Dynamic evolution and trend prediction of multi-scale green innovation in China

Numerous studies deal with spatial analysis of green innovation(GI).However,researchers have paid limited attention to analyzing the multi-scale evolution patterns and predicting trends of GI in China.This paper seeks to address this research gap by examining the multi-scale distribution and evolutionary characteristics of GI activities based on the data from 337 cities in China during 2000-2019.We used scale variance and the two-stage nested Theil decomposition method to examine the spatial distribution and inequalities of GI in China at multiple scales,including regional,provincial,and prefectural.Additionally,we utilized the Markov chain and spatial Markov chain to explore the dynamic evolution of GI in China and predict its long-term development.The findings indicate that GI in China has a multi-scale effect and is highly sensitive to changes in spatial scale,with significant spatial differences of GI decreasing in each scale.Furthermore,the spatiotemporal evolution of GI is influenced by both geospatial patterns and spatial scales,exhibiting the“club convergence”effect and a tendency to transfer to higher levels of proximity.This effect is more pronounced on a larger scale,but it is increasingly challenging to transfer to higher levels.The study also indicates a steady and sustained growth of GI in China,which concentrates on higher levels over time.These results contribute to a more precise understanding of the scale at which GI develops and provide a scientific basis and policy suggestions for optimizing the spatial structure of GI and promoting its development in China.

A semi-analytical model for coupled flow in stress-sensitive multi-scale shale reservoirs with fractal characteristics

A large number of nanopores and complex fracture structures in shale reservoirs results in multi-scale flow of oil. With the development of shale oil reservoirs, the permeability of multi-scale media undergoes changes due to stress sensitivity, which plays a crucial role in controlling pressure propagation and oil flow. This paper proposes a multi-scale coupled flow mathematical model of matrix nanopores, induced fractures, and hydraulic fractures. In this model, the micro-scale effects of shale oil flow in fractal nanopores, fractal induced fracture network, and stress sensitivity of multi-scale media are considered. We solved the model iteratively using Pedrosa transform, semi-analytic Segmented Bessel function, Laplace transform. The results of this model exhibit good agreement with the numerical solution and field production data, confirming the high accuracy of the model. As well, the influence of stress sensitivity on permeability, pressure and production is analyzed. It is shown that the permeability and production decrease significantly when induced fractures are weakly supported. Closed induced fractures can inhibit interporosity flow in the stimulated reservoir volume (SRV). It has been shown in sensitivity analysis that hydraulic fractures are beneficial to early production, and induced fractures in SRV are beneficial to middle production. The model can characterize multi-scale flow characteristics of shale oil, providing theoretical guidance for rapid productivity evaluation.

Deformable Catalytic Material Derived from Mechanical Flexibility for Hydrogen Evolution Reaction

Deformable catalytic material with excellent flexible structure is a new type of catalyst that has been applied in various chemical reactions,especially electrocatalytic hydrogen evolution reaction(HER).In recent years,deformable catalysts for HER have made great progress and would become a research hotspot.The catalytic activities of deformable catalysts could be adjustable by the strain engineering and surface reconfiguration.The surface curvature of flexible catalytic materials is closely related to the electrocatalytic HER properties.Here,firstly,we systematically summarized self-adaptive catalytic performance of deformable catalysts and various micro–nanostructures evolution in catalytic HER process.Secondly,a series of strategies to design highly active catalysts based on the mechanical flexibility of lowdimensional nanomaterials were summarized.Last but not least,we presented the challenges and prospects of the study of flexible and deformable micro–nanostructures of electrocatalysts,which would further deepen the understanding of catalytic mechanisms of deformable HER catalyst.

Multi-scale physics-informed neural networks for solving high Reynolds number boundary layer flows based on matched asymptotic expansions

Multi-scale system remains a classical scientific problem in fluid dynamics,biology,etc.In the present study,a scheme of multi-scale Physics-informed neural networks is proposed to solve the boundary layer flow at high Reynolds numbers without any data.The flow is divided into several regions with different scales based on Prandtl's boundary theory.Different regions are solved with governing equations in different scales.The method of matched asymptotic expansions is used to make the flow field continuously.A flow on a semi infinite flat plate at a high Reynolds number is considered a multi-scale problem because the boundary layer scale is much smaller than the outer flow scale.The results are compared with the reference numerical solutions,which show that the msPINNs can solve the multi-scale problem of the boundary layer in high Reynolds number flows.This scheme can be developed for more multi-scale problems in the future.

Mg/MgO interfaces as efficient hydrogen evolution cathodes causing accelerated corrosion of additive manufactured Mg alloys:A DFT analysis

The corrosion rates of additive-manufactured Mg alloys are higher than their as-cast counterparts,possibly due to increased kinetics for the hydrogen evolution reaction on secondary phases,which may include oxide inclusions.Scanning Kelvin Probe Force Microscopy demonstrated that MgO inclusions could act as cathodes for Mg corrosion,but their low conductivity likely precludes this.However,the density of state calculations through density functional theory using hybrid HSE06 functional revealed overlapping electronic states at the Mg/MgO interface,which facilitates electron transfers and participates in redox reactions.Subsequent determination of the hydrogen absorption energy at the Mg/MgO interface reveals it to be an excellent catalytic site,with HER being found to be a factor of 23x more efficient at the interface than on metallic Mg.The results not only support the plausibility of the Mg/MgO interface being an effective cathode to the adjacent anodic Mg matrix during corrosion but also contribute to the understanding of the enhanced cathodic activities observed during the anodic dissolution of magnesium.

Precisely Control Relationship between Sulfur Vacancy and H Absorption for Boosting Hydrogen Evolution Reaction

Ef fective and robust catalyst is the core of water splitting to produce hydrogen.Here, we report an anionic etching method to tailor the sulfur vacancy(VS) of NiS_(2) to further enhance the electrocatalytic performance for hydrogen evolution reaction(HER). With the VS concentration change from 2.4% to 8.5%, the H* adsorption strength on S sites changed and NiS_(2)-VS 5.9% shows the most optimized H* adsorption for HER with an ultralow onset potential(68 m V) and has long-term stability for 100 h in 1 M KOH media. In situ attenuated-total-reflection Fourier transform infrared spectroscopy(ATR-FTIRS) measurements are usually used to monitor the adsorption of intermediates. The S-H* peak of the Ni S_(2)-VS 5.9% appears at a very low voltage, which is favorable for the HER in alkaline media. Density functional theory calculations also demonstrate the Ni S_(2)-VS 5.9% has the optimal |ΔG^(H*)| of 0.17 e V. This work offers a simple and promising pathway to enhance catalytic activity via precise vacancies strategy.

Valence electronic engineering of superhydrophilic Dy-evoked Ni-MOF outperforming RuO_(2) for highly efficient electrocatalytic oxygen evolution

Tackling the problem of poor conductivity and catalytic stability of pristine metal-organic frameworks(MOFs) is crucial to improve their oxygen evolution reaction(OER) performance.Herein,we introduce a novel strategy of dysprosium(Dy) doping,using the unique 4f orbitals of this rare earth element to enhance electrocatalytic activity of MOFs.Our method involves constructing Dy-doped Ni-MOF(Dy@Ni-MOF) nanoneedles on carbon cloth via a Dy-induced valence electronic perturbation approach.Experiments and density functional theory(DFT) calculations reveal that Dy doping can effectively modify the electronic structure of the Ni active centers and foster a strong electronic interaction between Ni and Dy.The resulting benefits include a reduced work function and a closer proximity of the d-band center to the Fermi level,which is conducive to improving electrical conductivity and promoting the adsorption of oxygen-containing intermediates.Furthermore,the Dy@Ni-MOF achieves superhydrophilicity,ensuring effective electrolyte contact and thus accelerating reaction kinetics,Ex-situ and in-situ analysis results manifest Dy_(2)O_(3)/NiOOH as the actual active species.Therefore,Dy@Ni-MOF shows impressive OER performance,significantly surpassing Ni-MOF.Besides,the overall water splitting device with Dy@NiMOF as an anode delivers a low cell voltage of 1.51 V at 10 mA cm^(-2) and demonstrates long-term stability for 100 h,positioning it as a promising substitute for precious metal catalysts.

Microwave shock motivating the Sr substitution of 2D porous GdFeO_(3) perovskite for highly active oxygen evolution

The incorporation of partial A-site substitution in perovskite oxides represents a promising strategy for precisely controlling the electronic configuration and enhancing its intrinsic catalytic activity.Conventional methods for A-site substitution typically involve prolonged high-temperature processes.While these processes promote the development of unique nanostructures with highly exposed active sites,they often result in the uncontrolled configuration of introduced elements.Herein,we present a novel approach for synthesizing two-dimensional(2D)porous GdFeO_(3) perovskite with A-site strontium(Sr)substitution utilizing microwave shock method.This technique enables precise control of the Sr content and simultaneous construction of 2D porous structures in one step,capitalizing on the advantages of rapid heating and cooling(temperature~1100 K,rate~70 K s^(-1)).The active sites of this oxygen-rich defect structure can be clearly revealed through the simulation of the electronic configuration and the comprehensive analysis of the crystal structure.For electrocatalytic oxygen evolution reaction application,the synthesized 2D porous Gd_(0.8)Sr_(0.2)FeO_(3) electrocatalyst exhibits an exceptional overpotential of 294 mV at a current density of 10 mA cm^(-2)and a small Tafel slope of 55.85 mV dec^(-1)in alkaline electrolytes.This study offers a fresh perspective on designing crystal configurations and the construction of nanostructures in perovskite.

High-speed penetration of ogive-nose projectiles into thick concrete targets:Tests and a projectile nose evolution model

The majority of the projectiles used in the hypersonic penetration study are solid flat-nosed cylindrical projectiles with a diameter of less than 20 mm.This study aims to fill the gap in the experimental and analytical study of the evolution of the nose shape of larger hollow projectiles under hypersonic penetration.In the hypersonic penetration test,eight ogive-nose AerMet100 steel projectiles with a diameter of 40 mm were launched to hit concrete targets with impact velocities that ranged from 1351 to 1877 m/s.Severe erosion of the projectiles was observed during high-speed penetration of heterogeneous targets,and apparent localized mushrooming occurred in the front nose of recovered projectiles.By examining the damage to projectiles,a linear relationship was found between the relative length reduction rate and the initial kinetic energy of projectiles in different penetration tests.Furthermore,microscopic analysis revealed the forming mechanism of the localized mushrooming phenomenon for eroding penetration,i.e.,material spall erosion abrasion mechanism,material flow and redistribution abrasion mechanism and localized radial upsetting deformation mechanism.Finally,a model of highspeed penetration that included erosion was established on the basis of a model of the evolution of the projectile nose that considers radial upsetting;the model was validated by test data from the literature and the present study.Depending upon the impact velocity,v0,the projectile nose may behave as undistorted,radially distorted or hemispherical.Due to the effects of abrasion of the projectile and enhancement of radial upsetting on the duration and amplitude of the secondary rising segment in the pulse shape of projectile deceleration,the predicted DOP had an upper limit.

Carbon Emission Effects Driven by Evolution of Chinese Dietary Structure from 1987 to 2020

Exploring carbon emission effects based on the evolution of residents’ dietary structure to achieve the carbon neutrality goal and mitigate climate change is an important task.This study took China as the research object(data excluding Hong Kong,Macao and Taiwan) and used the carbon emission coefficient method to quantitatively measure the food carbon emissions from 1987–2020,then analyzed the carbon emission effects under the evolution of dietary structure.The results showed that during the study period,the Chinese dietary structure gradually changed to a high-carbon consumption pattern.The dietary structure of urban residents developed to a balanced one,while that of rural residents developed to a high-quality one.During the study period,the per capita food carbon emissions and total food consumption of Chinese showed an increasing trend.The per capita food carbon emissions of residents in urban and rural showed an overall upward trend.The total food carbon emissions in urban increased significantly,while that in rural increased first and then decreased.The influence of beef and mutton on carbon emissions is the highest in dietary structure.Compared with the balanced dietary pattern,the food carbon emissions of Chinese residents had not yet reached the peak,but were evolving to a high-carbon consumption pattern.

Tuning electronic structure of RuO_(2)by single atom Zn and oxygen vacancies to boost oxygen evolution reaction in acidic medium

The poor stability of RuO_(2)electrocatalysts has been the primary obstacles for their practical application in polymer electrolyte membrane electrolyzers.To dramatically enhance the durability of RuO_(2)to construct activity-stability trade-off model is full of significance but challenging.Herein,a single atom Zn stabilized RuO_(2)with enriched oxygen vacancies(SA Zn-RuO_(2))is developed as a promising alternative to iridium oxide for acidic oxygen evolution reaction(OER).Compared with commercial RuO_(2),the enhanced Ru–O bond strength of SA Zn-RuO_(2)by forming Zn-O-Ru local structure motif is favorable to stabilize surface Ru,while the electrons transferred from Zn single atoms to adjacent Ru atoms protects the Ru active sites from overoxidation.Simultaneously,the optimized surrounding electronic structure of Ru sites in SA ZnRuO_(2)decreases the adsorption energies of OER intermediates to reduce the reaction barrier.As a result,the representative SA Zn-RuO_(2)exhibits a low overpotential of 210 mV to achieve 10 mA cm^(-2)and a greatly enhanced durability than commercial RuO_(2).This work provides a promising dual-engineering strategy by coupling single atom doping and vacancy for the tradeoff of high activity and catalytic stability toward acidic OER.

Evolution of microstructure and properties of a novel Ni-based superalloy during stress relief annealing

We discussed the decrease in residual stress,precipitation evolution,and mechanical properties of GH4151 alloy in different annealing temperatures,which were studied by the scanning electron microscope(SEM),high-resolution transmission electron microscopy(HRTEM),and electron backscatter diffraction(EBSD).The findings reveal that annealing processing has a significant impact on diminishing residual stresses.As the annealing temperature rose from 950 to 1150℃,the majority of the residual stresses were relieved from 60.1 MPa down to 10.9 MPa.Moreover,the stress relaxation mechanism transitioned from being mainly controlled by dislocation slip to a combination of dislocation slip and grain boundary migration.Meanwhile,the annealing treatment promotes the decomposition of the Laves,accompanied by the precipitation ofμ-(Mo_(6)Co_(7))starting at 950℃ and reaching a maximum value at 1050℃.The tensile strength and plasticity of the annealing alloy at 1150℃ reached the maximum(1394 MPa,56.1%)which was 131%,200%fold than those of the as-cast alloy(1060 MPa,26.6%),but the oxidation process in the alloy was accelerated at 1150℃.The enhancement in durability and flexibility is primarily due to the dissolution of the brittle phase,along with the shape and dispersal of theγ′phase.

Exciting lattice oxygen of nickel–iron bi-metal alkoxide for efficient electrochemical oxygen evolution reaction

High efficiency,cost-effective and durable electrocatalysts are of pivotal importance in energy conversion and storage systems.The electro-oxidation of water to oxygen plays a crucial role in such energy conversion technologies.Herein,we report a robust method for the synthesis of a bimetallic alkoxide for efficient oxygen evolution reaction(OER)for alkaline electrolysis,which yields current density of 10 mA cm^(-2)at an overpotential of 215 mV in 0.1 M KOH electrolyte.The catalyst demonstrates an excellent durability for more than 540 h operation with negligible degradation in activity.Raman spectra revealed that the catalyst underwent structure reconstruction during OER,evolving into oxyhydroxide,which was the active site proceeding OER in alkaline electrolyte.In-situ synchrotron X-ray absorption experiment combined with density functional theory calculation suggests a lattice oxygen involved electrocatalytic reaction mechanism for the in-situ generated nickel–iron bimetal-oxyhydroxide catalyst.This mechanism together with the synergy between nickel and iron are responsible for the enhanced catalytic activity and durability.These findings provide promising strategies for the rational design of nonnoble metal OER catalysts.

Damage evolution of rock-encased-backfill structure under stepwise cyclic triaxial loading

Rock-encased-backfill(RB)structures are common in underground mining,for example in the cut-andfill and stoping methods.To understand the effects of cyclic excavation and blasting activities on the damage of these RB structures,a series of triaxial stepwise-increasing-amplitude cyclic loading experiments was conducted with cylindrical RB specimens(rock on outside,backfill on inside)with different volume fractions of rock(VF=0.48,0.61,0.73,and 0.84),confining pressures(0,6,9,and 12 MPa),and cyclic loading rates(200,300,400,and 500 N/s).The damage evolution and meso-crack formation during the cyclic tests were analyzed with results from stress-strain hysteresis loops,acoustic emission events,and post-failure X-ray 3D fracture morphology.The results showed significant differences between cyclic and monotonic loadings of RB specimens,particularly with regard to the generation of shear microcracks,the development of stress memory and strain hardening,and the contact forces and associated friction that develops along the rock-backfill interface.One important finding is that as a function of the number of cycles,the elastic strain increases linearly and the dissipated energy increases exponentially.Also,compared with monotonic loading,the cyclic strain hardening characteristics are more sensitive to rising confining pressures during the initial compaction stage.Another finding is that compared with monotonic loading,more shear microcracks are generated during every reloading stage,but these microcracks tend to be dispersed and lessen the likelihood of large shear fracture formation.The transition from elastic to plastic behavior varies depending on the parameters of each test(confinement,volume fraction,and cyclic rate),and an interesting finding was that the transformation to plastic behavior is significantly lower under the conditions of 0.73 rock volume fraction,400 N/s cyclic loading rate,and 9 MPa confinement.All the findings have important practical implications on the ability of backfill to support underground excavations.

MSD-Net: Pneumonia Classification Model Based on Multi-Scale Directional Feature Enhancement

Computer-aided diagnosis of pneumonia based on deep learning is a research hotspot.However,there are some problems that the features of different sizes and different directions are not sufficient when extracting the features in lung X-ray images.A pneumonia classification model based on multi-scale directional feature enhancement MSD-Net is proposed in this paper.The main innovations are as follows:Firstly,the Multi-scale Residual Feature Extraction Module(MRFEM)is designed to effectively extract multi-scale features.The MRFEM uses dilated convolutions with different expansion rates to increase the receptive field and extract multi-scale features effectively.Secondly,the Multi-scale Directional Feature Perception Module(MDFPM)is designed,which uses a three-branch structure of different sizes convolution to transmit direction feature layer by layer,and focuses on the target region to enhance the feature information.Thirdly,the Axial Compression Former Module(ACFM)is designed to perform global calculations to enhance the perception ability of global features in different directions.To verify the effectiveness of the MSD-Net,comparative experiments and ablation experiments are carried out.In the COVID-19 RADIOGRAPHY DATABASE,the Accuracy,Recall,Precision,F1 Score,and Specificity of MSD-Net are 97.76%,95.57%,95.52%,95.52%,and 98.51%,respectively.In the chest X-ray dataset,the Accuracy,Recall,Precision,F1 Score and Specificity of MSD-Net are 97.78%,95.22%,96.49%,95.58%,and 98.11%,respectively.This model improves the accuracy of lung image recognition effectively and provides an important clinical reference to pneumonia Computer-Aided Diagnosis.

Multi-scale context-aware network for continuous sign language recognition

The hands and face are the most important parts for expressing sign language morphemes in sign language videos.However,we find that existing Continuous Sign Language Recognition(CSLR)methods lack the mining of hand and face information in visual backbones or use expensive and time-consuming external extractors to explore this information.In addition,the signs have different lengths,whereas previous CSLR methods typically use a fixed-length window to segment the video to capture sequential features and then perform global temporal modeling,which disturbs the perception of complete signs.In this study,we propose a Multi-Scale Context-Aware network(MSCA-Net)to solve the aforementioned problems.Our MSCA-Net contains two main modules:(1)Multi-Scale Motion Attention(MSMA),which uses the differences among frames to perceive information of the hands and face in multiple spatial scales,replacing the heavy feature extractors;and(2)Multi-Scale Temporal Modeling(MSTM),which explores crucial temporal information in the sign language video from different temporal scales.We conduct extensive experiments using three widely used sign language datasets,i.e.,RWTH-PHOENIX-Weather-2014,RWTH-PHOENIX-Weather-2014T,and CSL-Daily.The proposed MSCA-Net achieve state-of-the-art performance,demonstrating the effectiveness of our approach.

YOLO-MFD:Remote Sensing Image Object Detection with Multi-Scale Fusion Dynamic Head

Remote sensing imagery,due to its high altitude,presents inherent challenges characterized by multiple scales,limited target areas,and intricate backgrounds.These inherent traits often lead to increased miss and false detection rates when applying object recognition algorithms tailored for remote sensing imagery.Additionally,these complexities contribute to inaccuracies in target localization and hinder precise target categorization.This paper addresses these challenges by proposing a solution:The YOLO-MFD model(YOLO-MFD:Remote Sensing Image Object Detection withMulti-scale Fusion Dynamic Head).Before presenting our method,we delve into the prevalent issues faced in remote sensing imagery analysis.Specifically,we emphasize the struggles of existing object recognition algorithms in comprehensively capturing critical image features amidst varying scales and complex backgrounds.To resolve these issues,we introduce a novel approach.First,we propose the implementation of a lightweight multi-scale module called CEF.This module significantly improves the model’s ability to comprehensively capture important image features by merging multi-scale feature information.It effectively addresses the issues of missed detection and mistaken alarms that are common in remote sensing imagery.Second,an additional layer of small target detection heads is added,and a residual link is established with the higher-level feature extraction module in the backbone section.This allows the model to incorporate shallower information,significantly improving the accuracy of target localization in remotely sensed images.Finally,a dynamic head attentionmechanism is introduced.This allows themodel to exhibit greater flexibility and accuracy in recognizing shapes and targets of different sizes.Consequently,the precision of object detection is significantly improved.The trial results show that the YOLO-MFD model shows improvements of 6.3%,3.5%,and 2.5%over the original YOLOv8 model in Precision,map@0.5 and map@0.5:0.95,separately.These results illustrate the clear advantages of the method.

Transfer learning framework for multi-scale crack type classification with sparse microseismic networks

Rock fracture mechanisms can be inferred from moment tensors(MT)inverted from microseismic events.However,MT can only be inverted for events whose waveforms are acquired across a network of sensors.This is limiting for underground mines where the microseismic stations often lack azimuthal coverage.Thus,there is a need for a method to invert fracture mechanisms using waveforms acquired by a sparse microseismic network.Here,we present a novel,multi-scale framework to classify whether a rock crack contracts or dilates based on a single waveform.The framework consists of a deep learning model that is initially trained on 2400000+manually labelled field-scale seismic and microseismic waveforms acquired across 692 stations.Transfer learning is then applied to fine-tune the model on 300000+MT-labelled labscale acoustic emission waveforms from 39 individual experiments instrumented with different sensor layouts,loading,and rock types in training.The optimal model achieves over 86%F-score on unseen waveforms at both the lab-and field-scale.This model outperforms existing empirical methods in classification of rock fracture mechanisms monitored by a sparse microseismic network.This facilitates rapid assessment of,and early warning against,various rock engineering hazard such as induced earthquakes and rock bursts.

MSC-YOLO:Improved YOLOv7 Based on Multi-Scale Spatial Context for Small Object Detection in UAV-View

Accurately identifying small objects in high-resolution aerial images presents a complex and crucial task in thefield of small object detection on unmanned aerial vehicles(UAVs).This task is challenging due to variations inUAV flight altitude,differences in object scales,as well as factors like flight speed and motion blur.To enhancethe detection efficacy of small targets in drone aerial imagery,we propose an enhanced You Only Look Onceversion 7(YOLOv7)algorithm based on multi-scale spatial context.We build the MSC-YOLO model,whichincorporates an additional prediction head,denoted as P2,to improve adaptability for small objects.We replaceconventional downsampling with a Spatial-to-Depth Convolutional Combination(CSPDC)module to mitigatethe loss of intricate feature details related to small objects.Furthermore,we propose a Spatial Context Pyramidwith Multi-Scale Attention(SCPMA)module,which captures spatial and channel-dependent features of smalltargets acrossmultiple scales.This module enhances the perception of spatial contextual features and the utilizationof multiscale feature information.On the Visdrone2023 and UAVDT datasets,MSC-YOLO achieves remarkableresults,outperforming the baseline method YOLOv7 by 3.0%in terms ofmean average precision(mAP).The MSCYOLOalgorithm proposed in this paper has demonstrated satisfactory performance in detecting small targets inUAV aerial photography,providing strong support for practical applications.

Origin and evolution of a new tetraploid mangrove species in an intertidal zone

Polyploidy is a major factor in the evolution of plants,yet we know little about the origin and evolution of polyploidy in intertidal species.This study aimed to identify the evolutionary transitions in three truemangrove species of the genus Acanthus distributed in the Indo-West Pacific region.For this purpose,we took an integrative approach that combined data on morphology,cytology,climatic niche,phylogeny,and biogeography of 493 samples from 42 geographic sites.Our results show that the Acanthus ilicifolius lineage distributed east of the Thai-Malay Peninsula possesses a tetraploid karyotype,which is morphologically distinct from that of the lineage on the west side.The haplotype networks and phylogenetic trees for the chloroplast genome and eight nuclear genes reveal that the tetraploid species has two sub-genomes,one each from A.ilicifolius and A.ebracteatus,the paternal and maternal parents,respectively.Population structure analysis also supports the hybrid speciation history of the new tetraploid species.The two sub-genomes of the tetraploid species diverged from their diploid progenitors during the Pleistocene.Environmental niche models revealed that the tetraploid species not only occupied the near-entire niche space of the diploids,but also expanded into novel environments.Our findings suggest that A.ilicifolius species distributed on the east side of the Thai-Malay Peninsula should be regarded as a new species,A.tetraploideus,which originated from hybridization between A.ilicifolius and A.ebracteatus,followed by chromosome doubling.This is the first report of a true-mangrove allopolyploid species that can reproduce sexually and clonally reproduction,which explains the long-term adaptive potential of the species.