthogonal polynomial expansions,which significantly alleviates stability constraints associated with conventional time-marching schemes.A fully connected neural network is employed to approximate the temperature-related variables,while governing equa-tions and boundary conditions are enforced through a physics-informed loss formulation.Numerical investigations demonstrate that the proposed method maintains high accuracy even when large time steps are adopted,where standard numerical solvers often suffer from instability or excessive computational cost.Moreover,the framework exhibits strong robustness for ultrathin configurations with extreme aspect ratios,achieving relative errors on the order of 10−5 or lower.These results indicate that the SINN framework provides a reliable and efficient alternative for transient thermal analysis of thin-walled structures under challenging computational conditions.展开更多
This research centers on structural health monitoring of bridges,a critical transportation infrastructure.Owing to the cumulative action of heavy vehicle loads,environmental variations,and material aging,bridge compon...This research centers on structural health monitoring of bridges,a critical transportation infrastructure.Owing to the cumulative action of heavy vehicle loads,environmental variations,and material aging,bridge components are prone to cracks and other defects,severely compromising structural safety and service life.Traditional inspection methods relying on manual visual assessment or vehicle-mounted sensors suffer from low efficiency,strong subjectivity,and high costs,while conventional image processing techniques and early deep learning models(e.g.,UNet,Faster R-CNN)still performinadequately in complex environments(e.g.,varying illumination,noise,false cracks)due to poor perception of fine cracks andmulti-scale features,limiting practical application.To address these challenges,this paper proposes CACNN-Net(CBAM-Augmented CNN),a novel dual-encoder architecture that innovatively couples a CNN for local detail extraction with a CBAM-Transformer for global context modeling.A key contribution is the dedicated Feature FusionModule(FFM),which strategically integratesmulti-scale features and focuses attention on crack regions while suppressing irrelevant noise.Experiments on bridge crack datasets demonstrate that CACNNNet achieves a precision of 77.6%,a recall of 79.4%,and an mIoU of 62.7%.These results significantly outperform several typical models(e.g.,UNet-ResNet34,Deeplabv3),confirming their superior accuracy and robust generalization,providing a high-precision automated solution for bridge crack detection and a novel network design paradigm for structural surface defect identification in complex scenarios,while future research may integrate physical features like depth information to advance intelligent infrastructure maintenance and digital twin management.展开更多
It is well known that aluminum and copper exhibit structural phase transformations in quasi-static and dynamic measurements,including shock wave loading.However,the dependence of phase transformations in a wide range ...It is well known that aluminum and copper exhibit structural phase transformations in quasi-static and dynamic measurements,including shock wave loading.However,the dependence of phase transformations in a wide range of crystallographic directions of shock loading has not been revealed.In this work,we calculated the shock Hugoniot for aluminum and copper in different crystallographic directions([100],[110],[111],[112],[102],[114],[123],[134],[221]and[401])of shock compression using molecular dynamics(MD)simulations.The results showed a high pressure(>160 GPa for Cu and>40 GPa for Al)of the FCC-to-BCC transition.In copper,different characteristics of the phase transition are observed depending on the loading direction with the[100]compression direction being the weakest.The FCC-to-BCC transition for copper is in the range of 150–220 GPa,which is consistent with the existing experimental data.Due to the high transition pressure,the BCC phase transition in copper competes with melting.In aluminum,the FCC-to-BCC transition is observed for all studied directions at pressures between 40 and 50 GPa far beyond the melting.In all considered cases we observe the coexistence of HCP and BCC phases during the FCC-to-BCC transition,which is consistent with the experimental data and atomistic calculations;this HCP phase forms in the course of accompanying plastic deformation with dislocation activity in the parent FCC phase.The plasticity incipience is also anisotropic in bothmetals,which is due to the difference in the projections of stress on the slip plane for different orientations of the FCC crystal.MD modeling results demonstrate a strong dependence of the FCC-to-BCC transition on the crystallographic direction,in which the material is loaded in the copper crystals.However,MD simulations data can only be obtained for specific points in the stereographic direction space;therefore,for more comprehensive understanding of the phase transition process,a feed-forward neural network was trained using MD modeling data.The trained machine learning model allowed us to construct continuous stereographic maps of phase transitions as a function of stress in the shock-compressed state of metal.Due to appearance and growth of multiple centers of new phase,the FCC-to-BCC transition leads to formation of a polycrystalline structure from the parent single crystal.展开更多
Six new lanthanide complexes:[Ln(3,4-DEOBA)3(4,4'-DM-2,2'-bipy)]2·2C_(2)H_(5)OH,[Ln=Dy(1),Eu(2),Tb(3),Sm(4),Ho(5),Gd(6);3,4-DEOBA-=3,4-diethoxybenzoate,4,4'-DM-2,2'-bipy=4,4'-dimethyl-2,2'...Six new lanthanide complexes:[Ln(3,4-DEOBA)3(4,4'-DM-2,2'-bipy)]2·2C_(2)H_(5)OH,[Ln=Dy(1),Eu(2),Tb(3),Sm(4),Ho(5),Gd(6);3,4-DEOBA-=3,4-diethoxybenzoate,4,4'-DM-2,2'-bipy=4,4'-dimethyl-2,2'-bipyridine]were successfully synthesized by the volatilization of the solution at room temperature.The crystal structures of six complexes were determined by single-crystal X-ray diffraction technology.The results showed that the complexes all have a binuclear structure,and the structures contain free ethanol molecules.Moreover,the coordination number of the central metal of each structural unit is eight.Adjacent structural units interact with each other through hydrogen bonds and further expand to form 1D chain-like and 2D planar structures.After conducting a systematic study on the luminescence properties of complexes 1-4,their emission and excitation spectra were obtained.Experimental results indicated that the fluorescence lifetimes of complexes 2 and 3 were 0.807 and 0.845 ms,respectively.The emission spectral data of complexes 1-4 were imported into the CIE chromaticity coordinate system,and their corre sponding luminescent regions cover the yellow light,red light,green light,and orange-red light bands,respectively.Within the temperature range of 299.15-1300 K,the thermal decomposition processes of the six complexes were comprehensively analyzed by using TG-DSC/FTIR/MS technology.The hypothesis of the gradual loss of ligand groups during the decomposition process was verified by detecting the escaped gas,3D infrared spectroscopy,and ion fragment information detected by mass spectrometry.The specific decomposition path is as follows:firstly,free ethanol molecules and neutral ligands are removed,and finally,acidic ligands are released;the final product is the corresponding metal oxide.CCDC:2430420,1;2430422,2;2430419,3;2430424,4;2430421,5;2430423,6.展开更多
In this study,a novel polysaccharide GPA-G 2-H was derived from ginseng.Furthermore,the coherent study of its structural characteristics,fermented characteristics in vitro,as well as antioxidant mechanism of fermented...In this study,a novel polysaccharide GPA-G 2-H was derived from ginseng.Furthermore,the coherent study of its structural characteristics,fermented characteristics in vitro,as well as antioxidant mechanism of fermented product FGPA-G 2-H on Aβ25-35-induced PC 12 cells were explored.The structure of GPA-G 2-H was determined by means of zeta potential analysis,FTIR,HPLC,XRD,GC-MS and NMR.The backbone of GPA-G 2-H was mainly composed of→4)-α-D-Glcp-(1→with branches substituted at O-3.Notably,GPA-G 2-H was degraded by intestinal microbiota in vitro with total sugar content and pH value decreasing,and short-chain fatty acids(SCFAs)increasing.Moreover,GPA-G 2-H significantly promoted the proliferation of Lactobacillus,Muribaculaceae and Weissella,thereby making positive alterations in intestinal microbiota composition.Additionally,FGPA-G 2-H activated the Nrf 2/HO-1 signaling pathway,enhanced HO-1,NQO 1,SOD and GSH-Px,while inhabited Keap 1,MDA and LDH,which alleviated Aβ-induced oxidative stress in PC 12 cells.These provide a solid theoretical basis for the further development of ginseng polysaccharides as functional food and antioxidant drugs.展开更多
Optimizing routing and resource allocation in decentralized unmanned aerial vehicle(UAV)networks remains challenging due to interference and rapidly changing topologies.The authors introduce a novel framework combinin...Optimizing routing and resource allocation in decentralized unmanned aerial vehicle(UAV)networks remains challenging due to interference and rapidly changing topologies.The authors introduce a novel framework combining double deep Q-networks(DDQNs)and graph neural networks(GNNs)for joint routing and resource allocation.The framework uses GNNs to model the network topology and DDQNs to adaptively control routing and resource allocation,addressing interference and improving network performance.Simulation results show that the proposed approach outperforms traditional methods such as Closest-to-Destination(c2Dst),Max-SINR(mSINR),and Multi-Layer Perceptron(MLP)-based models,achieving approximately 23.5% improvement in throughput,50% increase in connection probability,and 17.6% reduction in number of hops,demonstrating its effectiveness in dynamic UAV networks.展开更多
To explore the material basis and mechanisms of the anti-inflammatory effects of Hibiscus mutabilis L..The active ingredients and potential targets of Hibiscus mutabilis L.were obtained through the literature review a...To explore the material basis and mechanisms of the anti-inflammatory effects of Hibiscus mutabilis L..The active ingredients and potential targets of Hibiscus mutabilis L.were obtained through the literature review and SwissADME platform.Genes related to the inflammation were collected using Genecards and OMIM databases,and the intersection genes were submitted on STRING and DAVID websites.Then,the protein interaction network(PPI),gene ontology(GO)and pathway(KEGG)were analyzed.Cytoscape 3.7.2 software was used to construct the“Hibiscus mutabilis L.-active ingredient-target-inflammation”network diagram,and AutoDockTools-1.5.6 software was used for the molecular docking verification.The antiinflammatory effect of Hibiscus mutabilis L.active ingredient was verified by the RAW264.7 inflammatory cell model.The results showed that 11 active components and 94 potential targets,1029 inflammatory targets and 24 intersection targets were obtained from Hibiscus mutabilis L..The key anti-inflammatory active ingredients of Hibiscus mutabilis L.are quercetin,apigenin and luteolin.Its action pathway is mainly related to NF-κB,cancer pathway and TNF signaling pathway.Cell experiments showed that total flavonoids of Hibiscus mutabilis L.could effectively inhibit the expression of tumor necrosis factor(TNF-α),interleukin 8(IL-8)and epidermal growth factor receptor(EGFR)in LPS-induced RAW 264.7 inflammatory cells.It also downregulates the phosphorylation of human nuclear factor ĸB inhibitory protein α(IĸBα)and NF-κB p65 subunit protein(p65).Overall,the anti-inflammatory effect of Hibiscus mutabilis L.is related to many active components,many signal pathways and targets,which provides a theoretical basis for its further development and application.展开更多
Conformal truss-like lattice structures face significant manufacturability challenges in additive manufac-turing due to overhang angle limitations.To address this problem,we propose a novel angle-constrained optimizat...Conformal truss-like lattice structures face significant manufacturability challenges in additive manufac-turing due to overhang angle limitations.To address this problem,we propose a novel angle-constrained optimization method grounded in the global adjustment of nodal coordinates.First,a build direction is selected to minimize the number of violating struts.Then,an angular-constraint matrix is assembled from strut direction vectors,and analytical sensitivities with respect to nodal coordinates are derived to enable efficient constrained optimization under nonlinear angular inequality constraints.Numerical studies on two complex curved-surface lattices demonstrate that all overhang violations are eliminated while only minor changes are induced in global stiffness and strength.In particular,the maximum displacement of an ergonomic insole varies by only 2.87%after optimization.The results confirm the method’s versatility and engineering robustness,providing a practical approach for additive manufacturing-oriented lattice structure design.展开更多
Identifying the community structure of complex networks is crucial to extracting insights and understanding network properties.Although several community detection methods have been proposed,many are unsuitable for so...Identifying the community structure of complex networks is crucial to extracting insights and understanding network properties.Although several community detection methods have been proposed,many are unsuitable for social networks due to significant limitations.Specifically,most approaches depend mainly on user-user structural links while overlooking service-centric,semantic,and multi-attribute drivers of community formation,and they also lack flexible filtering mechanisms for large-scale,service-oriented settings.Our proposed approach,called community discovery-based service(CDBS),leverages user profiles and their interactions with consulted web services.The method introduces a novel similarity measure,global similarity interaction profile(GSIP),which goes beyond typical similarity measures by unifying user and service profiles for all attributes types into a coherent representation,thereby clarifying its novelty and contribution.It applies multiple filtering criteria related to user attributes,accessed services,and interaction patterns.Experimental comparisons against Louvain,Hierarchical Agglomerative Clustering,Label Propagation and Infomap show that CDBS reveals the higher performance as it achieves 0.74 modularity,0.13 conductance,0.77 coverage,and significantly fast response time of 9.8 s,even with 10,000 users and 400 services.Moreover,community discoverybased service consistently detects a larger number of communities with distinct topics of interest,underscoring its capacity to generate detailed and efficient structures in complex networks.These results confirm both the efficiency and effectiveness of the proposed method.Beyond controlled evaluation,communities discovery based service is applicable to targeted recommendations,group-oriented marketing,access control,and service personalization,where communities are shaped not only by user links but also by service engagement.展开更多
With the growing complexity and decentralization of network systems,the attack surface has expanded,which has led to greater concerns over network threats.In this context,artificial intelligence(AI)-based network intr...With the growing complexity and decentralization of network systems,the attack surface has expanded,which has led to greater concerns over network threats.In this context,artificial intelligence(AI)-based network intrusion detection systems(NIDS)have been extensively studied,and recent efforts have shifted toward integrating distributed learning to enable intelligent and scalable detection mechanisms.However,most existing works focus on individual distributed learning frameworks,and there is a lack of systematic evaluations that compare different algorithms under consistent conditions.In this paper,we present a comprehensive evaluation of representative distributed learning frameworks—Federated Learning(FL),Split Learning(SL),hybrid collaborative learning(SFL),and fully distributed learning—in the context of AI-driven NIDS.Using recent benchmark intrusion detection datasets,a unified model backbone,and controlled distributed scenarios,we assess these frameworks across multiple criteria,including detection performance,communication cost,computational efficiency,and convergence behavior.Our findings highlight distinct trade-offs among the distributed learning frameworks,demonstrating that the optimal choice depends strongly on systemconstraints such as bandwidth availability,node resources,and data distribution.This work provides the first holistic analysis of distributed learning approaches for AI-driven NIDS and offers practical guidelines for designing secure and efficient intrusion detection systems in decentralized environments.展开更多
Sandwich structures are widely favored for their lightweight,high strength and superior impact mitigation capabilities in blast mitigation and transportation safety applications.Their application in large-scale,high-e...Sandwich structures are widely favored for their lightweight,high strength and superior impact mitigation capabilities in blast mitigation and transportation safety applications.Their application in large-scale,high-energy rockfall protection remains limited due to their relatively low volumetric energy absorption efficiency and the complex fabrication processes of key energy-absorbing components.To address these limitations,this study proposes a novel sandwich structure incorporating mild steel tubes as core energy absorbers to efficiently mitigate highenergy rockfall impacts.A finite element model was developed in LS-DYNA to systematically investigate the deformation and energy absorption behaviors.Comprehensive parametric analyses were conducted to quantify the effects of key design variables,including tube wall thickness,tube spacing(number of tubes),and infill materials.The results demonstrate that increasing tube wall thickness significantly enhances ultimate energy absorption,with 12-mm-thick tubes absorbing 2.2 times more energy than 6-mm-thick tubes.Lateral constraints induced by adjacent tubes improve specific energy absorption per unit displacement by approximately 30%-45%.Furthermore,incorporating infill materials considerably enhances energy absorption,with aluminum foam infills achieving an 81%increase compared to empty tubes.Nevertheless,higher energy absorption capacity typically leads to greater peak impact forces,increasing the number of tubes offers a better balance between energy absorption and impact force,optimizing the structural performance.These findings provide valuable theoretical insights and practical guidelines for designing sandwich structures in civil and infrastructure engineering applications for effective rockfall protection.展开更多
Low-velocity impact tests are carried out to explore the energy absorption characteristics of bio-inspired lattices,mimicking the architecture of the marine sponge organism Euplectella aspergillum.These sea sponge-ins...Low-velocity impact tests are carried out to explore the energy absorption characteristics of bio-inspired lattices,mimicking the architecture of the marine sponge organism Euplectella aspergillum.These sea sponge-inspired lattice structures feature a square-grid 2D lattice with double diagonal bracings and are additively manufactured via digital light processing(DLP).The collapse strength and energy absorption capacity of sea sponge lattice structures are evaluated under various impact conditions and are compared to those of their constituent square-grid and double diagonal lattices.This study demonstrates that sea sponge lattices can achieve an 11-fold increase in energy absorption compared to the square-grid lattice,due to the stabilizing effect of the double diagonal bracings prompting the structure to collapse layer-bylayer under impact.By adjusting the thickness ratio in the sea sponge lattice,up to 76.7%increment in energy absorption is attained.It is also shown that sea-sponge lattices outperform well-established energy-absorbing materials of equal weight,such as hexagonal honeycombs,confirming their significant potential for impact mitigation.Additionally,this research highlights the enhancements in energy absorption achieved by adding a small amount(0.015 phr)of Multi-Walled Carbon Nanotubes(MWCNTs)to the photocurable resin,thus unlocking new possibilities for the design of innovative lightweight structures with multifunctional attributes.展开更多
To elucidate the effect of calcite-regulated activated carbon(AC)structure on low-temperature denitrification performance of SCR catalysts,this work prepared a series of Mn-Ce/De-AC-xCaCO_(3)(x is the calcite content ...To elucidate the effect of calcite-regulated activated carbon(AC)structure on low-temperature denitrification performance of SCR catalysts,this work prepared a series of Mn-Ce/De-AC-xCaCO_(3)(x is the calcite content in coal)catalysts were prepared by the incipient wetness impregnation method,followed by acid washing to remove calcium-containing minerals.Comprehensive characterization and low-temperature denitrification tests revealed that calcite-induced structural modulation of coal-derived AC significantly enhances catalytic activity.Specifically,NO conversion increased from 88.3%of Mn-Ce/De-AC to 91.7%of Mn-Ce/De-AC-1CaCO_(3)(210℃).The improved SCR denitrification activity results from the enhancement of physicochemical properties including higher Mn^(4+)content and Ce^(4+)/Ce^(3+)ratio,an abundance of chemisorbed oxygen and acidic sites,which could strengthen the SCR reaction pathways(richer NH_(3)activated species and bidentate nitrate active species).Therefore,NO removal is enhanced.展开更多
Anchovies are key forage species in coastal and pelagic food webs,playing crucial ecological and commercial roles in marine ecosystems.Encrasicholina punctifer is a commercially and ecologically important species,yet ...Anchovies are key forage species in coastal and pelagic food webs,playing crucial ecological and commercial roles in marine ecosystems.Encrasicholina punctifer is a commercially and ecologically important species,yet little is known about its osteological development characteristics.Understanding these ontogenetic patterns is essential for explaining phylogenetic relationships within Clupeiformes,informing larval identification in ichthyoplankton surveys,and enhancing aquaculture practices.This study describes the ontogenetic characteristics of the appendicular and median skeletons and fin supports in E.punctifer larvae and juveniles,providing quantitative ontogenetic timelines to address gaps in engraulid developmental biology and contribute to teleost ontogeny research.Larval and juvenile specimens of E.punctifer;size range:3.00-34.56 mm standard length(SL)and notochord length(NL)collected from the Philippine Sea were processed using the standard Alizarin red and Alcian blue clearing-and-staining technique to differentiate ossified and cartilaginous elements.Specimens were examined under a stereo microscope and imaged with an HTC1600ISP digital camera for detailed morphological analysis of skeletal structures.Caudal complex development was evident by 5.55 mm NL,with the initial appearance of cartilaginous hypurals 1–2 and parhypural,followed by Hy3–5 at 6.08 mm NL.Cartilaginous Hy6 was visible by 9.58 mm SL in postflexion larvae.Six hypural bones were present from the postflexion to juvenile stage.Principal fin rays formed via intramembranous ossification at 6.32 mm NL,and segmentation was evident by 10.24 mm SL.Neural arch 1 appeared at 7.38 mm NL,preceding full haemal arch development.Uroneurals 1–2 and ural centra ossified by 9.58 mm SL,with Hy5 detached from U1 at 10.24 mm SL.Preural centra ossified before the arches.Epurals 1 and 2 were evident by 10.24 mm SL.Dorsal fin proximal radials developed anteriorly and distal radials posteriorly.Pectoral fin development initiated with an ossified cleithrum and the coracoscapular cartilage at 5.25 mm NL.By 10.24 mm SL,cartilaginous neural and haemal arches and spines were distinct.Uroneural 1 initially develops as cartilage.The formation of a pleurostyle aligns with clupeoid fish skeletal ontogeny.Dorsal and anal fin development follows a distinctive pattern,with variability in fin support development.Our results reveal accelerated caudal complex formation in E.punctifer and contribute new knowledge on the osteological characteristics of the genus Encrasicholina,and aid in understanding larval and juvenile ontogeny of marine teleosts.展开更多
In modern ZnO varistors,traditional aging mechanisms based on increased power consumption are no longer relevant due to reduced power consumption during DC aging.Prolonged exposure to both AC and DC voltages results i...In modern ZnO varistors,traditional aging mechanisms based on increased power consumption are no longer relevant due to reduced power consumption during DC aging.Prolonged exposure to both AC and DC voltages results in increased leakage current,decreased breakdown voltage,and lower nonlinearity,ultimately compromising their protective performance.To investigate the evolution in electrical properties during DC aging,this work developed a finite element model based on Voronoi networks and conducted accelerated aging tests on commercial varistors.Throughout the aging process,current-voltage characteristics and Schottky barrier parameters were measured and analyzed.The results indicate that when subjected to constant voltage,current flows through regions with larger grain sizes,forming discharge channels.As aging progresses,the current focus increases on these channels,leading to a decline in the varistor’s overall performance.Furthermore,analysis of the Schottky barrier parameters shows that the changes in electrical performance during aging are non-monotonic.These findings offer theoretical support for understanding the aging mechanisms and condition assessment of modern stable ZnO varistors.展开更多
Abuse of chloramphenicol(CAP)could cause serious side effects to human health.Therefore,it is necessary to detect CAP residues in animal sourced food effectively.Here,the superiority(better stability,higher Apt-CAP lo...Abuse of chloramphenicol(CAP)could cause serious side effects to human health.Therefore,it is necessary to detect CAP residues in animal sourced food effectively.Here,the superiority(better stability,higher Apt-CAP loading efficiency,and higher CAP binding associated conformational change,etc.)of tetrahedral structure to double-chained structure for developing aptasensor was evaluated.Then,a self-assembled DNA tetrahedral structure-based electrochemical aptasensor targeting CAP was developed.Under the optimized conditions,the aptasensor exhibited high sensitivity toward CAP with a limit of detection(LOD)of 0.0676 ng/m L(linear range 0.19-387.76 ng/m L),and high selectivity against the structural analogs of CAP.Moreover,the recovery rate of CAP from spiked milk samples ranged from 100.57%to 101.69%,and only USD 1.34 is needed for detecting CAP in 1 sample.These results suggested the application potential of this aptasesor for detecting CAP in animal sourced foods.展开更多
基金Project supported by the National Natural Science Foun-dation of China(Grant No.62373197)the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province,China(Grant No.23KJB120010)+1 种基金the Industry-University-Research Cooperation Project of Jiangsu Province,China(Grant No.BY20251038)the Cultivation and In-cubation Project of the College of Automation,Nanjing Uni-versity of Posts and Telecommunications.
文摘Multilayer complex dynamical networks,characterized by the intricate topological connections and diverse hierarchical structures,present significant challenges in determining complete structural configurations due to the unique functional attributes and interaction patterns inherent to different layers.This paper addresses the critical question of whether structural information from a known layer can be used to reconstruct the unknown intralayer structure of a target layer within general weighted output-coupling multilayer networks.Building upon the generalized synchronization principle,we propose an innovative reconstruction method that incorporates two essential components in the design of structure observers,the cross-layer coupling modulator and the structural divergence term.A key advantage of the proposed reconstruction method lies in its flexibility to freely designate both the unknown target layer and the known reference layer from the general weighted output-coupling multilayer network.The reduced dependency on full-state observability enables more deployment in engineering applications with partial measurements.Numerical simulations are conducted to validate the effectiveness of the proposed structure reconstruction method.
基金supported by the National Natural Science Foundation of China(Nos.52231007,51872238,52074227,and 21806129)the Fundamental Research Funds for the Central Universities(Nos.3102018zy045,3102019AX11,and 5000220455)the Natural Science Basic Research Plan in Shaanxi Province of China(Nos.2017JQ5116 and 2020JM-118).
文摘The emergence of precision electronic devices and wearable electronic products urgently requires high-performance multifunctional electromagnetic wave(EMW)absorbers to meet the applicability and versatility in various applications.Herein,a dual-network(DN)gel was successfully prepared using acrylamide and sodium lignosulphonate as the basic units by simple chemical cross-linking and physical cross-linking methods.Specifically,the hydrogel forms two types of cross-linking networks through metal coordination and hydrogen bonding.Benefiting from the combined effects of dipole polarization and conductivity loss,the gel achieves an effective absorption bandwidth(EAB)of 6.74 GHz at a thickness of only 1.89 mm,demonstrating excellent EMW absorption performance.In addition,this unique structural configuration endows the EMW absorber with multifunctional features,such as remarkable tensile strength,good environmental compatibility,ultraviolet(UV)resistance,and excellent adhesion.Integrating multiple functional features into the EMW gels displays a broad application prospect in a variety of application scenarios.This research reveals the significance of DN structure design in the electromagnetic wave absorption(EWA)performance of gel-based materials,providing a substantial foundation for the multifunctional design of gel-based absorbers.
基金the financial support provided by the National Natural Science Foundation of China(grant no.22373032)the open research fund of Songshan Lake Materials Laboratory(grant no.2023SLABFK06)。
文摘With the rapid growth of technologies requiring high-power energy storage,achieving long-term cyclic stability under ultra-high current density is a key challenge.Aqueous zinc-ion batteries(AZIBs)are promising candidates due to their intrinsic safety and low cost,but they suffer from severe interfacial instability at rates exceeding 10 mA cm^(-2),which drastically shortens their cycle life.Inspired by theoretical calculations,triglyme(TGDE)additive with strong electron-donating groups into Zn(OTf)_(2) electrolytes effectively disrupts the hydrogen-bond network among free water molecules,while the weak coordination of TGDE with Zn^(2+)promotes the entry of OTf-into the primary Zn^(2+)solvated sheath,thus decreasing the coordination number of water with Zn^(2+).As such,the hydrogen-bond network and the bulk solvated structure are reconstructed with better stability.Moreover,the strong adsorption of TGDE lying on the Zn(002)surface would induce Zn depositions along(002)together with the reduced exposed surface,further effectively inhibiting side reactions.Likewise,TGDE electrolyte induces the formation of such ZnF_(2)-ZnS dual-layer solid electrolyte interface(SEI)with superior chemical stability and ionic conductivity,thereby regulating Zn^(2+)flux with dendrite-free depositions.Based on this electrolyte,Zn‖Zn cells can be stably cycled for 1300 h at a limit of 10 mA cm^(-2) and 10 mAh cm^(-2).The assembled Zn‖V_(2)O_(5) full cells still maintain 99.9%capacity retention after 1000 cycles at 10 A g^(-1).This work provides a feasible approach for designing aqueous electrolytes to reconstruct the hydrogen-bond network and solvated structure,which can be extended to the applications of high-rate and high-temperature scenarios.
基金Supported by the National Key Research Program(No.2024-1129-954-112)National Natural Science Foundation of China(No.52372033)Guangxi Science and Technology Major Program(No.AA24263054)。
文摘Alkali-free SiO_(2)-Al_(2)O_(3)-CaO-MgO with different SiO_(2)/Al_(2)O_(3)mass ratios was prepared by conventional melt quenching method.The glass network structure,thermodynamic properties and elastic modulus changes with SiO_(2)and Al_(2)O_(3)ratios were investigated using various techniques.It is found that when SiO_(2)is replaced by Al_(2)O_(3),the Q^(4) to Q^(3) transition of silicon-oxygen network decreases while the aluminum-oxygen network increases,which result in the transformation of Si-O-Si bonds to Si-O-Al bonds and an increase in glass network connectivity even though the intermolecular bond strength decreases.The glass transition temperature(T_(g))increases continuously,while the thermal expansion coefficient increases and high-temperature viscosity first decreases and then increases.Meanwhile,the elastic modulus values increase from 93 to 102 GPa.This indicates that the elastic modulus is mainly affected by packing factor and dissociation energy,and elements with higher packing factors and dissociation energies supplant those with lower values,resulting in increased rigidity within the glass.
基金supported by the National Natural Science Foundation of China(Nos.12422207 and 12372199).
文摘An efficient data-driven numerical framework is developed for transient heat conduction analysis in thin-walled structures.The proposed approach integrates spectral time discretization with neural network approximation,forming a spectral-integrated neural network(SINN)scheme tailored for problems characterized by long-time evolution.Temporal derivatives are treated through a spectral integration strategy based on orthogonal polynomial expansions,which significantly alleviates stability constraints associated with conventional time-marching schemes.A fully connected neural network is employed to approximate the temperature-related variables,while governing equa-tions and boundary conditions are enforced through a physics-informed loss formulation.Numerical investigations demonstrate that the proposed method maintains high accuracy even when large time steps are adopted,where standard numerical solvers often suffer from instability or excessive computational cost.Moreover,the framework exhibits strong robustness for ultrathin configurations with extreme aspect ratios,achieving relative errors on the order of 10−5 or lower.These results indicate that the SINN framework provides a reliable and efficient alternative for transient thermal analysis of thin-walled structures under challenging computational conditions.
基金supported by the National Natural Science Foundation of China(No.52308332)the General Scientific Research Project of the Education Department of Zhejiang Province(No.Y202455824).
文摘This research centers on structural health monitoring of bridges,a critical transportation infrastructure.Owing to the cumulative action of heavy vehicle loads,environmental variations,and material aging,bridge components are prone to cracks and other defects,severely compromising structural safety and service life.Traditional inspection methods relying on manual visual assessment or vehicle-mounted sensors suffer from low efficiency,strong subjectivity,and high costs,while conventional image processing techniques and early deep learning models(e.g.,UNet,Faster R-CNN)still performinadequately in complex environments(e.g.,varying illumination,noise,false cracks)due to poor perception of fine cracks andmulti-scale features,limiting practical application.To address these challenges,this paper proposes CACNN-Net(CBAM-Augmented CNN),a novel dual-encoder architecture that innovatively couples a CNN for local detail extraction with a CBAM-Transformer for global context modeling.A key contribution is the dedicated Feature FusionModule(FFM),which strategically integratesmulti-scale features and focuses attention on crack regions while suppressing irrelevant noise.Experiments on bridge crack datasets demonstrate that CACNNNet achieves a precision of 77.6%,a recall of 79.4%,and an mIoU of 62.7%.These results significantly outperform several typical models(e.g.,UNet-ResNet34,Deeplabv3),confirming their superior accuracy and robust generalization,providing a high-precision automated solution for bridge crack detection and a novel network design paradigm for structural surface defect identification in complex scenarios,while future research may integrate physical features like depth information to advance intelligent infrastructure maintenance and digital twin management.
基金founded by the Ministry of Science and Higher Education of the Russian Federation,State assignments for research,registration No.1024032600084-8-1.3.2Study of the grain growth and the formation of polycrystalline structure as a result of phase transition(Section 6)was founded by the Russian Science Foundation,Project No.24-71-00078+3 种基金https://rscf.ru/en/project/24-71-00078/(accessed on 01 December 2025).Study of the orientation dependence of the phase transition of aluminum in Section 3 was founded by the Russian Science Foundation,Project No.24-19-00684https://rscf.ru/en/project/24-19-00684/(accessed on 01 December 2025).
文摘It is well known that aluminum and copper exhibit structural phase transformations in quasi-static and dynamic measurements,including shock wave loading.However,the dependence of phase transformations in a wide range of crystallographic directions of shock loading has not been revealed.In this work,we calculated the shock Hugoniot for aluminum and copper in different crystallographic directions([100],[110],[111],[112],[102],[114],[123],[134],[221]and[401])of shock compression using molecular dynamics(MD)simulations.The results showed a high pressure(>160 GPa for Cu and>40 GPa for Al)of the FCC-to-BCC transition.In copper,different characteristics of the phase transition are observed depending on the loading direction with the[100]compression direction being the weakest.The FCC-to-BCC transition for copper is in the range of 150–220 GPa,which is consistent with the existing experimental data.Due to the high transition pressure,the BCC phase transition in copper competes with melting.In aluminum,the FCC-to-BCC transition is observed for all studied directions at pressures between 40 and 50 GPa far beyond the melting.In all considered cases we observe the coexistence of HCP and BCC phases during the FCC-to-BCC transition,which is consistent with the experimental data and atomistic calculations;this HCP phase forms in the course of accompanying plastic deformation with dislocation activity in the parent FCC phase.The plasticity incipience is also anisotropic in bothmetals,which is due to the difference in the projections of stress on the slip plane for different orientations of the FCC crystal.MD modeling results demonstrate a strong dependence of the FCC-to-BCC transition on the crystallographic direction,in which the material is loaded in the copper crystals.However,MD simulations data can only be obtained for specific points in the stereographic direction space;therefore,for more comprehensive understanding of the phase transition process,a feed-forward neural network was trained using MD modeling data.The trained machine learning model allowed us to construct continuous stereographic maps of phase transitions as a function of stress in the shock-compressed state of metal.Due to appearance and growth of multiple centers of new phase,the FCC-to-BCC transition leads to formation of a polycrystalline structure from the parent single crystal.
文摘Six new lanthanide complexes:[Ln(3,4-DEOBA)3(4,4'-DM-2,2'-bipy)]2·2C_(2)H_(5)OH,[Ln=Dy(1),Eu(2),Tb(3),Sm(4),Ho(5),Gd(6);3,4-DEOBA-=3,4-diethoxybenzoate,4,4'-DM-2,2'-bipy=4,4'-dimethyl-2,2'-bipyridine]were successfully synthesized by the volatilization of the solution at room temperature.The crystal structures of six complexes were determined by single-crystal X-ray diffraction technology.The results showed that the complexes all have a binuclear structure,and the structures contain free ethanol molecules.Moreover,the coordination number of the central metal of each structural unit is eight.Adjacent structural units interact with each other through hydrogen bonds and further expand to form 1D chain-like and 2D planar structures.After conducting a systematic study on the luminescence properties of complexes 1-4,their emission and excitation spectra were obtained.Experimental results indicated that the fluorescence lifetimes of complexes 2 and 3 were 0.807 and 0.845 ms,respectively.The emission spectral data of complexes 1-4 were imported into the CIE chromaticity coordinate system,and their corre sponding luminescent regions cover the yellow light,red light,green light,and orange-red light bands,respectively.Within the temperature range of 299.15-1300 K,the thermal decomposition processes of the six complexes were comprehensively analyzed by using TG-DSC/FTIR/MS technology.The hypothesis of the gradual loss of ligand groups during the decomposition process was verified by detecting the escaped gas,3D infrared spectroscopy,and ion fragment information detected by mass spectrometry.The specific decomposition path is as follows:firstly,free ethanol molecules and neutral ligands are removed,and finally,acidic ligands are released;the final product is the corresponding metal oxide.CCDC:2430420,1;2430422,2;2430419,3;2430424,4;2430421,5;2430423,6.
基金Supported by the National Key Research and Development Program of Traditional Chinese Medicine Modernization Project,China(No.2023YFC3504000)the Science and Technology Development Project of Jilin Province,China(No.20240404043ZP)the Science and Technology Innovation Cooperation Project of Changchun Science and Technology Bureau and Chinese Academy of Sciences,China(No.23SH14)。
文摘In this study,a novel polysaccharide GPA-G 2-H was derived from ginseng.Furthermore,the coherent study of its structural characteristics,fermented characteristics in vitro,as well as antioxidant mechanism of fermented product FGPA-G 2-H on Aβ25-35-induced PC 12 cells were explored.The structure of GPA-G 2-H was determined by means of zeta potential analysis,FTIR,HPLC,XRD,GC-MS and NMR.The backbone of GPA-G 2-H was mainly composed of→4)-α-D-Glcp-(1→with branches substituted at O-3.Notably,GPA-G 2-H was degraded by intestinal microbiota in vitro with total sugar content and pH value decreasing,and short-chain fatty acids(SCFAs)increasing.Moreover,GPA-G 2-H significantly promoted the proliferation of Lactobacillus,Muribaculaceae and Weissella,thereby making positive alterations in intestinal microbiota composition.Additionally,FGPA-G 2-H activated the Nrf 2/HO-1 signaling pathway,enhanced HO-1,NQO 1,SOD and GSH-Px,while inhabited Keap 1,MDA and LDH,which alleviated Aβ-induced oxidative stress in PC 12 cells.These provide a solid theoretical basis for the further development of ginseng polysaccharides as functional food and antioxidant drugs.
文摘Optimizing routing and resource allocation in decentralized unmanned aerial vehicle(UAV)networks remains challenging due to interference and rapidly changing topologies.The authors introduce a novel framework combining double deep Q-networks(DDQNs)and graph neural networks(GNNs)for joint routing and resource allocation.The framework uses GNNs to model the network topology and DDQNs to adaptively control routing and resource allocation,addressing interference and improving network performance.Simulation results show that the proposed approach outperforms traditional methods such as Closest-to-Destination(c2Dst),Max-SINR(mSINR),and Multi-Layer Perceptron(MLP)-based models,achieving approximately 23.5% improvement in throughput,50% increase in connection probability,and 17.6% reduction in number of hops,demonstrating its effectiveness in dynamic UAV networks.
文摘To explore the material basis and mechanisms of the anti-inflammatory effects of Hibiscus mutabilis L..The active ingredients and potential targets of Hibiscus mutabilis L.were obtained through the literature review and SwissADME platform.Genes related to the inflammation were collected using Genecards and OMIM databases,and the intersection genes were submitted on STRING and DAVID websites.Then,the protein interaction network(PPI),gene ontology(GO)and pathway(KEGG)were analyzed.Cytoscape 3.7.2 software was used to construct the“Hibiscus mutabilis L.-active ingredient-target-inflammation”network diagram,and AutoDockTools-1.5.6 software was used for the molecular docking verification.The antiinflammatory effect of Hibiscus mutabilis L.active ingredient was verified by the RAW264.7 inflammatory cell model.The results showed that 11 active components and 94 potential targets,1029 inflammatory targets and 24 intersection targets were obtained from Hibiscus mutabilis L..The key anti-inflammatory active ingredients of Hibiscus mutabilis L.are quercetin,apigenin and luteolin.Its action pathway is mainly related to NF-κB,cancer pathway and TNF signaling pathway.Cell experiments showed that total flavonoids of Hibiscus mutabilis L.could effectively inhibit the expression of tumor necrosis factor(TNF-α),interleukin 8(IL-8)and epidermal growth factor receptor(EGFR)in LPS-induced RAW 264.7 inflammatory cells.It also downregulates the phosphorylation of human nuclear factor ĸB inhibitory protein α(IĸBα)and NF-κB p65 subunit protein(p65).Overall,the anti-inflammatory effect of Hibiscus mutabilis L.is related to many active components,many signal pathways and targets,which provides a theoretical basis for its further development and application.
基金supported by the National Natural Science Foundation of China(Grant Nos.12432005 and 12472116)the Fundamental Research Funds for the Central Universities(DUTZD25240).
文摘Conformal truss-like lattice structures face significant manufacturability challenges in additive manufac-turing due to overhang angle limitations.To address this problem,we propose a novel angle-constrained optimization method grounded in the global adjustment of nodal coordinates.First,a build direction is selected to minimize the number of violating struts.Then,an angular-constraint matrix is assembled from strut direction vectors,and analytical sensitivities with respect to nodal coordinates are derived to enable efficient constrained optimization under nonlinear angular inequality constraints.Numerical studies on two complex curved-surface lattices demonstrate that all overhang violations are eliminated while only minor changes are induced in global stiffness and strength.In particular,the maximum displacement of an ergonomic insole varies by only 2.87%after optimization.The results confirm the method’s versatility and engineering robustness,providing a practical approach for additive manufacturing-oriented lattice structure design.
文摘Identifying the community structure of complex networks is crucial to extracting insights and understanding network properties.Although several community detection methods have been proposed,many are unsuitable for social networks due to significant limitations.Specifically,most approaches depend mainly on user-user structural links while overlooking service-centric,semantic,and multi-attribute drivers of community formation,and they also lack flexible filtering mechanisms for large-scale,service-oriented settings.Our proposed approach,called community discovery-based service(CDBS),leverages user profiles and their interactions with consulted web services.The method introduces a novel similarity measure,global similarity interaction profile(GSIP),which goes beyond typical similarity measures by unifying user and service profiles for all attributes types into a coherent representation,thereby clarifying its novelty and contribution.It applies multiple filtering criteria related to user attributes,accessed services,and interaction patterns.Experimental comparisons against Louvain,Hierarchical Agglomerative Clustering,Label Propagation and Infomap show that CDBS reveals the higher performance as it achieves 0.74 modularity,0.13 conductance,0.77 coverage,and significantly fast response time of 9.8 s,even with 10,000 users and 400 services.Moreover,community discoverybased service consistently detects a larger number of communities with distinct topics of interest,underscoring its capacity to generate detailed and efficient structures in complex networks.These results confirm both the efficiency and effectiveness of the proposed method.Beyond controlled evaluation,communities discovery based service is applicable to targeted recommendations,group-oriented marketing,access control,and service personalization,where communities are shaped not only by user links but also by service engagement.
基金supported by the Research year project of the KongjuNational University in 2025 and the Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.RS-2024-00444170,Research and International Collaboration on Trust Model-Based Intelligent Incident Response Technologies in 6G Open Network Environment).
文摘With the growing complexity and decentralization of network systems,the attack surface has expanded,which has led to greater concerns over network threats.In this context,artificial intelligence(AI)-based network intrusion detection systems(NIDS)have been extensively studied,and recent efforts have shifted toward integrating distributed learning to enable intelligent and scalable detection mechanisms.However,most existing works focus on individual distributed learning frameworks,and there is a lack of systematic evaluations that compare different algorithms under consistent conditions.In this paper,we present a comprehensive evaluation of representative distributed learning frameworks—Federated Learning(FL),Split Learning(SL),hybrid collaborative learning(SFL),and fully distributed learning—in the context of AI-driven NIDS.Using recent benchmark intrusion detection datasets,a unified model backbone,and controlled distributed scenarios,we assess these frameworks across multiple criteria,including detection performance,communication cost,computational efficiency,and convergence behavior.Our findings highlight distinct trade-offs among the distributed learning frameworks,demonstrating that the optimal choice depends strongly on systemconstraints such as bandwidth availability,node resources,and data distribution.This work provides the first holistic analysis of distributed learning approaches for AI-driven NIDS and offers practical guidelines for designing secure and efficient intrusion detection systems in decentralized environments.
基金supported by the National Key R&D Program of China(Grant No.2019YFC1509703)the Tianjin Science and Technology Program Project(Grant No.23YFYSHZ00130)。
文摘Sandwich structures are widely favored for their lightweight,high strength and superior impact mitigation capabilities in blast mitigation and transportation safety applications.Their application in large-scale,high-energy rockfall protection remains limited due to their relatively low volumetric energy absorption efficiency and the complex fabrication processes of key energy-absorbing components.To address these limitations,this study proposes a novel sandwich structure incorporating mild steel tubes as core energy absorbers to efficiently mitigate highenergy rockfall impacts.A finite element model was developed in LS-DYNA to systematically investigate the deformation and energy absorption behaviors.Comprehensive parametric analyses were conducted to quantify the effects of key design variables,including tube wall thickness,tube spacing(number of tubes),and infill materials.The results demonstrate that increasing tube wall thickness significantly enhances ultimate energy absorption,with 12-mm-thick tubes absorbing 2.2 times more energy than 6-mm-thick tubes.Lateral constraints induced by adjacent tubes improve specific energy absorption per unit displacement by approximately 30%-45%.Furthermore,incorporating infill materials considerably enhances energy absorption,with aluminum foam infills achieving an 81%increase compared to empty tubes.Nevertheless,higher energy absorption capacity typically leads to greater peak impact forces,increasing the number of tubes offers a better balance between energy absorption and impact force,optimizing the structural performance.These findings provide valuable theoretical insights and practical guidelines for designing sandwich structures in civil and infrastructure engineering applications for effective rockfall protection.
基金supported by the Khalifa University of Science and Technology internal grants(Nos.2021-CIRA-109,2020-CIRA-007,and 2020-CIRA-024).
文摘Low-velocity impact tests are carried out to explore the energy absorption characteristics of bio-inspired lattices,mimicking the architecture of the marine sponge organism Euplectella aspergillum.These sea sponge-inspired lattice structures feature a square-grid 2D lattice with double diagonal bracings and are additively manufactured via digital light processing(DLP).The collapse strength and energy absorption capacity of sea sponge lattice structures are evaluated under various impact conditions and are compared to those of their constituent square-grid and double diagonal lattices.This study demonstrates that sea sponge lattices can achieve an 11-fold increase in energy absorption compared to the square-grid lattice,due to the stabilizing effect of the double diagonal bracings prompting the structure to collapse layer-bylayer under impact.By adjusting the thickness ratio in the sea sponge lattice,up to 76.7%increment in energy absorption is attained.It is also shown that sea-sponge lattices outperform well-established energy-absorbing materials of equal weight,such as hexagonal honeycombs,confirming their significant potential for impact mitigation.Additionally,this research highlights the enhancements in energy absorption achieved by adding a small amount(0.015 phr)of Multi-Walled Carbon Nanotubes(MWCNTs)to the photocurable resin,thus unlocking new possibilities for the design of innovative lightweight structures with multifunctional attributes.
基金Supported by the Science and Technology Cooperation and Exchange special project of Cooperation of Shanxi Province(202404041101014)the Fundamental Research Program of Shanxi Province(202403021212333)+3 种基金the Joint Funds of the National Natural Science Foundation of China(U24A20555)the Lvliang Key R&D of University-Local Cooperation(2023XDHZ10)the Initiation Fund for Doctoral Research of Taiyuan University of Science and Technology(20242026)the Outstanding Doctor Funding Award of Shanxi Province(20242080).
文摘To elucidate the effect of calcite-regulated activated carbon(AC)structure on low-temperature denitrification performance of SCR catalysts,this work prepared a series of Mn-Ce/De-AC-xCaCO_(3)(x is the calcite content in coal)catalysts were prepared by the incipient wetness impregnation method,followed by acid washing to remove calcium-containing minerals.Comprehensive characterization and low-temperature denitrification tests revealed that calcite-induced structural modulation of coal-derived AC significantly enhances catalytic activity.Specifically,NO conversion increased from 88.3%of Mn-Ce/De-AC to 91.7%of Mn-Ce/De-AC-1CaCO_(3)(210℃).The improved SCR denitrification activity results from the enhancement of physicochemical properties including higher Mn^(4+)content and Ce^(4+)/Ce^(3+)ratio,an abundance of chemisorbed oxygen and acidic sites,which could strengthen the SCR reaction pathways(richer NH_(3)activated species and bidentate nitrate active species).Therefore,NO removal is enhanced.
文摘Anchovies are key forage species in coastal and pelagic food webs,playing crucial ecological and commercial roles in marine ecosystems.Encrasicholina punctifer is a commercially and ecologically important species,yet little is known about its osteological development characteristics.Understanding these ontogenetic patterns is essential for explaining phylogenetic relationships within Clupeiformes,informing larval identification in ichthyoplankton surveys,and enhancing aquaculture practices.This study describes the ontogenetic characteristics of the appendicular and median skeletons and fin supports in E.punctifer larvae and juveniles,providing quantitative ontogenetic timelines to address gaps in engraulid developmental biology and contribute to teleost ontogeny research.Larval and juvenile specimens of E.punctifer;size range:3.00-34.56 mm standard length(SL)and notochord length(NL)collected from the Philippine Sea were processed using the standard Alizarin red and Alcian blue clearing-and-staining technique to differentiate ossified and cartilaginous elements.Specimens were examined under a stereo microscope and imaged with an HTC1600ISP digital camera for detailed morphological analysis of skeletal structures.Caudal complex development was evident by 5.55 mm NL,with the initial appearance of cartilaginous hypurals 1–2 and parhypural,followed by Hy3–5 at 6.08 mm NL.Cartilaginous Hy6 was visible by 9.58 mm SL in postflexion larvae.Six hypural bones were present from the postflexion to juvenile stage.Principal fin rays formed via intramembranous ossification at 6.32 mm NL,and segmentation was evident by 10.24 mm SL.Neural arch 1 appeared at 7.38 mm NL,preceding full haemal arch development.Uroneurals 1–2 and ural centra ossified by 9.58 mm SL,with Hy5 detached from U1 at 10.24 mm SL.Preural centra ossified before the arches.Epurals 1 and 2 were evident by 10.24 mm SL.Dorsal fin proximal radials developed anteriorly and distal radials posteriorly.Pectoral fin development initiated with an ossified cleithrum and the coracoscapular cartilage at 5.25 mm NL.By 10.24 mm SL,cartilaginous neural and haemal arches and spines were distinct.Uroneural 1 initially develops as cartilage.The formation of a pleurostyle aligns with clupeoid fish skeletal ontogeny.Dorsal and anal fin development follows a distinctive pattern,with variability in fin support development.Our results reveal accelerated caudal complex formation in E.punctifer and contribute new knowledge on the osteological characteristics of the genus Encrasicholina,and aid in understanding larval and juvenile ontogeny of marine teleosts.
文摘In modern ZnO varistors,traditional aging mechanisms based on increased power consumption are no longer relevant due to reduced power consumption during DC aging.Prolonged exposure to both AC and DC voltages results in increased leakage current,decreased breakdown voltage,and lower nonlinearity,ultimately compromising their protective performance.To investigate the evolution in electrical properties during DC aging,this work developed a finite element model based on Voronoi networks and conducted accelerated aging tests on commercial varistors.Throughout the aging process,current-voltage characteristics and Schottky barrier parameters were measured and analyzed.The results indicate that when subjected to constant voltage,current flows through regions with larger grain sizes,forming discharge channels.As aging progresses,the current focus increases on these channels,leading to a decline in the varistor’s overall performance.Furthermore,analysis of the Schottky barrier parameters shows that the changes in electrical performance during aging are non-monotonic.These findings offer theoretical support for understanding the aging mechanisms and condition assessment of modern stable ZnO varistors.
基金supported by the National Nature Science Foundation of China(82174531)the Medicine and Health Science Technology Development Project of Shandong Province,China(202212060626).
文摘Abuse of chloramphenicol(CAP)could cause serious side effects to human health.Therefore,it is necessary to detect CAP residues in animal sourced food effectively.Here,the superiority(better stability,higher Apt-CAP loading efficiency,and higher CAP binding associated conformational change,etc.)of tetrahedral structure to double-chained structure for developing aptasensor was evaluated.Then,a self-assembled DNA tetrahedral structure-based electrochemical aptasensor targeting CAP was developed.Under the optimized conditions,the aptasensor exhibited high sensitivity toward CAP with a limit of detection(LOD)of 0.0676 ng/m L(linear range 0.19-387.76 ng/m L),and high selectivity against the structural analogs of CAP.Moreover,the recovery rate of CAP from spiked milk samples ranged from 100.57%to 101.69%,and only USD 1.34 is needed for detecting CAP in 1 sample.These results suggested the application potential of this aptasesor for detecting CAP in animal sourced foods.
