Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LM...Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LMRB's terrestrial water storage anomaly(TWSA)and its spatio-temporal dynamics during 2002–2020.Considering the effects of natural factors and human activities,the respective contributions of climate variability and human activities to terrestrial water storage change(TWSC)were separated.Results showed that:(1)LMRB's TWSA decreased by 0.3158 cm/a.(2)TWSA showed a gradual increase in distribution from southwest of MRB to middle LMRB and from northeast of LRB to middle LMRB.TWSA positively changed in Myanmar while slightly changed in Laos and China.It negatively changed in Vietnam,Thailand and Cambodia.(3)TWSA components decreased in a descending order of soil moisture,groundwater and precipitation.(4)Natural factors had a substantial and spatial differentiated influence on TWSA over the LMRB.(5)Climate variability contributed 79%of TWSC in the LMRB while human activities contributed 21%with an increasing impact after 2008.The TWSC of upstream basin countries was found to be controlled by climate variability while Vietnam and Cambodia's TWSC has been controlled by human activities since 2012.展开更多
Ammonia and nitric acid,versatile industrial feedstocks,and burgeoning clean energy vectors hold immense promise for sustainable development.However,Haber–Bosch and Ostwald processes,which generates carbon dioxide as...Ammonia and nitric acid,versatile industrial feedstocks,and burgeoning clean energy vectors hold immense promise for sustainable development.However,Haber–Bosch and Ostwald processes,which generates carbon dioxide as massive by-product,contribute to greenhouse effects and pose environmental challenges.Thus,the pursuit of nitrogen fixation through carbon–neutral pathways under benign conditions is a frontier of scientific topics,with the harnessing of solar energy emerging as an enticing and viable option.This review delves into the refinement strategies for scale-up mild photocatalytic nitrogen fixation,fields ripe with potential for innovation.The narrative is centered on enhancing the intrinsic capabilities of catalysts to surmount current efficiency barriers.Key focus areas include the in-depth exploration of fundamental mechanisms underpinning photocatalytic procedures,rational element selection,and functional planning,state-of-the-art experimental protocols for understanding photo-fixation processes,valid photocatalytic activity evaluation,and the rational design of catalysts.Furthermore,the review offers a suite of forward-looking recommendations aimed at propelling the advancement of mild nitrogen photo-fixation.It scrutinizes the existing challenges and prospects within this burgeoning domain,aspiring to equip researchers with insightful perspectives that can catalyze the evolution of cutting-edge nitrogen fixation methodologies and steer the development of next-generation photocatalytic systems.展开更多
The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to u...The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.展开更多
Due to the low content of alloying elements and the lack of effective nucleation sites,the fusion zone(FZ)of tungsten inert gas(TIG)welded AZ31 alloy typically exhibits undesirable coarse columnar grains,which can res...Due to the low content of alloying elements and the lack of effective nucleation sites,the fusion zone(FZ)of tungsten inert gas(TIG)welded AZ31 alloy typically exhibits undesirable coarse columnar grains,which can result in solidification defects and reduced mechanical properties.In this work,a novel welding wire containing MgO particles has been developed to promote columnar-to-equiaxed transition(CET)in the FZ of TIG-welded AZ31 alloy.The results show the achievement of a fully equiaxed grain structure in the FZ,with a significant 71.9%reduction in grain size to 41 μm from the original coarse columnar dendrites.Furthermore,the combination of using MgO-containing welding wire and pulse current can further refine the grain size to 25.6 μm.Microstructural analyses reveal the homogeneous distribution of MgO particles in the FZ.The application of pulse current results in an increase in the number density of MgO(1-2 μm)from 5.16 × 10^(4) m^(-3) to 6.18 × 10^(4) m^(-3).The good crystallographic matching relationship between MgO and α-Mg matrix,characterized by the orientation relationship of[11(2)0]α-Mg//[0(1)1]MgO and(0002)_(α-Mg)//(111)_(MgO),indicates that the MgO particles can act as effective nucleation sites for α-Mg to reduce nucleation undercooling.According to the Hunt criteria,the critical temperature gradient for CET is greatly enhanced due to the significantly increased number density of MgO nucleation sites.In addition,the correlation with the thermal simulation results reveals a transition in the solidification conditions within the welding pool from the columnar grain zone to the equiaxed grain zone in the CET map,leading to the realization of CET.The exceptional grain refinement has contributed to a simultaneous improvement in the strength and plasticity of welded joints.This study presents a novel strategy for controlling equiaxed microstructure and optimizing mechanical properties in fusion welding or wire and arc additive manufacturing of Mg alloy components.展开更多
Al-Cu-Mg-Ag alloys have become a research hotspot because of its good heat resistance.Its excellent mechanical properties are inseparable from the regulation of the structure by researchers.The method of material stru...Al-Cu-Mg-Ag alloys have become a research hotspot because of its good heat resistance.Its excellent mechanical properties are inseparable from the regulation of the structure by researchers.The method of material structure simulation has become more and more perfect.This study employs numerical simulation to investigate the microstructure evolution of Al-Cu-Mg-Ag alloys during solidification with the aim of controlling its structure.The size distribution of Ti-containing particles in an Al-Ti-B master alloy was characterized via microstructure observation,serving as a basis for optimizing the nucleation density parameters for particles of varying radii in the phase field model.The addition of refiner inhibited the growth of dendrites and no longer produced coarse dendrites.With the increase of refiner,the grains gradually tended to form cellular morphology.The refined grains were about 100μm in size.Experimental validation of the simulated as-cast grain morphology was conducted.The samples were observed by metallographic microscope and scanning electron microscope.The addition of refiner had a significant effect on the refinement of the alloy,and the average grain size after refinement was also about 100μm.At the same time,the XRD phase identification of the alloy was carried out.The observation of the microstructure morphology under the scanning electron microscope showed that the precipitated phase was mainly concentrated on the grain boundary.The Al_(2)Cu accounted for about 5%,and the matrix phase FCC accounted for about 95%,which also corresponded well with the simulation results.展开更多
Objective To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis(TB)in the Guangdong Province between 2010 and 2019.Method Spatial and temporal variations in TB ...Objective To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis(TB)in the Guangdong Province between 2010 and 2019.Method Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering.Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive(ST-CAR)model.Results Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000in 2019.Spatial hotspots were found in northeastern Guangdong,particularly in Heyuan,Shanwei,and Shantou,while Shenzhen,Dongguan,and Foshan had the lowest rates in the Pearl River Delta.The STCAR model showed that the TB risk was lower with higher per capita Gross Domestic Product(GDP)[Relative Risk(RR),0.91;95%Confidence Interval(CI):0.86–0.98],more the ratio of licensed physicians and physician(RR,0.94;95%CI:0.90-0.98),and higher per capita public expenditure(RR,0.94;95%CI:0.90–0.97),with a marginal effect of population density(RR,0.86;95%CI:0.86–1.00).Conclusion The incidence of TB in Guangdong varies spatially and temporally.Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection.Strategies focusing on equitable health resource distribution and economic development are the key to TB control.展开更多
This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in So...This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in Sonipat have undergone notable transformation,as open spaces and agricultural lands are increasingly converted into residential colonies,commercial hubs,and industrial zones.While such changes reflect economic development and urban growth,they also raise critical concerns about sustainability,especially in terms of food security,groundwater depletion,and environmental degradation.The study examines land use changes between 2000 and 2024 using remote sensing techniques and spatial analysis.It further incorporates secondary data and insights from community-level interactions to assess the socio-economic and ecological impacts of this transformation.The findings indicate rising land fragmentation,loss of agricultural livelihoods,pressure on civic infrastructure,and increasing pollution—factors that threaten long-term regional sustainability.The study underscores the urgent need to reconcile urban development with environmental and social sustainability.By offering a detailed case study of Sonipat,this research contributes to the broader discourse on India’s urbanisation pathways.It aims to provide policymakers,planners,and researchers with evidence-based recommendations to manage land transitions more responsibly,promoting urban growth models that ensure ecological integrity,equitable development,and long-term resilience.展开更多
As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limi...As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limits their ability to capture temporal differences between frames.Current methods also exhibit limited generalization capabilities,struggling to detect content generated by unknown forgery algorithms.Moreover,the diversity and complexity of forgery techniques introduced by Artificial Intelligence Generated Content(AIGC)present significant challenges for traditional detection frameworks,whichmust balance high detection accuracy with robust performance.To address these challenges,we propose a novel Deepfake detection framework that combines a two-stream convolutional network with a Vision Transformer(ViT)module to enhance spatio-temporal feature representation.The ViT model extracts spatial features from the forged video,while the 3D convolutional network captures temporal features.The 3D convolution enables cross-frame feature extraction,allowing the model to detect subtle facial changes between frames.The confidence scores from both the ViT and 3D convolution submodels are fused at the decision layer,enabling themodel to effectively handle unknown forgery techniques.Focusing on Deepfake videos and GAN-generated images,the proposed approach is evaluated on two widely used public face forgery datasets.Compared to existing state-of-theartmethods,it achieves higher detection accuracy and better generalization performance,offering a robust solution for deepfake detection in real-world scenarios.展开更多
Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decode...Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decoder (ACSF-ED) network to predict the action and locate the object efficiently. In the Adaptive Cross-Scale Fusion Spatio-Temporal Encoder (ACSF ST-Encoder), the Asymptotic Cross-scale Feature-fusion Module (ACCFM) is designed to address the issue of information degradation caused by the propagation of high-level semantic information, thereby extracting high-quality multi-scale features to provide superior features for subsequent spatio-temporal information modeling. Within the Shared-Head Decoder structure, a shared classification and regression detection head is constructed. A multi-constraint loss function composed of one-to-one, one-to-many, and contrastive denoising losses is designed to address the problem of insufficient constraint force in predicting results with traditional methods. This loss function enhances the accuracy of model classification predictions and improves the proximity of regression position predictions to ground truth objects. The proposed method model is evaluated on the popular dataset UCF101-24 and JHMDB-21. Experimental results demonstrate that the proposed method achieves an accuracy of 81.52% on the Frame-mAP metric, surpassing current existing methods.展开更多
Electrocardiogram (ECG) analysis is critical for detecting arrhythmias, but traditional methods struggle with large-scale Electrocardiogram data and rare arrhythmia events in imbalanced datasets. These methods fail to...Electrocardiogram (ECG) analysis is critical for detecting arrhythmias, but traditional methods struggle with large-scale Electrocardiogram data and rare arrhythmia events in imbalanced datasets. These methods fail to perform multi-perspective learning of temporal signals and Electrocardiogram images, nor can they fully extract the latent information within the data, falling short of the accuracy required by clinicians. Therefore, this paper proposes an innovative hybrid multimodal spatiotemporal neural network to address these challenges. The model employs a multimodal data augmentation framework integrating visual and signal-based features to enhance the classification performance of rare arrhythmias in imbalanced datasets. Additionally, the spatiotemporal fusion module incorporates a spatiotemporal graph convolutional network to jointly model temporal and spatial features, uncovering complex dependencies within the Electrocardiogram data and improving the model’s ability to represent complex patterns. In experiments conducted on the MIT-BIH arrhythmia dataset, the model achieved 99.95% accuracy, 99.80% recall, and a 99.78% F1 score. The model was further validated for generalization using the clinical INCART arrhythmia dataset, and the results demonstrated its effectiveness in terms of both generalization and robustness.展开更多
The phase field model can coherently address the relatively complex fracture phenomenon,such as crack nucleation,branching,deflection,etc.The model has been extensively implemented in the finite element package Abaqus...The phase field model can coherently address the relatively complex fracture phenomenon,such as crack nucleation,branching,deflection,etc.The model has been extensively implemented in the finite element package Abaqus to solve brittle fracture problems in recent studies.However,accurate numerical analysis typically requires fine meshes to model the evolving crack path effectively.A broad region must be discretized without prior knowledge of the crack path,further augmenting the computational expenses.In this proposed work,we present an automated framework utilizing a posteriori error-indicator(MISESERI)to demarcate and sufficiently refine the mesh along the anticipated crack path.This eliminates the need for manual mesh refinement based on previous experimental/computational results or heuristic judgment.The proposed Python-based framework integrates the preanalysis,sufficient mesh refinement,and subsequent phase-field model-based numerical analysis with user-defined subroutines in a single streamlined pass.The novelty of the proposed work lies in integrating Abaqus’s native error estimation and mesh refinement capability,tailored explicitly for phase-field simulations.The proposed methodology aims to reduce the computational resource requirement,thereby enhancing the efficiency of the phase-field simulations while preserving the solution accuracy,making the framework particularly advantageous for complex fracture problems where the computational/experimental results are limited or unavailable.Several benchmark numerical problems are solved to showcase the effectiveness and accuracy of the proposed approach.The numerical examples present the proposed approach’s efficacy in the case of a complex mixed-mode fracture problem.The results show significant reductions in computational resources compared to traditional phase-field methods,which is promising.展开更多
The Fe–Mn damping alloys possess considerable damping capacity,but their yield strength is rather low.The 800 MPa Fe–Mn alloy with expected damping capacity was designed by the combination of grain refinement and ε...The Fe–Mn damping alloys possess considerable damping capacity,but their yield strength is rather low.The 800 MPa Fe–Mn alloy with expected damping capacity was designed by the combination of grain refinement and ε-martensite introduction.The yield strength can be greatly raised to around 700 MPa by refining grain size from 88.4 to 1.8μm.Although there exist numerous stacking faults in the fine-grained alloy,the damping capacity is strongly deteriorated due to the suppression of thermally activated ε-martensite.We demonstrate that the stacking faults cannot provide effective contribution to damping capacity and hence introduce a considerable volume fraction of stress/strain-induced ε-martensite to raise damping sources,including ε-martensite and γ/ε interfaces,etc.,by a small pre-strain.From this,the damping capacity can be improved,and the yield strength can be further enhanced from nearly 700 MPa to around 800 MPa.Thus,the combination of high yield strength and good damping capacity is realized.展开更多
Exploring the spatial evolution patterns of land use in creative urban tourism complexes provides theoretical and decision-making support to foster creative tourism projects.This study focuses on the Hangzhou Leisure ...Exploring the spatial evolution patterns of land use in creative urban tourism complexes provides theoretical and decision-making support to foster creative tourism projects.This study focuses on the Hangzhou Leisure Expo Garden as a case study,utilizing a land use change index model to analyze the spatial evolution characteristics and dynamic processes of creative urban tourism complexes,as well as to explore their spatial differentiation mechanisms.The analysis indicates that Hangzhou Leisure Expo Garden,initially a derelict industrial area dominated by production and residential land use,has evolved into a creative urban tourism complex with tourism comprehensive service land at its core,going through the pattern evolution processes of“constrained sprawl,”“intensive expansion,”and“random integration.”From the perspective of tourism human-land relationships,the formation of land use evolution patterns in creative urban tourism complexes results from various stakeholders(government,tourism enterprises,residents,tourists,etc.),as humanistic factors,continuously adapting to specific urban spaces,which are considered as geographical elements and have locational advantages and are oriented towards economic and social values.Based on the acquisition of stakeholder interests,the transformation of resource-disadvantaged areas into tourism advantage areas is facilitated,thereby achieving the re-creation of tourism creative space and promoting intensive spatial growth.展开更多
Strong sensitivity of satellite microwave remote sensing to the change of surface dielectric properties,as well as the insensitivity to air pollution and solar illumination effects,makes it very suitable for monitorin...Strong sensitivity of satellite microwave remote sensing to the change of surface dielectric properties,as well as the insensitivity to air pollution and solar illumination effects,makes it very suitable for monitoring freeze-thaw conditions.The freeze-thaw cycle changes in the Qinghai-Xizang Plateau have an important impact on the ecological environment and infrastructure.Based on the Scanning Multi-channel Microwave Radiometer(SMMR)and other sensors of microwave satellite,the freeze-thaw cycle data of permafrost in the Qinghai-Xizang Plateau in the past 40 years from 1981 to 2020 was obtained.The changes of soil freeze-thaw conditions in different seasons of 2020 and in the same season of 1990,2000,2010 and 2020 were compared,and the annual variation trend of soil freeze-thaw area in the four years was analyzed.Further,the linear regression analysis was carried out on the duration of soil freezing/thawing/transition and the interannual variation trend under different area conditions from 1981 to 2020.The results show that the freeze-thaw changes in different years are similar.In winter,it is mainly frozen for about 110 days.Spring and autumn are transitional periods,lasting for 170 days.In summer,it is mainly thawed for about 80 days.From 1981 to 2020,the freezing period and the average freezing area of the Qinghai-Xizang Plateau decreased at a rate of 0.22 days and 1986 km^(2) per year,respectively,while the thawing period and the average thawing area increased at a rate of 0.07 days and 3187 km^(2) per year,respectively.The research results provide important theoretical support for the ecological environment and permafrost protection of the Qinghai-Xizang Plateau.展开更多
False Data Injection Attacks(FDIAs)pose a critical security threat to modern power grids,corrupting state estimation and enabling malicious control actions that can lead to severe consequences,including cascading fail...False Data Injection Attacks(FDIAs)pose a critical security threat to modern power grids,corrupting state estimation and enabling malicious control actions that can lead to severe consequences,including cascading failures,large-scale blackouts,and significant economic losses.While detecting attacks is important,accurately localizing compromised nodes or measurements is even more critical,as it enables timely mitigation,targeted response,and enhanced system resilience beyond what detection alone can offer.Existing research typically models topological features using fixed structures,which can introduce irrelevant information and affect the effectiveness of feature extraction.To address this limitation,this paper proposes an FDIA localization model with adaptive neighborhood selection,which dynamically captures spatial dependencies of the power grid by adjusting node relationships based on data-driven similarities.The improved Transformer is employed to pre-fuse global spatial features of the graph,enriching the feature representation.To improve spatio-temporal correlation extraction for FDIA localization,the proposed model employs dilated causal convolution with a gating mechanism combined with graph convolution to capture and fuse long-range temporal features and adaptive topological features.This fully exploits the temporal dynamics and spatial dependencies inherent in the power grid.Finally,multi-source information is integrated to generate highly robust node embeddings,enhancing FDIA detection and localization.Experiments are conducted on IEEE 14,57,and 118-bus systems,and the results demonstrate that the proposed model substantially improves the accuracy of FDIA localization.Additional experiments are conducted to verify the effectiveness and robustness of the proposed model.展开更多
This study investigated the effect of Si addition on the microstructure and the silicide precipitation behavior in a novel near-βtitanium alloy.The results show that coarse and continuous silicides were preferentiall...This study investigated the effect of Si addition on the microstructure and the silicide precipitation behavior in a novel near-βtitanium alloy.The results show that coarse and continuous silicides were preferentially precipitated at the grain boundary during the solidification process,and theβgrain size of the as-cast alloy was refined.Dynamic recrystallization occurs under isothermal compression,and the silicide could inhibit the growth of recrystallized grains.The element redistribution and dislocation accumulation during hot deformation promote the dynamic precipitation of silicide,resulting in a discontinuous distribution of silicides at the grain boundaries.This work provides insight into how silicide dynamic precipitation will affect the microstructure and plastic deformation behavior of metal alloys.展开更多
Depth maps play a crucial role in various practical applications such as computer vision,augmented reality,and autonomous driving.How to obtain clear and accurate depth information in video depth estimation is a signi...Depth maps play a crucial role in various practical applications such as computer vision,augmented reality,and autonomous driving.How to obtain clear and accurate depth information in video depth estimation is a significant challenge faced in the field of computer vision.However,existing monocular video depth estimation models tend to produce blurred or inaccurate depth information in regions with object edges and low texture.To address this issue,we propose a monocular depth estimation model architecture guided by semantic segmentation masks,which introduces semantic information into the model to correct the ambiguous depth regions.We have evaluated the proposed method,and experimental results show that our method improves the accuracy of edge depth,demonstrating the effectiveness of our approach.展开更多
The fatigue life of components can be significantly enhanced by the formation of the surface hardness layer through surface strengthening technology.To avoid the geometric distortion of thin-walled com-ponents caused ...The fatigue life of components can be significantly enhanced by the formation of the surface hardness layer through surface strengthening technology.To avoid the geometric distortion of thin-walled com-ponents caused by strengthening,the strengthening energy is limited and the ideal strengthening effect cannot be obtained.This work aims to propose a novel approach to address this issue effectively.The surface layer with high-density dislocations was obtained by a low-energy surface strengthening method(shot peening)at first.Then the surface strengthening mechanism changes from dislocation strengthen-ing to grain boundary strengthening after electropulsing treatment(EPT).The evolution of residual stress and microstructure was analyzed using multi-scale characterization techniques.The results demonstrate that EPT followed by surface strengthening makes a remarkable 304%increase in fatigue life of TC11 titanium alloy.The enhancement of fatigue life can be attributed to the grain refinement accompanied by the formation of nanotwins and sub-grains in the surface-strengthened layer,as well as the reduction in dislocation density within the substrate after EPT.This study demonstrates the significant potential of EPT in further enhancing the fatigue life of surface pre-strengthened thin-walled components.展开更多
This study investigates zinc’s(Zn)key role in enhancing the precipitation kinetics and refinement of Mg_(17)Al_(12)and Mg_(2)Sn phases in magnesium alloys through trace sodium(Na)additions.Magnesium alloys with varyi...This study investigates zinc’s(Zn)key role in enhancing the precipitation kinetics and refinement of Mg_(17)Al_(12)and Mg_(2)Sn phases in magnesium alloys through trace sodium(Na)additions.Magnesium alloys with varying compositions of aluminum(Al),tin(Sn),Zn,and Na were prepared and aged at 453 K.Microstructural analyses were conducted using transmission electron microscopy(TEM),scanning transmission electron microscopy(STEM),and atom probe tomography(APT).Trace additions of Na significantly enhanced the precipitation responses of both Mg_(17)Al_(12)and Mg_(2)Sn phases.When Zn was co-added with Na,as in the ATZ641N3 alloy(Mg–6Al–4Sn–1Zn–0.3Na),there was a pronounced refinement in precipitate morphology and acceleration of precipitation kinetics.The ATZ641N3 alloy achieved a peak hardness of 103 Hv at 36 hours,compared to 91 Hv at 72 hours for the ATZ641 alloy without Na.The simultaneous addition of Zn and Na led to the formation of Sn–Na–Zn particles that acted as effective nucleation sites for Mg_(2)Sn,promoting aluminum partitioning and accelerating the precipitation of Mg_(17)Al_(12)through Al-rich regions.Additionally,Zn and Na co-segregated within the Mg_(17)Al_(12)phase,reducing misfit strain caused by Zn substitution and improving precipitate stability and refinement.These findings highlight Zn’s critical role,alongside trace Na additions,in refining and accelerating the precipitation of Mg_(17)Al_(12)and Mg_(2)Sn phases,thereby enhancing the age-hardening response of magnesium alloys.展开更多
Based on thermodynamic calculations and continuous rheological extrusion(CRE)technology,Al-Ti-V-B master alloys were designed and prepared.The morphology and the distribution of the refined phases in the master alloys...Based on thermodynamic calculations and continuous rheological extrusion(CRE)technology,Al-Ti-V-B master alloys were designed and prepared.The morphology and the distribution of the refined phases in the master alloys were analyzed by XRD,SEM,and TEM.The effects of master alloy addition and holding time on the microstructure and mechanical properties of A356 alloy were investigated.Under the optimum refiner addition of 0.3wt.%and the holding time of 20 min,the average grain size of the refined A356 alloy is 151.8±9.11μm,89.62%lower than that of original A356 alloy.The tensile strength and elongation of as-cast A356refined alloy are 196.11 MPa and 5.75%,respectively.After T6 treatment,the tensile strength and elongation of A356 refined alloy are 290.1 MPa and 3.09%,respectively.The fracture morphology is characterized by a predominance of along-crystal fracture with a small amount of through-crystal fracture,attributed to the refined grains.Finer grains promote crack path deflection and localized plastic deformation,enhancing energy dissipation and reducing the tendency for brittle fracture.This study provides a novel approach to improving the mechanical properties of A356 alloy through grain refinement using CRE Al-Ti-V-B master alloy.展开更多
基金National Natural Science Foundation of China,No.42161006Yunnan Fundamental Research Projects No.202201AT070094,No.202301BF070001-004+1 种基金Special Project for High-level Talents of Yunnan Province for Young Top Talents,No.C6213001159European Research Council(ERC)Starting-Grant STORIES,No.101040939。
文摘Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LMRB's terrestrial water storage anomaly(TWSA)and its spatio-temporal dynamics during 2002–2020.Considering the effects of natural factors and human activities,the respective contributions of climate variability and human activities to terrestrial water storage change(TWSC)were separated.Results showed that:(1)LMRB's TWSA decreased by 0.3158 cm/a.(2)TWSA showed a gradual increase in distribution from southwest of MRB to middle LMRB and from northeast of LRB to middle LMRB.TWSA positively changed in Myanmar while slightly changed in Laos and China.It negatively changed in Vietnam,Thailand and Cambodia.(3)TWSA components decreased in a descending order of soil moisture,groundwater and precipitation.(4)Natural factors had a substantial and spatial differentiated influence on TWSA over the LMRB.(5)Climate variability contributed 79%of TWSC in the LMRB while human activities contributed 21%with an increasing impact after 2008.The TWSC of upstream basin countries was found to be controlled by climate variability while Vietnam and Cambodia's TWSC has been controlled by human activities since 2012.
基金financially supported by the National Natural Science Foundation of China(No.21675131)the Volkswagen Foundation(Freigeist Fellowship No.89592)+1 种基金the Natural Science Foundation of Chongqing(No.2020jcyj-zdxmX0003,CSTB2023NSCQ-MSX0924)the National Research Foundation,Singapore,and A*STAR(Agency for Science Technology and Research)under its LCER Phase 2 Programme Hydrogen&Emerging Technologies FI,Directed Hydrogen Programme(Award No.U2305D4003).
文摘Ammonia and nitric acid,versatile industrial feedstocks,and burgeoning clean energy vectors hold immense promise for sustainable development.However,Haber–Bosch and Ostwald processes,which generates carbon dioxide as massive by-product,contribute to greenhouse effects and pose environmental challenges.Thus,the pursuit of nitrogen fixation through carbon–neutral pathways under benign conditions is a frontier of scientific topics,with the harnessing of solar energy emerging as an enticing and viable option.This review delves into the refinement strategies for scale-up mild photocatalytic nitrogen fixation,fields ripe with potential for innovation.The narrative is centered on enhancing the intrinsic capabilities of catalysts to surmount current efficiency barriers.Key focus areas include the in-depth exploration of fundamental mechanisms underpinning photocatalytic procedures,rational element selection,and functional planning,state-of-the-art experimental protocols for understanding photo-fixation processes,valid photocatalytic activity evaluation,and the rational design of catalysts.Furthermore,the review offers a suite of forward-looking recommendations aimed at propelling the advancement of mild nitrogen photo-fixation.It scrutinizes the existing challenges and prospects within this burgeoning domain,aspiring to equip researchers with insightful perspectives that can catalyze the evolution of cutting-edge nitrogen fixation methodologies and steer the development of next-generation photocatalytic systems.
文摘The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction tasks.The comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest accuracy.On the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 min.Similarly,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer periods.The Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time intervals.These numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.
基金supported by the National Natural Science Foundation of China(No.51871155).
文摘Due to the low content of alloying elements and the lack of effective nucleation sites,the fusion zone(FZ)of tungsten inert gas(TIG)welded AZ31 alloy typically exhibits undesirable coarse columnar grains,which can result in solidification defects and reduced mechanical properties.In this work,a novel welding wire containing MgO particles has been developed to promote columnar-to-equiaxed transition(CET)in the FZ of TIG-welded AZ31 alloy.The results show the achievement of a fully equiaxed grain structure in the FZ,with a significant 71.9%reduction in grain size to 41 μm from the original coarse columnar dendrites.Furthermore,the combination of using MgO-containing welding wire and pulse current can further refine the grain size to 25.6 μm.Microstructural analyses reveal the homogeneous distribution of MgO particles in the FZ.The application of pulse current results in an increase in the number density of MgO(1-2 μm)from 5.16 × 10^(4) m^(-3) to 6.18 × 10^(4) m^(-3).The good crystallographic matching relationship between MgO and α-Mg matrix,characterized by the orientation relationship of[11(2)0]α-Mg//[0(1)1]MgO and(0002)_(α-Mg)//(111)_(MgO),indicates that the MgO particles can act as effective nucleation sites for α-Mg to reduce nucleation undercooling.According to the Hunt criteria,the critical temperature gradient for CET is greatly enhanced due to the significantly increased number density of MgO nucleation sites.In addition,the correlation with the thermal simulation results reveals a transition in the solidification conditions within the welding pool from the columnar grain zone to the equiaxed grain zone in the CET map,leading to the realization of CET.The exceptional grain refinement has contributed to a simultaneous improvement in the strength and plasticity of welded joints.This study presents a novel strategy for controlling equiaxed microstructure and optimizing mechanical properties in fusion welding or wire and arc additive manufacturing of Mg alloy components.
文摘Al-Cu-Mg-Ag alloys have become a research hotspot because of its good heat resistance.Its excellent mechanical properties are inseparable from the regulation of the structure by researchers.The method of material structure simulation has become more and more perfect.This study employs numerical simulation to investigate the microstructure evolution of Al-Cu-Mg-Ag alloys during solidification with the aim of controlling its structure.The size distribution of Ti-containing particles in an Al-Ti-B master alloy was characterized via microstructure observation,serving as a basis for optimizing the nucleation density parameters for particles of varying radii in the phase field model.The addition of refiner inhibited the growth of dendrites and no longer produced coarse dendrites.With the increase of refiner,the grains gradually tended to form cellular morphology.The refined grains were about 100μm in size.Experimental validation of the simulated as-cast grain morphology was conducted.The samples were observed by metallographic microscope and scanning electron microscope.The addition of refiner had a significant effect on the refinement of the alloy,and the average grain size after refinement was also about 100μm.At the same time,the XRD phase identification of the alloy was carried out.The observation of the microstructure morphology under the scanning electron microscope showed that the precipitated phase was mainly concentrated on the grain boundary.The Al_(2)Cu accounted for about 5%,and the matrix phase FCC accounted for about 95%,which also corresponded well with the simulation results.
基金supported by the Guangdong Provincial Clinical Research Center for Tuberculosis(No.2020B1111170014)。
文摘Objective To investigate the spatiotemporal patterns and socioeconomic factors influencing the incidence of tuberculosis(TB)in the Guangdong Province between 2010 and 2019.Method Spatial and temporal variations in TB incidence were mapped using heat maps and hierarchical clustering.Socioenvironmental influencing factors were evaluated using a Bayesian spatiotemporal conditional autoregressive(ST-CAR)model.Results Annual incidence of TB in Guangdong decreased from 91.85/100,000 in 2010 to 53.06/100,000in 2019.Spatial hotspots were found in northeastern Guangdong,particularly in Heyuan,Shanwei,and Shantou,while Shenzhen,Dongguan,and Foshan had the lowest rates in the Pearl River Delta.The STCAR model showed that the TB risk was lower with higher per capita Gross Domestic Product(GDP)[Relative Risk(RR),0.91;95%Confidence Interval(CI):0.86–0.98],more the ratio of licensed physicians and physician(RR,0.94;95%CI:0.90-0.98),and higher per capita public expenditure(RR,0.94;95%CI:0.90–0.97),with a marginal effect of population density(RR,0.86;95%CI:0.86–1.00).Conclusion The incidence of TB in Guangdong varies spatially and temporally.Areas with poor economic conditions and insufficient healthcare resources are at an increased risk of TB infection.Strategies focusing on equitable health resource distribution and economic development are the key to TB control.
文摘This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in Sonipat have undergone notable transformation,as open spaces and agricultural lands are increasingly converted into residential colonies,commercial hubs,and industrial zones.While such changes reflect economic development and urban growth,they also raise critical concerns about sustainability,especially in terms of food security,groundwater depletion,and environmental degradation.The study examines land use changes between 2000 and 2024 using remote sensing techniques and spatial analysis.It further incorporates secondary data and insights from community-level interactions to assess the socio-economic and ecological impacts of this transformation.The findings indicate rising land fragmentation,loss of agricultural livelihoods,pressure on civic infrastructure,and increasing pollution—factors that threaten long-term regional sustainability.The study underscores the urgent need to reconcile urban development with environmental and social sustainability.By offering a detailed case study of Sonipat,this research contributes to the broader discourse on India’s urbanisation pathways.It aims to provide policymakers,planners,and researchers with evidence-based recommendations to manage land transitions more responsibly,promoting urban growth models that ensure ecological integrity,equitable development,and long-term resilience.
基金supported by National Natural Science Foundation of China(Nos.62477026,62177029,61807020)Humanities and Social Sciences Research Program of the Ministry of Education of China(No.23YJAZH047)the Startup Foundation for Introducing Talent of Nanjing University of Posts and Communications under Grant NY222034.
文摘As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limits their ability to capture temporal differences between frames.Current methods also exhibit limited generalization capabilities,struggling to detect content generated by unknown forgery algorithms.Moreover,the diversity and complexity of forgery techniques introduced by Artificial Intelligence Generated Content(AIGC)present significant challenges for traditional detection frameworks,whichmust balance high detection accuracy with robust performance.To address these challenges,we propose a novel Deepfake detection framework that combines a two-stream convolutional network with a Vision Transformer(ViT)module to enhance spatio-temporal feature representation.The ViT model extracts spatial features from the forged video,while the 3D convolutional network captures temporal features.The 3D convolution enables cross-frame feature extraction,allowing the model to detect subtle facial changes between frames.The confidence scores from both the ViT and 3D convolution submodels are fused at the decision layer,enabling themodel to effectively handle unknown forgery techniques.Focusing on Deepfake videos and GAN-generated images,the proposed approach is evaluated on two widely used public face forgery datasets.Compared to existing state-of-theartmethods,it achieves higher detection accuracy and better generalization performance,offering a robust solution for deepfake detection in real-world scenarios.
基金support for this work was supported by Key Lab of Intelligent and Green Flexographic Printing under Grant ZBKT202301.
文摘Current spatio-temporal action detection methods lack sufficient capabilities in extracting and comprehending spatio-temporal information. This paper introduces an end-to-end Adaptive Cross-Scale Fusion Encoder-Decoder (ACSF-ED) network to predict the action and locate the object efficiently. In the Adaptive Cross-Scale Fusion Spatio-Temporal Encoder (ACSF ST-Encoder), the Asymptotic Cross-scale Feature-fusion Module (ACCFM) is designed to address the issue of information degradation caused by the propagation of high-level semantic information, thereby extracting high-quality multi-scale features to provide superior features for subsequent spatio-temporal information modeling. Within the Shared-Head Decoder structure, a shared classification and regression detection head is constructed. A multi-constraint loss function composed of one-to-one, one-to-many, and contrastive denoising losses is designed to address the problem of insufficient constraint force in predicting results with traditional methods. This loss function enhances the accuracy of model classification predictions and improves the proximity of regression position predictions to ground truth objects. The proposed method model is evaluated on the popular dataset UCF101-24 and JHMDB-21. Experimental results demonstrate that the proposed method achieves an accuracy of 81.52% on the Frame-mAP metric, surpassing current existing methods.
基金supported by The Henan Province Science and Technology Research Project(242102211046)the Key Scientific Research Project of Higher Education Institutions in Henan Province(25A520039)+1 种基金theNatural Science Foundation project of Zhongyuan Institute of Technology(K2025YB011)the Zhongyuan University of Technology Graduate Education and Teaching Reform Research Project(JG202424).
文摘Electrocardiogram (ECG) analysis is critical for detecting arrhythmias, but traditional methods struggle with large-scale Electrocardiogram data and rare arrhythmia events in imbalanced datasets. These methods fail to perform multi-perspective learning of temporal signals and Electrocardiogram images, nor can they fully extract the latent information within the data, falling short of the accuracy required by clinicians. Therefore, this paper proposes an innovative hybrid multimodal spatiotemporal neural network to address these challenges. The model employs a multimodal data augmentation framework integrating visual and signal-based features to enhance the classification performance of rare arrhythmias in imbalanced datasets. Additionally, the spatiotemporal fusion module incorporates a spatiotemporal graph convolutional network to jointly model temporal and spatial features, uncovering complex dependencies within the Electrocardiogram data and improving the model’s ability to represent complex patterns. In experiments conducted on the MIT-BIH arrhythmia dataset, the model achieved 99.95% accuracy, 99.80% recall, and a 99.78% F1 score. The model was further validated for generalization using the clinical INCART arrhythmia dataset, and the results demonstrated its effectiveness in terms of both generalization and robustness.
文摘The phase field model can coherently address the relatively complex fracture phenomenon,such as crack nucleation,branching,deflection,etc.The model has been extensively implemented in the finite element package Abaqus to solve brittle fracture problems in recent studies.However,accurate numerical analysis typically requires fine meshes to model the evolving crack path effectively.A broad region must be discretized without prior knowledge of the crack path,further augmenting the computational expenses.In this proposed work,we present an automated framework utilizing a posteriori error-indicator(MISESERI)to demarcate and sufficiently refine the mesh along the anticipated crack path.This eliminates the need for manual mesh refinement based on previous experimental/computational results or heuristic judgment.The proposed Python-based framework integrates the preanalysis,sufficient mesh refinement,and subsequent phase-field model-based numerical analysis with user-defined subroutines in a single streamlined pass.The novelty of the proposed work lies in integrating Abaqus’s native error estimation and mesh refinement capability,tailored explicitly for phase-field simulations.The proposed methodology aims to reduce the computational resource requirement,thereby enhancing the efficiency of the phase-field simulations while preserving the solution accuracy,making the framework particularly advantageous for complex fracture problems where the computational/experimental results are limited or unavailable.Several benchmark numerical problems are solved to showcase the effectiveness and accuracy of the proposed approach.The numerical examples present the proposed approach’s efficacy in the case of a complex mixed-mode fracture problem.The results show significant reductions in computational resources compared to traditional phase-field methods,which is promising.
基金supported by Fundamental Research Funds for Central Universities(Grant No.N2107009)Reviving-Liaoning Excellence Plan(Grant No.XLYC2203186).
文摘The Fe–Mn damping alloys possess considerable damping capacity,but their yield strength is rather low.The 800 MPa Fe–Mn alloy with expected damping capacity was designed by the combination of grain refinement and ε-martensite introduction.The yield strength can be greatly raised to around 700 MPa by refining grain size from 88.4 to 1.8μm.Although there exist numerous stacking faults in the fine-grained alloy,the damping capacity is strongly deteriorated due to the suppression of thermally activated ε-martensite.We demonstrate that the stacking faults cannot provide effective contribution to damping capacity and hence introduce a considerable volume fraction of stress/strain-induced ε-martensite to raise damping sources,including ε-martensite and γ/ε interfaces,etc.,by a small pre-strain.From this,the damping capacity can be improved,and the yield strength can be further enhanced from nearly 700 MPa to around 800 MPa.Thus,the combination of high yield strength and good damping capacity is realized.
文摘Exploring the spatial evolution patterns of land use in creative urban tourism complexes provides theoretical and decision-making support to foster creative tourism projects.This study focuses on the Hangzhou Leisure Expo Garden as a case study,utilizing a land use change index model to analyze the spatial evolution characteristics and dynamic processes of creative urban tourism complexes,as well as to explore their spatial differentiation mechanisms.The analysis indicates that Hangzhou Leisure Expo Garden,initially a derelict industrial area dominated by production and residential land use,has evolved into a creative urban tourism complex with tourism comprehensive service land at its core,going through the pattern evolution processes of“constrained sprawl,”“intensive expansion,”and“random integration.”From the perspective of tourism human-land relationships,the formation of land use evolution patterns in creative urban tourism complexes results from various stakeholders(government,tourism enterprises,residents,tourists,etc.),as humanistic factors,continuously adapting to specific urban spaces,which are considered as geographical elements and have locational advantages and are oriented towards economic and social values.Based on the acquisition of stakeholder interests,the transformation of resource-disadvantaged areas into tourism advantage areas is facilitated,thereby achieving the re-creation of tourism creative space and promoting intensive spatial growth.
基金National Natural Science foundation of China(No.42271432)Foundation of Shanxi Vocational University of Engineering Science and Technology(No.KJ 202426).
文摘Strong sensitivity of satellite microwave remote sensing to the change of surface dielectric properties,as well as the insensitivity to air pollution and solar illumination effects,makes it very suitable for monitoring freeze-thaw conditions.The freeze-thaw cycle changes in the Qinghai-Xizang Plateau have an important impact on the ecological environment and infrastructure.Based on the Scanning Multi-channel Microwave Radiometer(SMMR)and other sensors of microwave satellite,the freeze-thaw cycle data of permafrost in the Qinghai-Xizang Plateau in the past 40 years from 1981 to 2020 was obtained.The changes of soil freeze-thaw conditions in different seasons of 2020 and in the same season of 1990,2000,2010 and 2020 were compared,and the annual variation trend of soil freeze-thaw area in the four years was analyzed.Further,the linear regression analysis was carried out on the duration of soil freezing/thawing/transition and the interannual variation trend under different area conditions from 1981 to 2020.The results show that the freeze-thaw changes in different years are similar.In winter,it is mainly frozen for about 110 days.Spring and autumn are transitional periods,lasting for 170 days.In summer,it is mainly thawed for about 80 days.From 1981 to 2020,the freezing period and the average freezing area of the Qinghai-Xizang Plateau decreased at a rate of 0.22 days and 1986 km^(2) per year,respectively,while the thawing period and the average thawing area increased at a rate of 0.07 days and 3187 km^(2) per year,respectively.The research results provide important theoretical support for the ecological environment and permafrost protection of the Qinghai-Xizang Plateau.
基金supported by National Key Research and Development Plan of China(No.2022YFB3103304).
文摘False Data Injection Attacks(FDIAs)pose a critical security threat to modern power grids,corrupting state estimation and enabling malicious control actions that can lead to severe consequences,including cascading failures,large-scale blackouts,and significant economic losses.While detecting attacks is important,accurately localizing compromised nodes or measurements is even more critical,as it enables timely mitigation,targeted response,and enhanced system resilience beyond what detection alone can offer.Existing research typically models topological features using fixed structures,which can introduce irrelevant information and affect the effectiveness of feature extraction.To address this limitation,this paper proposes an FDIA localization model with adaptive neighborhood selection,which dynamically captures spatial dependencies of the power grid by adjusting node relationships based on data-driven similarities.The improved Transformer is employed to pre-fuse global spatial features of the graph,enriching the feature representation.To improve spatio-temporal correlation extraction for FDIA localization,the proposed model employs dilated causal convolution with a gating mechanism combined with graph convolution to capture and fuse long-range temporal features and adaptive topological features.This fully exploits the temporal dynamics and spatial dependencies inherent in the power grid.Finally,multi-source information is integrated to generate highly robust node embeddings,enhancing FDIA detection and localization.Experiments are conducted on IEEE 14,57,and 118-bus systems,and the results demonstrate that the proposed model substantially improves the accuracy of FDIA localization.Additional experiments are conducted to verify the effectiveness and robustness of the proposed model.
基金funded by the National Natural Science Foundation of China(Nos.52371117,52171122,52275362)the Central Government Guides the Special Fund Projects of Local Scientific and Technological Development,China(Nos.YDZJSX2021A016,YDZX-20191400002149)+1 种基金the Key Project of Natural Science Foundation of Ningxia,China(No.2022AAC02077)the Natural Science Foundation of Shanxi Province,China(No.20210302124077)。
文摘This study investigated the effect of Si addition on the microstructure and the silicide precipitation behavior in a novel near-βtitanium alloy.The results show that coarse and continuous silicides were preferentially precipitated at the grain boundary during the solidification process,and theβgrain size of the as-cast alloy was refined.Dynamic recrystallization occurs under isothermal compression,and the silicide could inhibit the growth of recrystallized grains.The element redistribution and dislocation accumulation during hot deformation promote the dynamic precipitation of silicide,resulting in a discontinuous distribution of silicides at the grain boundaries.This work provides insight into how silicide dynamic precipitation will affect the microstructure and plastic deformation behavior of metal alloys.
文摘Depth maps play a crucial role in various practical applications such as computer vision,augmented reality,and autonomous driving.How to obtain clear and accurate depth information in video depth estimation is a significant challenge faced in the field of computer vision.However,existing monocular video depth estimation models tend to produce blurred or inaccurate depth information in regions with object edges and low texture.To address this issue,we propose a monocular depth estimation model architecture guided by semantic segmentation masks,which introduces semantic information into the model to correct the ambiguous depth regions.We have evaluated the proposed method,and experimental results show that our method improves the accuracy of edge depth,demonstrating the effectiveness of our approach.
基金supported by the National Nature Science Foun-dation of China(Grant No.50875061).
文摘The fatigue life of components can be significantly enhanced by the formation of the surface hardness layer through surface strengthening technology.To avoid the geometric distortion of thin-walled com-ponents caused by strengthening,the strengthening energy is limited and the ideal strengthening effect cannot be obtained.This work aims to propose a novel approach to address this issue effectively.The surface layer with high-density dislocations was obtained by a low-energy surface strengthening method(shot peening)at first.Then the surface strengthening mechanism changes from dislocation strengthen-ing to grain boundary strengthening after electropulsing treatment(EPT).The evolution of residual stress and microstructure was analyzed using multi-scale characterization techniques.The results demonstrate that EPT followed by surface strengthening makes a remarkable 304%increase in fatigue life of TC11 titanium alloy.The enhancement of fatigue life can be attributed to the grain refinement accompanied by the formation of nanotwins and sub-grains in the surface-strengthened layer,as well as the reduction in dislocation density within the substrate after EPT.This study demonstrates the significant potential of EPT in further enhancing the fatigue life of surface pre-strengthened thin-walled components.
基金supported by the Fundamental Research Program(PNKA130)of the Korea Institute of Materials Science,Republic of Korea。
文摘This study investigates zinc’s(Zn)key role in enhancing the precipitation kinetics and refinement of Mg_(17)Al_(12)and Mg_(2)Sn phases in magnesium alloys through trace sodium(Na)additions.Magnesium alloys with varying compositions of aluminum(Al),tin(Sn),Zn,and Na were prepared and aged at 453 K.Microstructural analyses were conducted using transmission electron microscopy(TEM),scanning transmission electron microscopy(STEM),and atom probe tomography(APT).Trace additions of Na significantly enhanced the precipitation responses of both Mg_(17)Al_(12)and Mg_(2)Sn phases.When Zn was co-added with Na,as in the ATZ641N3 alloy(Mg–6Al–4Sn–1Zn–0.3Na),there was a pronounced refinement in precipitate morphology and acceleration of precipitation kinetics.The ATZ641N3 alloy achieved a peak hardness of 103 Hv at 36 hours,compared to 91 Hv at 72 hours for the ATZ641 alloy without Na.The simultaneous addition of Zn and Na led to the formation of Sn–Na–Zn particles that acted as effective nucleation sites for Mg_(2)Sn,promoting aluminum partitioning and accelerating the precipitation of Mg_(17)Al_(12)through Al-rich regions.Additionally,Zn and Na co-segregated within the Mg_(17)Al_(12)phase,reducing misfit strain caused by Zn substitution and improving precipitate stability and refinement.These findings highlight Zn’s critical role,alongside trace Na additions,in refining and accelerating the precipitation of Mg_(17)Al_(12)and Mg_(2)Sn phases,thereby enhancing the age-hardening response of magnesium alloys.
基金supported by the National Key Research and Development Program of China (Grant No.2022YFB3706801)the National Natural Science Foundation of China (Grant Nos.U2341253,52371019,U2241232)+2 种基金the Dalian High-level Talents Innovation Support Program (Grant No.2021RD06)the Applied Basic Research Program of Liaoning Province (Grant No.2022JH2/101300003)the Natural Science Foundation of Liaoning Province (Grant Nos.2022-BS-262,JYTMS20230031)。
文摘Based on thermodynamic calculations and continuous rheological extrusion(CRE)technology,Al-Ti-V-B master alloys were designed and prepared.The morphology and the distribution of the refined phases in the master alloys were analyzed by XRD,SEM,and TEM.The effects of master alloy addition and holding time on the microstructure and mechanical properties of A356 alloy were investigated.Under the optimum refiner addition of 0.3wt.%and the holding time of 20 min,the average grain size of the refined A356 alloy is 151.8±9.11μm,89.62%lower than that of original A356 alloy.The tensile strength and elongation of as-cast A356refined alloy are 196.11 MPa and 5.75%,respectively.After T6 treatment,the tensile strength and elongation of A356 refined alloy are 290.1 MPa and 3.09%,respectively.The fracture morphology is characterized by a predominance of along-crystal fracture with a small amount of through-crystal fracture,attributed to the refined grains.Finer grains promote crack path deflection and localized plastic deformation,enhancing energy dissipation and reducing the tendency for brittle fracture.This study provides a novel approach to improving the mechanical properties of A356 alloy through grain refinement using CRE Al-Ti-V-B master alloy.
