Natural hybridization is known to play a vital role in speciation;however,the mechanisms underlying the early stages of natural hybridization remain unclear.Where two plant species come into contact,two driving forces...Natural hybridization is known to play a vital role in speciation;however,the mechanisms underlying the early stages of natural hybridization remain unclear.Where two plant species come into contact,two driving forces may balance the dynamic consequences of hybridization:fusion by hybridization-mediated gene flow,and separation by reproductive isolation(RI)(Ma et al.,2010a,b;Chang et al.,2022).展开更多
One approach to understand the importance of reproductive barriers to the speciation process is to study the break- down of barriers between formerly distinct species. One reproductive barrier, sexual isolation, reduc...One approach to understand the importance of reproductive barriers to the speciation process is to study the break- down of barriers between formerly distinct species. One reproductive barrier, sexual isolation, reduces gene flow between species through differences in mate preferences and mating signals and is likely important for species formation and maintenance. We measure sexual isolation in two limnetic-benthic threespine stickleback species pairs （Gasterosteus spp.）. One species pair main- tains strong reproductive isolation while the other species pair has recently collapsed into a hybrid swarm. We compare the strength of sexual isolation in the hybridizing pair to the currently isolated pair. We provide the first evidence that sexual isolation has been lost in the hybridizing pair and show furthermore that preferences females have for conspecific mates and the traits they use to distinguish conspecific and heterospecific males contribute to this loss. This work highlights the fragility of reproductive isolation between young species pairs and considers the role of sexual isolation in speciation [Current Zoology 59 （5）： 591-603, 2013].展开更多
Many studies on fiber reinforced polymer composite bars, as a substitute for reinforcing bars, have been conducted to solve corrosion of steel in reinforced concrete structures since 1960s’. However, FRP Bars have a ...Many studies on fiber reinforced polymer composite bars, as a substitute for reinforcing bars, have been conducted to solve corrosion of steel in reinforced concrete structures since 1960s’. However, FRP Bars have a lower elastic modulus than steel rebar as a structural component of concrete structures. Material properties with brittleness fracture and low elastic modulus can be improved by combining cheaper steel than carbon or aramid fibers. In this study, prototypes of FRP Bars with inserted steel wires (i.e., “FRP Hybrid Bars”) were developed and their tensile performance was compared depending on the proportion and diameter of steel. The FRP Hybrid Bars were made by dividing them into D13 and D16 according to the diameter and proportion of inserted wires: GFRPs were combined with wires having different diameters of 0.5 mm, 1.0 mm, and 2.0 mm in the proportion of 10%, 30%, 50%, and 70%, respectively. As a result of tensile tests, the elastic modulus of FRP Hybrid Bars were improved as 20% - 190% in comparison with the fully GFRP Bars.展开更多
Correlations among behavioral traits can generate trade-offs and constrain phenotypic evolution. Interspecific hybridization has the potential to alter behavioral trait correlations, but the effect of hybridization on...Correlations among behavioral traits can generate trade-offs and constrain phenotypic evolution. Interspecific hybridization has the potential to alter behavioral trait correlations, but the effect of hybridization on suites of behavioral traits has received relatively little attention. We evaluated how natural hybridization changes the relationship between boldness （time of emergence and proportion of time out of shelter） and response to a simulated predator threat in swordtails （Teleostei： Xiphophorus）. In poeciliid fishes, bold individuals have increased survival in the presence of predators. This non-intuitive observation may arise as a result of bold individuals being more likely to engage in anti-predator behaviors. Contrary to our prediction, bold indi- viduals were less likely to perform a fast-start response to a predator threat. This correlation was consistent among populations and species but was only significant in hybrids. The observed correlation between boldness and anti-predator behavior could im- pact hybrid fitness and the evolvability of hybrid lineages. More generally, our findings suggest that hybridization could influence the integration of behavioral phenotypes, as has been amply documented for morphology. Animal personality and behavioral syndromes could therefore play an important role in the evolutionary fate of natural hybrids [Current Zoology 61 （4）： 596-603, 2015].展开更多
The closely related Black-headed Bunting(Emberiza melanocephala,a western Palearctic lineage)and Red-headed Bunting(Emberiza bruniceps,an eastern Palearctic lineage)hybridize and replace each other south of the Caspia...The closely related Black-headed Bunting(Emberiza melanocephala,a western Palearctic lineage)and Red-headed Bunting(Emberiza bruniceps,an eastern Palearctic lineage)hybridize and replace each other south of the Caspian Sea.The parental species have distinct phenotypes and therefore morphology is useful for assessing hybridization in the contact zone.In the years of 1940 and 1977,quite a few hybrids were collected and studied morphologically.Since then,the hybrid zone appears to have expanded westwards,but there has been a time gap in the collection of morphological data.Here we reanalyze bunting specimens morphologically and compare the historical data with recent data.Morphometric and phenotypic traits from three time periods(1940,1977 and recent)were studied to assess phenotypic variation of hybrids,pattern of hybridization,and transgressive traits in the hybrid zone.Our results show that most of the birds in the hybrid zone exhibit intermediate phenotypes(both colors and morphometric characters),ranging from the pure phenotype of either of the parental species.However,hybridization has also produced novel phenotypes not seen in any of the parents.Using a canonical discriminant function analysis,the morphometric characters separated each parental species and the hybrids quite well.Our results showed morphometric intermediacy of hybrids in accordance with phenotypes.We observe a time trend in which recent hybrids are more similar to Red-headed Buntings phenotypically compared to historical samples.This pattern is likely a signature of a westward expansion of the Red-headed Bunting into the breeding range of the Black-headed Bunting.展开更多
FeSiBCuNb/FeNi composite magnetic powder cores(CMPCs)with outstanding high-frequency permeability and low core loss(P_(cv))have been developed by hybridizing HNO 3-passivated Fe_(73.5)Cu_(1)Nb_(3)Si_(13.5)B_(9) nanocr...FeSiBCuNb/FeNi composite magnetic powder cores(CMPCs)with outstanding high-frequency permeability and low core loss(P_(cv))have been developed by hybridizing HNO 3-passivated Fe_(73.5)Cu_(1)Nb_(3)Si_(13.5)B_(9) nanocrystalline powder with finer Fe 50Ni 50 powder.A 7 wt.%HNO 3 passivation treatment forms a Fe_(3)O_(4)-dominant oxidation layer on the nanocrystalline powder surface,which increases its electrical resistivity and reduces the P_(cv) of the power cores.As FeNi content increases from 0 to 40 wt.%,the porosity of the CMPCs decreases consistently,while saturation magnetization(M_(s)),effective permeability(μ_(e)),and P_(cv) gradually enhance.An appropriate increase in compaction pressure further decreases the porosity and leads to enhanced M s,μe,and lowered P_(cv).The CMPC with 40 wt.%FeNi,compacted at 1000 MPa,exhibits the best comprehensive soft magnetic properties with M s,μe,and P_(cv) at 50 mT/200 kHz of 136.3 emu/g,57.4,and 599 mW/cm^(3),respectively.The improved M_(s) andμe result from the reduced porosity combined with the FeNi’s inherently higher M_(s) and μ_(e).The increased high-frequency P_(cv) after FeNi addition mainly arises from the raised eddy loss due to decreased electrical resistivity.The reduced P_(cv) through the optimal compaction pressure is due to the further elimination of pore defects in the CMPCs.展开更多
The high-quality assembly of Large Aircraft Components(LACs)is essential in modern aviation manufacturing.Numerical control locators are employed for the posture adjustment of LAC,yet the system's multi-input mult...The high-quality assembly of Large Aircraft Components(LACs)is essential in modern aviation manufacturing.Numerical control locators are employed for the posture adjustment of LAC,yet the system's multi-input multi-output,nonlinearity,and strong coupling presents significant challenges.The substantial internal force generated during the adjustment process can potentially damage the LAC and degrade the assembly quality.Hence,a workspace-based hybrid force position control scheme was developed to achieve high quality assembly with high-precision and lower internal force.Firstly,an offline workspace analysis with inherent geometric characteristics to form time-varying posture error constraint.Then,the posture error is integrated into the online position axis control to ensure tracking the ideal posture,while the force control axis compensates for posture deviation by minimizing internal force,thereby achieving high precision and low internal force.Finally,the effectiveness was demonstrated through experiments.The root mean square errors of orientation and position are 104 rad and 0.1 mm,respectively.A reduction in internal force can range from 10.96%to 57.4%compared to the traditional method.Key points'max position error is decreased from 0.32 mm to 0.18 mm,satisfying the 0.5 mm tolerance.Therefore,the proposed method will help promote the development of high-performance manufacturing.展开更多
We report first-principles predictions of a cage-like polymeric nitrogen phase(cage-N)composed of interlocked N10 clusters stabilized by mixed sp^(2)/sp^(3) hybridization.Under high pressure,cage-N exhibits exceptiona...We report first-principles predictions of a cage-like polymeric nitrogen phase(cage-N)composed of interlocked N10 clusters stabilized by mixed sp^(2)/sp^(3) hybridization.Under high pressure,cage-N exhibits exceptional mechanical performance,including an ideal compressive strength of 343 GPa at a pressure of 300 GPa,~33% higher than that of diamond.This ultrahigh strength arises from the synergistic interplay between its three-dimensional covalent framework and hybridized bonding topology,which enables isotropic stress accommodation and dynamic electronic rearrangement.These results establish cage-N as a promising non-carbon ultrahard material and provide a bonding-driven route toward designing superhard frameworks under extreme conditions.展开更多
A hybrid model combining Fully Non-Linear Potential Flow Theory(FNPT)based on the Finite Element Method(FEM)and the Unified Navier-Stokes equation,using the 3D Improved Meshless Local Petrov Galerkin method with Ranki...A hybrid model combining Fully Non-Linear Potential Flow Theory(FNPT)based on the Finite Element Method(FEM)and the Unified Navier-Stokes equation,using the 3D Improved Meshless Local Petrov Galerkin method with Rankine Source(IMLPG_R),is developed to study wave interactions with a porous layer.In previous studies,the above formulations are applied to wave interaction with fixed cylindrical structures.The present study extends this framework by integrating a unified governing equation within the hybrid modeling approach to capture the dynamics of wave interaction with porous media.The porous layers are employed to replicate the wave-dissipating behavior of the structure.A weak coupling strategy is implemented within a designated buffer zone,wherein field variables from the 2D Fully Nonlinear Potential Theory(FNPT)simulations are transferred to the 3D Improved Moving Least Squares-based Petrov-Galerkin(IMLPG_R)model at each time step.This domain decomposition significantly reduces computational cost compared to a full 3D simulation by partitioning the domain into two subregions:the FNPT domain representing the far-field without structures,and the IMLPG_R domain encompassing the porous region.The Unified Navier-Stokes formulation is extended by incorporating additional drag forces governed by Darcy’s law to model the resistance introduced by the porous medium.A stationary background node framework is utilized for interpolation by fluid particles at each time step to accommodate the porous representation.To enhance numerical stability and accuracy,particularly in the presence of sloping boundaries,the Particle Shifting Technique(PST)is integrated into the IMLPG_R model.This implementation involves a modified version of the PST algorithm,where key parameters such as the weight function,velocity ratio,and radius of influence are optimized for IMLPG_R.This is the first time the application of 3D IMLPG_R for porous structure has been reported.Further,the model is subsequently validated against experimental data.展开更多
This paper proposes a tamper detection technique for semi-fragile watermarking using Quantizationbased Discrete Cosine Transform(DCT)for tamper localization.In this study,the proposed embedding strategy is investigate...This paper proposes a tamper detection technique for semi-fragile watermarking using Quantizationbased Discrete Cosine Transform(DCT)for tamper localization.In this study,the proposed embedding strategy is investigated by experimental tests over the diagonal order of the DCT coefficients.The cover image is divided into non-overlapping blocks of size 8×8 pixels.The DCT is applied to each block,and the coefficients are arranged using a zig-zag pattern within the block.In this study,the low-frequency coefficients are selected to examine the impact of the imperceptibility score and tamper detection accuracy.High accuracy of tamper detection can be achieved by checking the surrounding blocks to determine whether the corresponding block has been tampered with.The proposed tamper detection is tested under various malicious,incidental,and hybrid attacks(both incidental and malicious attacks).The experimental results demonstrate that the proposed technique achieves a Peak-Signal-to-Noise Ratio(PSNR)value of 41.2318 dB,an average Structural Similarity Index Measure(SSIM)value of 0.9768.The proposed scheme is also evaluated against malicious attacks such as copy-move,object deletion,object manipulation,and collage attacks.The proposed scheme can detect the malicious attack localization under various tampering rates.In addition,the proposed scheme can still detect tampered pixels under a hybrid attack,such as a combination ofmalicious and incidental attacks,with an average accuracy of 96.44%.展开更多
The world’s first hybrid commutated converter(HCC)—a next-generation high-voltage direct current(HVDC)transmission valve based on integrated gate commutated thyristor(IGCT)technology—officially commenced commercial...The world’s first hybrid commutated converter(HCC)—a next-generation high-voltage direct current(HVDC)transmission valve based on integrated gate commutated thyristor(IGCT)technology—officially commenced commercial operation at the Lingbao Converter Station in Henan Province,China,on December 28,2025,as shown in Figure 1.This milestone signifies the resolution of the“commutation failure”challenge that has plagued global HVDC transmission systems for over half a century.展开更多
Penduline tits(genus Remiz)are small passerines distributed across Europe,Central and East Asia,and North Africa,renowned for their elaborate nests and unusually diverse mating systems.However,the taxonomy and evoluti...Penduline tits(genus Remiz)are small passerines distributed across Europe,Central and East Asia,and North Africa,renowned for their elaborate nests and unusually diverse mating systems.However,the taxonomy and evolutionary relationships within this genus have remained contentious due to overlapping breeding distributions and extensive hybridization.Using broad-range geographic sampling and whole-genome sequencing,here we report the phylogenetic relationships within this genus.Our results from maximum likelihood trees,species trees,population structure,and PCA analyses consistently identify four distinct,well-supported monophyletic clades.Based on these robust results,we support dividing Remiz into four species:the Eurasian Penduline Tit(R.pendulinus),Black-headed Penduline Tit(R.macronyx),White-crowned Penduline Tit(R.coronatus),and Chinese Penduline Tit(R.consobrinus).Among these species,R.consobrinus diverged earlier from other species,followed by R.coronatus,and then,R.pendulinus and R.macronyx.R.pendulinus and R.macronyx showed shallow genetic differentiation with recent divergence(~87,000 years ago)and ongoing gene flow.Our findings demonstrate the effectiveness of phylogenomic approaches in resolving taxonomic ambiguities and provide a robust evolutionary framework for tracing the diversification of life history traits,particularly nest structures and mating systems,across the genus.展开更多
Precise forecasts of wildfire danger are crucial for proactive fuel management and emergency responses,yet they pose a challenge at the subseasonal scale due to limitations in prediction capabilities and a gap between...Precise forecasts of wildfire danger are crucial for proactive fuel management and emergency responses,yet they pose a challenge at the subseasonal scale due to limitations in prediction capabilities and a gap between forecast outputs and the needs of decision-makers.This study introduces an innovative hybrid modeling framework that integrates artificial intelligence(AI)with climate dynamic prediction systems to accurately forecast High Fire-Danger Days(HFDDs)for the following month.These HFDDs are derived from historical satellite fire data and the optimum fire danger index,with a particular focus on Southwest China as a case study.The AI module,based on the ResNet-18 neural network model,integrates observational and physically constrained analysis to establish links between HFDDs and optimal predictors of atmospheric circulation from both the concurrent and preceding months.Leveraging climate dynamical forecasting,this hybrid model provides more reliable deterministic predictions for monthly HFDDs than conventional methods that rely solely on terrestrial variables such as precipitation.More importantly,the integration of dynamical ensemble prediction enhances the model’s capability for skillful probabilistic predictions of HFDDs,facilitating the creation of customized fire danger outlooks and emergency action maps tailored to stakeholders’needs.The model’s added economic value was also evaluated,demonstrating its potential to improve decision-making in disaster management and bridge the“last-mile gap”in climate service delivery.This work contributes to the Seamless Prediction and Services for Sustainable Natural and Built Environment(SEPRESS)Program(2025–32),under the United Nations Educational Scientific and Cultural Organization(UNESCO)International Decade of Sciences for Sustainable Development(2024–33).展开更多
In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honey...In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honeycomb cells,was created by constructing arrangement matrices to achieve structural lightweight.The machine learning(ML)framework consisted of a neural network(NN)forward regression model for predicting impact resistance and a multi-objective optimization algorithm for generating high-performance designs.The surrogate of the local design space was initially realized by establishing the NN in the small sample dataset,and the active learning strategy was used to continuously extended the local optimal design until the model converged in the global space.The results indicated that the active learning strategy significantly improved the inference capability of the NN model in unknown design domains.By guiding the iteration direction of the optimization algorithm,lightweight designs with high impact resistance were identified.The energy absorption capacity of the optimal design reached 94.98%of the EARE honeycomb,while the initial peak stress and mass decreased by 28.85%and 19.91%,respectively.Furthermore,Shapley Additive Explanations(SHAP)for global explanation of the NN indicated a strong correlation between the arrangement mode of HCS and its impact resistance.By reducing the stiffness of the cells at the top boundary of the structure,the initial impact damage sustained by the structure can be significantly improved.Overall,this study proposed a general lightweight design method for array structures under impact loads,which is beneficial for the widespread application of honeycomb-based protective structures.展开更多
This study investigates the genetic variability and environmental adaptability of Acacia hybrid clones across three distinct ecological regions,providing insights into growth characteristics and stem quality for futur...This study investigates the genetic variability and environmental adaptability of Acacia hybrid clones across three distinct ecological regions,providing insights into growth characteristics and stem quality for future breeding strategies.42 natural hybrid clones were evaluated over a five-year period in three clonal trials in northern,central and southern Vietnam for height(HT),diameter at breast height(DBH),volume(VOL),trunk straightness(STR),branch size(BRA)and survival.Significant clonal differences were found in all traits across all three regions.From age 2-5,the clone repeatability(H_(C)^(2))for growth traits improved from 0.19 to 0.59,indicating substantial genetic control.Genotypic coefficients of variation(CVG)for volume ranged from 21%to 34%,suggesting significant potential for genetic improvement.Site-to-site genotypic correlations ranged from 0.53 to 0.78,pointing to the existence of genotype-environment interactions.Clones derived from Acacia mangium material demonstrated enhanced growth,while the hybrid clones exhibited superior stem quality,particularly in terms of straightness.The findings emphasize the importance of selecting clones that are adapted to specific environmental conditions,with both growth and quality traits considered in breeding programs.展开更多
D-π hybridization is a key structural feature that may significantly affect the intrinsic electronic properties of metallopolymers.Herein,we present the electrosynthesis and memristive properties of metallopolymers u...D-π hybridization is a key structural feature that may significantly affect the intrinsic electronic properties of metallopolymers.Herein,we present the electrosynthesis and memristive properties of metallopolymers using the distinct d-π hybridization monomers R_(1) and R_(2).R_(1)(Ru^(Ⅱ)-(tpz)Cl_(2))features tetradentate ligands(tpz,6,6'-di(1H-pyrazol-1-yl)-2,2'-bipyridine)enforcing quasi-octahedral geometry;R_(2)(Ru^(Ⅱ)-(bpp)_(2))incorporates tridentate ligands(bpp,2,6-di(1H-pyrazol-1-yl)pyridine)inducing pronounced geometric distortion.The planar ligand(tpz)in R_(1) facilitates ordered molecular assembly through high conformational rigidity and extensive π-π stacking,resulting in increased molecular densities and enhanced morphological uniformity compared to R_(2) metallopolymers.Due to pyrazole’s weaker π-acceptance and strongerσ-donation compared to pyridine,R_(1) exhibits a 119 nm red-shift in metal-to-ligand charge transfer(MLCT)band and a 30 mV anodic shift in Ru^(+2/+3)redox potential relative to R_(2).Coupled with a reduced HOMO-LUMO gap,the uniform and ordered structure leads to a lower conductance decay constant in R_(1).Additionally,R_(2) metallopolymers exhibit superior memristive performance(characterized by lower switching voltage and higher switching ratio)via redox-induced aromatic transitions in axial ligands enhancing electronic delocalization.This work compares two metallopolymers with different ligand geometries,revealing how this difference leads to distinct charge transport and memristive behaviors.展开更多
The net capturing method holds great potential for space debris removal due to its adaptability to the various target shapes and high fault tolerance.However,the capture mechanisms of current rope nets,which rely sole...The net capturing method holds great potential for space debris removal due to its adaptability to the various target shapes and high fault tolerance.However,the capture mechanisms of current rope nets,which rely solely on a passive wrap-ping mechanism,limit their capacity to capture objects within a specific size range and make it challenging to handle unexpected situations.Inspired by spider webs,which combine wrapping and adhering to capture prey of various sizes,we present a new type of net(envelope diameter:208.49 mm)for on-orbit capture.This net adopts a spiral symmetric structure similar to spider webs,incorporates electrostatic-microstructure hybrid adhesives,and increases the maximum contact area by 38.31%,allowing it to capture debris ranging from fragments smaller than the mesh size(envelope diam-eter:2.7 mm-4.4 mm)to larger objects(envelope diameter:270 mm),and effectively grasps flexible items(450 mm2),planar items(350 mm2)and three-dimensional items(160 mm3).Moreover,to validate the net's capability for wrapping and adhesion,simulations and experiments are demonstrated that this dual capture method can effectively handle various targets.展开更多
Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may r...Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships.Networking structures are highly sensitive in social networks,requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks.In addition,they miss out on accurately identifying clusters.Since single-objective optimization cannot always generate accurate and comprehensive results,as multi-objective optimization can.Therefore,we utilized two objective functions that enable strong connections between communities and weak connections between them.In this study,we utilized the intra function,which has proven effective in state-of-the-art research studies.We proposed a new inter-function that has demonstrated its effectiveness by making the objective of detecting external connections between communities is to make them more distinct and sparse.Furthermore,we proposed a Multi-Objective community strength enhancement algorithm(MOCSE).The proposed algorithm is based on the framework of the Multi-Objective Evolutionary Algorithm with Decomposition(MOEA/D),integrated with a new heuristic mutation strategy,community strength enhancement(CSE).The results demonstrate that the model is effective in accurately identifying community structures while also being computationally efficient.The performance measures used to evaluate the MOEA/D algorithm in our work are normalized mutual information(NMI)and modularity(Q).It was tested using five state-of-the-art algorithms on social networks,comprising real datasets(Zachary,Dolphin,Football,Krebs,SFI,Jazz,and Netscience),as well as twenty synthetic datasets.These results provide the robustness and practical value of the proposed algorithm in multi-objective community identification.展开更多
基金supported by the National Natural Science Foundation of China(U23A20160,32360336)Guizhou Provincial Key Technology R&D Program(Qian KeHe ZhiCheng[2023]YiBan035).
文摘Natural hybridization is known to play a vital role in speciation;however,the mechanisms underlying the early stages of natural hybridization remain unclear.Where two plant species come into contact,two driving forces may balance the dynamic consequences of hybridization:fusion by hybridization-mediated gene flow,and separation by reproductive isolation(RI)(Ma et al.,2010a,b;Chang et al.,2022).
基金Acknowledgements We thank C. Long and M. Rounds for help with data collection. Thanks to Tom Getty, Genevieve Kozak, Michael Jennions, several anonymous reviewers, and the Boughman lab for helping to improve this manuscript. Research was conducted under permits from the Ministry of the Environment, BC and approval from University of Wis- consin-Madison Institutional Animal Care and Use Committee. This work was supported by the Emlen Fund from the Zoolo- gy Department of the University of Wisconsin, Madison to ACRL and the National Science Foundation to JWB.
文摘One approach to understand the importance of reproductive barriers to the speciation process is to study the break- down of barriers between formerly distinct species. One reproductive barrier, sexual isolation, reduces gene flow between species through differences in mate preferences and mating signals and is likely important for species formation and maintenance. We measure sexual isolation in two limnetic-benthic threespine stickleback species pairs （Gasterosteus spp.）. One species pair main- tains strong reproductive isolation while the other species pair has recently collapsed into a hybrid swarm. We compare the strength of sexual isolation in the hybridizing pair to the currently isolated pair. We provide the first evidence that sexual isolation has been lost in the hybridizing pair and show furthermore that preferences females have for conspecific mates and the traits they use to distinguish conspecific and heterospecific males contribute to this loss. This work highlights the fragility of reproductive isolation between young species pairs and considers the role of sexual isolation in speciation [Current Zoology 59 （5）： 591-603, 2013].
文摘Many studies on fiber reinforced polymer composite bars, as a substitute for reinforcing bars, have been conducted to solve corrosion of steel in reinforced concrete structures since 1960s’. However, FRP Bars have a lower elastic modulus than steel rebar as a structural component of concrete structures. Material properties with brittleness fracture and low elastic modulus can be improved by combining cheaper steel than carbon or aramid fibers. In this study, prototypes of FRP Bars with inserted steel wires (i.e., “FRP Hybrid Bars”) were developed and their tensile performance was compared depending on the proportion and diameter of steel. The FRP Hybrid Bars were made by dividing them into D13 and D16 according to the diameter and proportion of inserted wires: GFRPs were combined with wires having different diameters of 0.5 mm, 1.0 mm, and 2.0 mm in the proportion of 10%, 30%, 50%, and 70%, respectively. As a result of tensile tests, the elastic modulus of FRP Hybrid Bars were improved as 20% - 190% in comparison with the fully GFRP Bars.
基金We would like to thank the Mexican federal government and the state of Hidalgo for providing permits to collect fish and Nick Ratterman, Kirk Winemiller and Lee Fitzgerald for helpful comments on early versions of this manuscript. This work was supported by funding provided by a National Science Foundation grant （I0S-0923825） award- ed to G.G.R.R.E. was supported by an Undergraduate Program in Biological and Mathematical Sciences （UBM National Science Foundation grant （DBI-1029401） directed by Dr. Jay Walton. All experiments conducted in this study complied with current state, federal, and local laws in the United States and Mexico.
文摘Correlations among behavioral traits can generate trade-offs and constrain phenotypic evolution. Interspecific hybridization has the potential to alter behavioral trait correlations, but the effect of hybridization on suites of behavioral traits has received relatively little attention. We evaluated how natural hybridization changes the relationship between boldness （time of emergence and proportion of time out of shelter） and response to a simulated predator threat in swordtails （Teleostei： Xiphophorus）. In poeciliid fishes, bold individuals have increased survival in the presence of predators. This non-intuitive observation may arise as a result of bold individuals being more likely to engage in anti-predator behaviors. Contrary to our prediction, bold indi- viduals were less likely to perform a fast-start response to a predator threat. This correlation was consistent among populations and species but was only significant in hybrids. The observed correlation between boldness and anti-predator behavior could im- pact hybrid fitness and the evolvability of hybrid lineages. More generally, our findings suggest that hybridization could influence the integration of behavioral phenotypes, as has been amply documented for morphology. Animal personality and behavioral syndromes could therefore play an important role in the evolutionary fate of natural hybrids [Current Zoology 61 （4）： 596-603, 2015].
基金support from the Shiraz University(during 2015-2022)Ferdowsi University of Mashhad,Iran(during 2011-2013)the Department of Environment(DOE)for giving permission to AG for sampling(91.51843)。
文摘The closely related Black-headed Bunting(Emberiza melanocephala,a western Palearctic lineage)and Red-headed Bunting(Emberiza bruniceps,an eastern Palearctic lineage)hybridize and replace each other south of the Caspian Sea.The parental species have distinct phenotypes and therefore morphology is useful for assessing hybridization in the contact zone.In the years of 1940 and 1977,quite a few hybrids were collected and studied morphologically.Since then,the hybrid zone appears to have expanded westwards,but there has been a time gap in the collection of morphological data.Here we reanalyze bunting specimens morphologically and compare the historical data with recent data.Morphometric and phenotypic traits from three time periods(1940,1977 and recent)were studied to assess phenotypic variation of hybrids,pattern of hybridization,and transgressive traits in the hybrid zone.Our results show that most of the birds in the hybrid zone exhibit intermediate phenotypes(both colors and morphometric characters),ranging from the pure phenotype of either of the parental species.However,hybridization has also produced novel phenotypes not seen in any of the parents.Using a canonical discriminant function analysis,the morphometric characters separated each parental species and the hybrids quite well.Our results showed morphometric intermediacy of hybrids in accordance with phenotypes.We observe a time trend in which recent hybrids are more similar to Red-headed Buntings phenotypically compared to historical samples.This pattern is likely a signature of a westward expansion of the Red-headed Bunting into the breeding range of the Black-headed Bunting.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFB3804100)the National Natural Science Foundation of China(Grant Nos.52171153,and 52371149).
文摘FeSiBCuNb/FeNi composite magnetic powder cores(CMPCs)with outstanding high-frequency permeability and low core loss(P_(cv))have been developed by hybridizing HNO 3-passivated Fe_(73.5)Cu_(1)Nb_(3)Si_(13.5)B_(9) nanocrystalline powder with finer Fe 50Ni 50 powder.A 7 wt.%HNO 3 passivation treatment forms a Fe_(3)O_(4)-dominant oxidation layer on the nanocrystalline powder surface,which increases its electrical resistivity and reduces the P_(cv) of the power cores.As FeNi content increases from 0 to 40 wt.%,the porosity of the CMPCs decreases consistently,while saturation magnetization(M_(s)),effective permeability(μ_(e)),and P_(cv) gradually enhance.An appropriate increase in compaction pressure further decreases the porosity and leads to enhanced M s,μe,and lowered P_(cv).The CMPC with 40 wt.%FeNi,compacted at 1000 MPa,exhibits the best comprehensive soft magnetic properties with M s,μe,and P_(cv) at 50 mT/200 kHz of 136.3 emu/g,57.4,and 599 mW/cm^(3),respectively.The improved M_(s) andμe result from the reduced porosity combined with the FeNi’s inherently higher M_(s) and μ_(e).The increased high-frequency P_(cv) after FeNi addition mainly arises from the raised eddy loss due to decreased electrical resistivity.The reduced P_(cv) through the optimal compaction pressure is due to the further elimination of pore defects in the CMPCs.
基金co-supported by the National Natural Science Foundation of China(No.52125504)the Liaoning Revitalization Talents Program(No.XLYC2202017)Dalian Support Policy Project for Innovation of Technological Talents(No.2023RG001)。
文摘The high-quality assembly of Large Aircraft Components(LACs)is essential in modern aviation manufacturing.Numerical control locators are employed for the posture adjustment of LAC,yet the system's multi-input multi-output,nonlinearity,and strong coupling presents significant challenges.The substantial internal force generated during the adjustment process can potentially damage the LAC and degrade the assembly quality.Hence,a workspace-based hybrid force position control scheme was developed to achieve high quality assembly with high-precision and lower internal force.Firstly,an offline workspace analysis with inherent geometric characteristics to form time-varying posture error constraint.Then,the posture error is integrated into the online position axis control to ensure tracking the ideal posture,while the force control axis compensates for posture deviation by minimizing internal force,thereby achieving high precision and low internal force.Finally,the effectiveness was demonstrated through experiments.The root mean square errors of orientation and position are 104 rad and 0.1 mm,respectively.A reduction in internal force can range from 10.96%to 57.4%compared to the traditional method.Key points'max position error is decreased from 0.32 mm to 0.18 mm,satisfying the 0.5 mm tolerance.Therefore,the proposed method will help promote the development of high-performance manufacturing.
基金supported by the Natural Science Foundation of China(Grant Nos.T2325013,52288102,52090024,12034009,12474004,and 12304036)the National Key R&D Program of China Grant No.2023YFA1610000+1 种基金the Fundamental Research Funds for the Central Universitiesthe Program for Jilin University and Sun Yat-sen University.
文摘We report first-principles predictions of a cage-like polymeric nitrogen phase(cage-N)composed of interlocked N10 clusters stabilized by mixed sp^(2)/sp^(3) hybridization.Under high pressure,cage-N exhibits exceptional mechanical performance,including an ideal compressive strength of 343 GPa at a pressure of 300 GPa,~33% higher than that of diamond.This ultrahigh strength arises from the synergistic interplay between its three-dimensional covalent framework and hybridized bonding topology,which enables isotropic stress accommodation and dynamic electronic rearrangement.These results establish cage-N as a promising non-carbon ultrahard material and provide a bonding-driven route toward designing superhard frameworks under extreme conditions.
基金funded by Prime Minister’s Research Fellowship(PMRF),grant number SB22230924OEPMRF008608.
文摘A hybrid model combining Fully Non-Linear Potential Flow Theory(FNPT)based on the Finite Element Method(FEM)and the Unified Navier-Stokes equation,using the 3D Improved Meshless Local Petrov Galerkin method with Rankine Source(IMLPG_R),is developed to study wave interactions with a porous layer.In previous studies,the above formulations are applied to wave interaction with fixed cylindrical structures.The present study extends this framework by integrating a unified governing equation within the hybrid modeling approach to capture the dynamics of wave interaction with porous media.The porous layers are employed to replicate the wave-dissipating behavior of the structure.A weak coupling strategy is implemented within a designated buffer zone,wherein field variables from the 2D Fully Nonlinear Potential Theory(FNPT)simulations are transferred to the 3D Improved Moving Least Squares-based Petrov-Galerkin(IMLPG_R)model at each time step.This domain decomposition significantly reduces computational cost compared to a full 3D simulation by partitioning the domain into two subregions:the FNPT domain representing the far-field without structures,and the IMLPG_R domain encompassing the porous region.The Unified Navier-Stokes formulation is extended by incorporating additional drag forces governed by Darcy’s law to model the resistance introduced by the porous medium.A stationary background node framework is utilized for interpolation by fluid particles at each time step to accommodate the porous representation.To enhance numerical stability and accuracy,particularly in the presence of sloping boundaries,the Particle Shifting Technique(PST)is integrated into the IMLPG_R model.This implementation involves a modified version of the PST algorithm,where key parameters such as the weight function,velocity ratio,and radius of influence are optimized for IMLPG_R.This is the first time the application of 3D IMLPG_R for porous structure has been reported.Further,the model is subsequently validated against experimental data.
基金funded by Ministry of Higher Education Malaysia through Universiti Malaysia Pahang Al-Sultan Abdullah under Internal Research Grant(RDU233003).
文摘This paper proposes a tamper detection technique for semi-fragile watermarking using Quantizationbased Discrete Cosine Transform(DCT)for tamper localization.In this study,the proposed embedding strategy is investigated by experimental tests over the diagonal order of the DCT coefficients.The cover image is divided into non-overlapping blocks of size 8×8 pixels.The DCT is applied to each block,and the coefficients are arranged using a zig-zag pattern within the block.In this study,the low-frequency coefficients are selected to examine the impact of the imperceptibility score and tamper detection accuracy.High accuracy of tamper detection can be achieved by checking the surrounding blocks to determine whether the corresponding block has been tampered with.The proposed tamper detection is tested under various malicious,incidental,and hybrid attacks(both incidental and malicious attacks).The experimental results demonstrate that the proposed technique achieves a Peak-Signal-to-Noise Ratio(PSNR)value of 41.2318 dB,an average Structural Similarity Index Measure(SSIM)value of 0.9768.The proposed scheme is also evaluated against malicious attacks such as copy-move,object deletion,object manipulation,and collage attacks.The proposed scheme can detect the malicious attack localization under various tampering rates.In addition,the proposed scheme can still detect tampered pixels under a hybrid attack,such as a combination ofmalicious and incidental attacks,with an average accuracy of 96.44%.
文摘The world’s first hybrid commutated converter(HCC)—a next-generation high-voltage direct current(HVDC)transmission valve based on integrated gate commutated thyristor(IGCT)technology—officially commenced commercial operation at the Lingbao Converter Station in Henan Province,China,on December 28,2025,as shown in Figure 1.This milestone signifies the resolution of the“commutation failure”challenge that has plagued global HVDC transmission systems for over half a century.
基金supported by the National Natural Science Foundation of China(32161143024,32500368,31970405)the Third Xinjiang Scientific Expedition Program(2022xjkk0200)+2 种基金INSF-NSFC Joint Research Project(No.4002006)HUN-REN-Debrecen University Reproductive Strategies Research Group grant(Ref 1102207)supported by the Postdoctoral Fellowship Program of CPSF under Grant Number GZC20240121。
文摘Penduline tits(genus Remiz)are small passerines distributed across Europe,Central and East Asia,and North Africa,renowned for their elaborate nests and unusually diverse mating systems.However,the taxonomy and evolutionary relationships within this genus have remained contentious due to overlapping breeding distributions and extensive hybridization.Using broad-range geographic sampling and whole-genome sequencing,here we report the phylogenetic relationships within this genus.Our results from maximum likelihood trees,species trees,population structure,and PCA analyses consistently identify four distinct,well-supported monophyletic clades.Based on these robust results,we support dividing Remiz into four species:the Eurasian Penduline Tit(R.pendulinus),Black-headed Penduline Tit(R.macronyx),White-crowned Penduline Tit(R.coronatus),and Chinese Penduline Tit(R.consobrinus).Among these species,R.consobrinus diverged earlier from other species,followed by R.coronatus,and then,R.pendulinus and R.macronyx.R.pendulinus and R.macronyx showed shallow genetic differentiation with recent divergence(~87,000 years ago)and ongoing gene flow.Our findings demonstrate the effectiveness of phylogenomic approaches in resolving taxonomic ambiguities and provide a robust evolutionary framework for tracing the diversification of life history traits,particularly nest structures and mating systems,across the genus.
基金J.YANG was supported by funding from the National Natural Science Foundation of China(Grant Nos.42475022,42261144671)the National Key R&D Program of China(Project No.2024YFC3013100)+2 种基金the Fundamental Research Funds for the Central UniversitiesM.LU was supported by the Otto Poon Centre of Climate Resilience and Sustainability at HKUST and the Hong Kong Research Grant Committee(Project No.16300424)Data processing and storage were supported by the National Key Scientific and Technological Infrastructure project“Earth System Numerical Simulation Facility”(EarthLab).
文摘Precise forecasts of wildfire danger are crucial for proactive fuel management and emergency responses,yet they pose a challenge at the subseasonal scale due to limitations in prediction capabilities and a gap between forecast outputs and the needs of decision-makers.This study introduces an innovative hybrid modeling framework that integrates artificial intelligence(AI)with climate dynamic prediction systems to accurately forecast High Fire-Danger Days(HFDDs)for the following month.These HFDDs are derived from historical satellite fire data and the optimum fire danger index,with a particular focus on Southwest China as a case study.The AI module,based on the ResNet-18 neural network model,integrates observational and physically constrained analysis to establish links between HFDDs and optimal predictors of atmospheric circulation from both the concurrent and preceding months.Leveraging climate dynamical forecasting,this hybrid model provides more reliable deterministic predictions for monthly HFDDs than conventional methods that rely solely on terrestrial variables such as precipitation.More importantly,the integration of dynamical ensemble prediction enhances the model’s capability for skillful probabilistic predictions of HFDDs,facilitating the creation of customized fire danger outlooks and emergency action maps tailored to stakeholders’needs.The model’s added economic value was also evaluated,demonstrating its potential to improve decision-making in disaster management and bridge the“last-mile gap”in climate service delivery.This work contributes to the Seamless Prediction and Services for Sustainable Natural and Built Environment(SEPRESS)Program(2025–32),under the United Nations Educational Scientific and Cultural Organization(UNESCO)International Decade of Sciences for Sustainable Development(2024–33).
基金the financial supports from National Key R&D Program for Young Scientists of China(Grant No.2022YFC3080900)National Natural Science Foundation of China(Grant No.52374181)+1 种基金BIT Research and Innovation Promoting Project(Grant No.2024YCXZ017)supported by Science and Technology Innovation Program of Beijing institute of technology under Grant No.2022CX01025。
文摘In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honeycomb cells,was created by constructing arrangement matrices to achieve structural lightweight.The machine learning(ML)framework consisted of a neural network(NN)forward regression model for predicting impact resistance and a multi-objective optimization algorithm for generating high-performance designs.The surrogate of the local design space was initially realized by establishing the NN in the small sample dataset,and the active learning strategy was used to continuously extended the local optimal design until the model converged in the global space.The results indicated that the active learning strategy significantly improved the inference capability of the NN model in unknown design domains.By guiding the iteration direction of the optimization algorithm,lightweight designs with high impact resistance were identified.The energy absorption capacity of the optimal design reached 94.98%of the EARE honeycomb,while the initial peak stress and mass decreased by 28.85%and 19.91%,respectively.Furthermore,Shapley Additive Explanations(SHAP)for global explanation of the NN indicated a strong correlation between the arrangement mode of HCS and its impact resistance.By reducing the stiffness of the cells at the top boundary of the structure,the initial impact damage sustained by the structure can be significantly improved.Overall,this study proposed a general lightweight design method for array structures under impact loads,which is beneficial for the widespread application of honeycomb-based protective structures.
基金funded by the project:Breeding and selection of Acacia hybrids and Acacia auriculiformis for large-timber plantation establishment in major ecological zones(000.00.16.G06-230504-0003).
文摘This study investigates the genetic variability and environmental adaptability of Acacia hybrid clones across three distinct ecological regions,providing insights into growth characteristics and stem quality for future breeding strategies.42 natural hybrid clones were evaluated over a five-year period in three clonal trials in northern,central and southern Vietnam for height(HT),diameter at breast height(DBH),volume(VOL),trunk straightness(STR),branch size(BRA)and survival.Significant clonal differences were found in all traits across all three regions.From age 2-5,the clone repeatability(H_(C)^(2))for growth traits improved from 0.19 to 0.59,indicating substantial genetic control.Genotypic coefficients of variation(CVG)for volume ranged from 21%to 34%,suggesting significant potential for genetic improvement.Site-to-site genotypic correlations ranged from 0.53 to 0.78,pointing to the existence of genotype-environment interactions.Clones derived from Acacia mangium material demonstrated enhanced growth,while the hybrid clones exhibited superior stem quality,particularly in terms of straightness.The findings emphasize the importance of selecting clones that are adapted to specific environmental conditions,with both growth and quality traits considered in breeding programs.
文摘D-π hybridization is a key structural feature that may significantly affect the intrinsic electronic properties of metallopolymers.Herein,we present the electrosynthesis and memristive properties of metallopolymers using the distinct d-π hybridization monomers R_(1) and R_(2).R_(1)(Ru^(Ⅱ)-(tpz)Cl_(2))features tetradentate ligands(tpz,6,6'-di(1H-pyrazol-1-yl)-2,2'-bipyridine)enforcing quasi-octahedral geometry;R_(2)(Ru^(Ⅱ)-(bpp)_(2))incorporates tridentate ligands(bpp,2,6-di(1H-pyrazol-1-yl)pyridine)inducing pronounced geometric distortion.The planar ligand(tpz)in R_(1) facilitates ordered molecular assembly through high conformational rigidity and extensive π-π stacking,resulting in increased molecular densities and enhanced morphological uniformity compared to R_(2) metallopolymers.Due to pyrazole’s weaker π-acceptance and strongerσ-donation compared to pyridine,R_(1) exhibits a 119 nm red-shift in metal-to-ligand charge transfer(MLCT)band and a 30 mV anodic shift in Ru^(+2/+3)redox potential relative to R_(2).Coupled with a reduced HOMO-LUMO gap,the uniform and ordered structure leads to a lower conductance decay constant in R_(1).Additionally,R_(2) metallopolymers exhibit superior memristive performance(characterized by lower switching voltage and higher switching ratio)via redox-induced aromatic transitions in axial ligands enhancing electronic delocalization.This work compares two metallopolymers with different ligand geometries,revealing how this difference leads to distinct charge transport and memristive behaviors.
基金the New Chongqing Innovative Young Talent Project under Grant 2024NSCQ-qncxX0468Dreams Foundation of Jianghuai Advance Technology Center under Grant 2023-ZM01Z007.
文摘The net capturing method holds great potential for space debris removal due to its adaptability to the various target shapes and high fault tolerance.However,the capture mechanisms of current rope nets,which rely solely on a passive wrap-ping mechanism,limit their capacity to capture objects within a specific size range and make it challenging to handle unexpected situations.Inspired by spider webs,which combine wrapping and adhering to capture prey of various sizes,we present a new type of net(envelope diameter:208.49 mm)for on-orbit capture.This net adopts a spiral symmetric structure similar to spider webs,incorporates electrostatic-microstructure hybrid adhesives,and increases the maximum contact area by 38.31%,allowing it to capture debris ranging from fragments smaller than the mesh size(envelope diam-eter:2.7 mm-4.4 mm)to larger objects(envelope diameter:270 mm),and effectively grasps flexible items(450 mm2),planar items(350 mm2)and three-dimensional items(160 mm3).Moreover,to validate the net's capability for wrapping and adhesion,simulations and experiments are demonstrated that this dual capture method can effectively handle various targets.
文摘Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships.Networking structures are highly sensitive in social networks,requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks.In addition,they miss out on accurately identifying clusters.Since single-objective optimization cannot always generate accurate and comprehensive results,as multi-objective optimization can.Therefore,we utilized two objective functions that enable strong connections between communities and weak connections between them.In this study,we utilized the intra function,which has proven effective in state-of-the-art research studies.We proposed a new inter-function that has demonstrated its effectiveness by making the objective of detecting external connections between communities is to make them more distinct and sparse.Furthermore,we proposed a Multi-Objective community strength enhancement algorithm(MOCSE).The proposed algorithm is based on the framework of the Multi-Objective Evolutionary Algorithm with Decomposition(MOEA/D),integrated with a new heuristic mutation strategy,community strength enhancement(CSE).The results demonstrate that the model is effective in accurately identifying community structures while also being computationally efficient.The performance measures used to evaluate the MOEA/D algorithm in our work are normalized mutual information(NMI)and modularity(Q).It was tested using five state-of-the-art algorithms on social networks,comprising real datasets(Zachary,Dolphin,Football,Krebs,SFI,Jazz,and Netscience),as well as twenty synthetic datasets.These results provide the robustness and practical value of the proposed algorithm in multi-objective community identification.
