The shop scheduling problem with limited buffers has broad applications in real-world production scenarios,so this research direction is of great practical significance.However,there is currently little research on th...The shop scheduling problem with limited buffers has broad applications in real-world production scenarios,so this research direction is of great practical significance.However,there is currently little research on the hybrid flow shop scheduling problem with limited buffers(LBHFSP).This paper deeply investigates the LBHFSP to optimize the goal of the total completion time.To better solve the LBHFSP,a multi-level subpopulation-based particle swarm optimization algorithm(MLPSO)is proposed,which is founded on the attributes of the LBHFSP and the shortcomings of the basic PSO(particle swarm optimization)algorithm.In MLPSO,firstly,considering the impact of the limited buffers on the process of subsequent operations,a specific circular decoding strategy is developed to accommodate the characteristics of limited buffers.Secondly,an initialization strategy based on blocking time is designed to enhance the quality and diversity of the initial population.Afterward,a multi-level subpopulation collaborative search is developed to prevent being trapped in a local optimum and improve the global exploration capability.Additionally,a local search strategy based on the first blocked job is designed to enhance the MLPSO algorithm’s exploitation capability.Lastly,numerous experiments are carried out to test the performance of the proposed MLPSO by comparing it with classical intelligent optimization and popular algorithms in recent years.The results confirm that the proposed MLPSO has an outstanding performance when compared to other algorithms when solving LBHFSP.展开更多
The influence of different solution and aging conditions on the microstructure,impact toughness,and crack initiation and propagation mechanisms of the novel α+β titanium alloy Ti6422 was systematically investigated....The influence of different solution and aging conditions on the microstructure,impact toughness,and crack initiation and propagation mechanisms of the novel α+β titanium alloy Ti6422 was systematically investigated.By adjusting the furnace cooling time after solution treatment and the aging temperature,Ti6422 alloy samples were developed with a multi-level lamellar microstructure,in-cluding microscaleαcolonies and α_(p) lamellae,as well as nanoscale α_(s) phases.Extending the furnace cooling time after solution treatment at 920℃ for 1 h from 240 to 540 min,followed by aging at 600℃ for 6 h,increased the α_(p) lamella content,reduced the α_(s) phase content,expanded theαcolonies and α_(p) lamellae size,and improved the impact toughness from 22.7 to 53.8 J/cm^(2).Additionally,under the same solution treatment,raising the aging temperature from 500 to 700℃ resulted in a decrease in the α_(s) phase content and a growth in the thickness of the α_(p) lamella and α_(s) phase.The impact toughness increased significantly with these changes.Samples with high α_(p) lamellae content or large α_(s) phase size exhibited high crack initiation and propagation energies.Impact deformation caused severe kinking of the α_(p) lamellae in crack initiation and propagation areas,leading to a uniform and high-density kernel average misorientation(KAM)distribu-tion,enhancing plastic deformation coordination and uniformity.Moreover,the multidirectional arrangement of coarserαcolonies and α_(p) lamellae continuously deflect the crack propagation direction,inhibiting crack propagation.展开更多
As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods ge...As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.展开更多
The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly comple...The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.展开更多
The squeezing deformation of surrounding rock is an important factor restricting the safe construction and long-term operation of tunnels when a tunnel passes through soft strata with high ground stress.Under such sof...The squeezing deformation of surrounding rock is an important factor restricting the safe construction and long-term operation of tunnels when a tunnel passes through soft strata with high ground stress.Under such soft rock geological conditions,the large deformation of the surrounding rock can easily lead to the failure of supporting structures,including shotcrete cracks,spalling,and steel arch distortion.To improve the lining support performance during the large deformation of squeezed surrounding rock,this work selects aluminum foam with densities of 0.25 g/cm3,0.42 g/cm3 and 0.61 g/cm3 as the buffer layer material and carries out uniaxial confined compression tests.Through the evaluation and analysis of energy absorption and the comparison of the yield pressure of aluminum foam with those of other cushioning materials and yield pressure support systems,the strength,deformation and energy absorption of aluminum foam with a density of 0.25 g/cm3 meet the yield pressure performance requirements.The numerical model of the buffer layer yielding support system is then established via the finite element analysis software ABAQUS,and the influence of the buffer layer setting on the lining support is analyzed.Compared with the conventional support scheme,the addition of an aluminum foam buffer layer can reduce the stress and deformation of the primary support and secondary lining.The maximum and minimum principal stresses of the primary support are reduced by 13%and 15%,respectively.The maximum and minimum principal stresses of the secondary lining are reduced by 15%and 12%,respectively,and the displacement deformation of the secondary lining position is reduced by 15%.In summary,the application of aluminum foam buffer layer can reduce the stress and deformation of the primary support and secondary lining,improve the stress safety of the support and reduce the deformation of the support.展开更多
Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,ther...Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,there is limited research on the spatiotemporal characteristics of landslide deformation.This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention(MFA-MRSTGRN)that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion.This model integrates internal seepage factors as data feature enhancements with external triggering factors,allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset.The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules:multilevel feature attention,temporal-residual decomposition,spatial multi-relational graph convolution,and spatiotemporal fusion prediction.This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets,facilitating adaptive exploration of the evolving multi-relational,multi-dimensional spatiotemporal complexities in landslides.When applying this model to predict the displacement of the Liangshuijing landslide,we demonstrate that the MFA-MRSTGRN model surpasses traditional models,such as random forest(RF),long short-term memory(LSTM),and spatial temporal graph convolutional networks(ST-GCN)models in terms of various evaluation metrics including mean absolute error(MAE=1.27 mm),root mean square error(RMSE=1.49 mm),mean absolute percentage error(MAPE=0.026),and R-squared(R^(2)=0.88).Furthermore,feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models.This research provides an advanced and reliable method for landslide displacement prediction.展开更多
The Casimir pressure plays an important role in the adhesion stability of nanofilms at submicro scales.In this work,the Casimir pressure of peptide films deposited on a layered substrate is investigated.Three types of...The Casimir pressure plays an important role in the adhesion stability of nanofilms at submicro scales.In this work,the Casimir pressure of peptide films deposited on a layered substrate is investigated.Three types of semi-infinite substrates,i.e.,silica,silicon and gold,are considered.The buffer layer between the peptide film and substrate consists of silicon or silica.The switching sign of the Casimir pressure can be controlled in a region ranging from about 130 nm to 1000 nm,depending on the thickness of the buffer layer and the substrate.The results suggest that the critical thickness of peptide films for Casimir equilibrium increases(or decreases)by increasing the thickness of the silicon(or silica)buffer film.The influences of wetting and electrolyte screening on the Casimir pressure are also investigated.Our finding provides a theoretical guide for the adhesion stability of peptide films in organic electronics.展开更多
As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could ra...As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could range from kilometers to tens of kilometers, and even hundreds and thousands of kilometers. Therefore, it is crucial to develop effective long-range path planning for lunar rovers to meet the demands of lunar patrol exploration. This paper presents a hierarchical map model path planning method that utilizes the existing high-resolution images, digital elevation models and mineral abundance maps. The objective is to address the issue of the construction of lunar rover travel costs in the absence of large-scale, high-resolution digital elevation models. This method models the reference and semantic layers using the middle- and low-resolution remote sensing data. The multi-scale obstacles on the lunar surface are extracted by combining the deep learning algorithm on the high-resolution image, and the obstacle avoidance layer is modeled. A two-stage exploratory path planning decision is employed for long-distance driving path planning on a global–local scale. The proposed method analyzes the long-distance accessibility of various areas of scientific significance, such as Rima Bode. A high-precision digital elevation model is created using stereo images to validate the method. Based on the findings, it can be observed that the entire route spans a distance of 930.32 km. The route demonstrates an impressive ability to avoid meter-level impact craters and linear structures while maintaining an average slope of less than 8°. This paper explores scientific research by traversing at least seven basalt units, uncovering the secrets of lunar volcanic activities, and establishing ‘golden spike’ reference points for lunar stratigraphy. The final result of path planning can serve as a valuable reference for the design, mission demonstration, and subsequent project implementation of the new manned lunar rover.展开更多
Stochastic optical reconstruction microscopy(STORM),as a typical technique of single-molecule localization microscopy(SMLM),has overcome the diffraction limit by randomly switching fluorophores between fluorescent and...Stochastic optical reconstruction microscopy(STORM),as a typical technique of single-molecule localization microscopy(SMLM),has overcome the diffraction limit by randomly switching fluorophores between fluorescent and dark states,allowing for the precise localization of isolated emission patterns and the super-resolution reconstruction from millions of localized positions of single fluorophores.A critical factor influencing localization precision is the photo-switching behavior of fluorophores,which is affected by the imaging buffer.The imaging buffer typically comprises oxygen scavengers,photo-switching reagents,and refractive index regulators.Oxygen scavengers help prevent photobleaching,photo-switching reagents assist in facilitating the conversion of fluorophores,and refractive index regulators are used to adjust the refractive index of the solution.The synergistic interaction of these components promotes stable blinking of fluorophores,reduces irreversible photobleaching,and thereby ensures high-quality super-resolution imaging.This review provides a comprehensive overview of the essential compositions and functionalities of imaging buffers used in STORM,serving as a valuable resource for researchers seeking to select appropriate imaging buffers for their experiments.展开更多
Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective metho...Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective method to mitigate the problem,which is able to learn an adaptive segmentation model by transferring knowledge from a rich-labeled source domain.In this paper,we propose a multi-level distribution alignment-based unsupervised domain adaptation network(MDA-Net)for segmentation of 3D neuronal soma images.Distribution alignment is performed in both feature space and output space.In the feature space,features from different scales are adaptively fused to enhance the feature extraction capability for small target somata and con-strained to be domain invariant by adversarial adaptation strategy.In the output space,local discrepancy maps that can reveal the spatial structures of somata are constructed on the predicted segmentation results.Then thedistribution alignment is performed on the local discrepancies maps across domains to obtain a superior discrepancy map in the target domain,achieving refined segmentation performance of neuronal somata.Additionally,after a period of distribution align-ment procedure,a portion of target samples with high confident pseudo-labels are selected as training data,which assist in learning a more adaptive segmentation network.We verified the superiority of the proposed algorithm by comparing several domain adaptation networks on two 3D mouse brain neuronal somata datasets and one macaque brain neuronal soma dataset.展开更多
Maglev trains experience significant aerodynamic effects when passing through tunnels.A moving model test was conducted to explore the practical effects of speed reduction and entrance buffer structures on mitigating ...Maglev trains experience significant aerodynamic effects when passing through tunnels.A moving model test was conducted to explore the practical effects of speed reduction and entrance buffer structures on mitigating tunnel/maglev aerodynamic effects.It is found that both have an overall positive effect on mitigating the aerodynamic environment inside and outside the tunnel.Trains operating at 200 km/h show a 49.8%decrease in peak-to-peak pressure and a 50.7%decrease in transient pressure instability on inner walls compared to those at 280 km/h.Lower speeds resulted in a 65.6%decrease in amplitude and a 24.5%decrease in decay rate,both of which are parameters for exponential fittings of pressure peaks that decay naturally after the train leaves.The buffer structures result in a reduction of up to 25.7%in the maximum positive pressure and a 29.0%decrease in transient pressure instability.Additionally,a reduction in amplitude of up to 21.2%and a 32.2%increase in decay rate were observed with the use of buffer structures.Nevertheless,it is difficult to conclude direct correlations between the maximum pressure,peak-to-peak values,etc.,and the speeds or buffer structures due to the complex wave propagation in tunnels.However,speed reduction and buffer structures are proven to be effective in reducing the micro-pressure wave levels with a simpler monotonic relationship.展开更多
Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to vari...Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.展开更多
Man-made superheavy elements(SHE)are produced as energetic recoils in complete-fusion reactions and need to be thermalized in a gas-filled chamber for chemical studies.The ever-shorter half-lives and decreasing produc...Man-made superheavy elements(SHE)are produced as energetic recoils in complete-fusion reactions and need to be thermalized in a gas-filled chamber for chemical studies.The ever-shorter half-lives and decreasing production rates of the elements beyond Fl(atomic number Z=114)-the heaviest element chemically studied today-require the development of novel techniques for quantitative thermalization and fast extraction efficiency.The Universal high-density gas stopping Cell(UniCell),currently under construction,was proposed to achieve this.Within this work,we propose an Ion Transfer by Gas Flow(ITGF)device,which serves as a UniCell ejector to interface with a gas chromatography detector array for chemical studies.Detailed parameter optimizations,using gas dynamics and Monte Carlo ion-trajectory simulations,promise fast(within a few ms)and highly efficient(up to 100%)ion extraction across a wide mass range.These ions can then be transmitted quantitatively through the ITGF into the high-pressure environment needed for further chemical studies.展开更多
Temperate forests exert significant biogeophysical influences on local and regional climates through modulating the energy and moisture exchanges between the land surface and the atmosphere,thereby serving as crucial ...Temperate forests exert significant biogeophysical influences on local and regional climates through modulating the energy and moisture exchanges between the land surface and the atmosphere,thereby serving as crucial barriers with significant buffering impacts on the productivity of adjacent agricultural ecosystems.However,the extent and underlying mechanisms of these biogeophysical and buffering effects of temperate forest barriers remains insufficiently understood.In this study,we integrated the dynamic crop model Noah-MP-Crop with the Weather Research and Forecasting(WRF)model to investigate the biogeophysical climate regulation of temperate forests and its buffering effects on crop yields in adjacent agricultural lands across Northeast China.Our findings revealed that temperate forest barriers induced significant local climate effects by cooling air and surface temperatures and reducing wind speeds within forested areas during the growing season,while also regulating non-local climate,particularly by altering regional precipitation patterns,2 m water vapor mixing ratio(Q2),and soil moisture,predominantly in adjacent cropland areas.Furthermore,these forest barriers were found to modulate climate extremes,through affecting maximum temperature and wind speed on a local scale,as well as both maximum and minimum Q2 in non-local croplands.Our study also observed that temperate forest barriers,through biogeophysical climate regulation,enhanced GPP,NPP,and grain yields across most cropland areas.This productivity boost was especially pronounced,with yield increases up to 20%in certain regions during the extreme drought conditions of 2017,underscoring the critical role of temperate forest barriers in sustaining and enhancing crop yields under severe climatic stress.Our findings underscore the significant buffering effects of temperate forest barriers on regional agricultural production,having important implications for climate adaptation strategies aimed at bolstering agricultural resilience in the face of increasing climate variability and extremes.展开更多
Aqueous zinc-ion batteries(AZIBs)have developed rapidly in recent years but still face several challenges,including zinc dendrites growth,hydrogen evolution reaction,passivation and corrosion.The pH of the electrolyte...Aqueous zinc-ion batteries(AZIBs)have developed rapidly in recent years but still face several challenges,including zinc dendrites growth,hydrogen evolution reaction,passivation and corrosion.The pH of the electrolyte plays a crucial role in these processes,significantly impacting the stability and reversibility of Zn^(2+)deposition.Therefore,pH-buffer tris(hydroxymethyl)amino methane(tris)is chosen as a versatile electrolyte additive to address these issues.Tris can buffer electrolyte pH at Zn/electrolyte interface by protonated/deprotonated nature of amino group,optimize the coordination environment of zinc solvate ions by its strong interaction with zinc ions,and simultaneously create an in-situ stable solid electrolyte interface membrane on the zinc anode surface.These synergistic effects effectively restrain dendrite formation and side reactions,resulting in a highly stable and reversible Zn anode,thereby enhancing the electrochemical performance of AZIBs.The Zn||Zn battery with 0.15 wt%tris additives maintains stable cycling for 1500 h at 4 mA·cm^(−2) and 1120 h at 10 mA·cm^(−2).Furthermore,the Coulombic efficiency reaches~99.2%at 4 mA·cm^(−2)@1 mAh·cm^(−2).The Zn||NVO full batteries also demonstrated a stable specific capacity and exceptional capacity retention.展开更多
Photocatalytic hydrogen peroxide(H_(2)O_(2))production offers a sustainable route to convert water and oxygen into H_(2)O_(2)using solar energy.However,achieving long-term stability in photocatalysts remains a critica...Photocatalytic hydrogen peroxide(H_(2)O_(2))production offers a sustainable route to convert water and oxygen into H_(2)O_(2)using solar energy.However,achieving long-term stability in photocatalysts remains a critical challenge due to mismatched kinetics between oxygen reduction(ORR)and water oxidation(WOR),which leads to hole accumulation and oxidative degradation.Here,we report a redox-mediated strategy to address this bottleneck by designing a hydroquinone-embedded covalent organic framework(Tz-QH-COF)that enables reversible hole buffering and kinetic balance.The hydroquinone(QH)units act as dynamic hole reservoirs,capturing excess holes during ORR and converting to benzoquinone(Q),which is regenerated to QH via WOR,thereby preventing oxidative decomposition.This reversible QH/Q cycle,directly visualized through in situ attenuated total reflection surface-enhanced infrared absorption spectroscopy,ensures unmatched stability,achieving continuous H_(2)O_(2) production for 528 h(22 d)with an accumulated yield of 18.6 mmol L^(–1)—the highest reported duration for organic photocatalysts.Density functional theory calculations reveal that the QH units exhibit a strong oxygen adsorption energy and favorable two-electron ORR/WOR pathways with low energy barriers.The synergy between experimental and theoretical insights elucidates a redox-mediated charge-balance mechanism,advancing the design of robust photocatalysts for solar-driven H_(2)O_(2) synthesis.展开更多
The buffer zone of a World Natural Heritage Site constitutes a critical element of the heritage site protection system.It not only functions as an ecological security barrier,but also significantly influences the visu...The buffer zone of a World Natural Heritage Site constitutes a critical element of the heritage site protection system.It not only functions as an ecological security barrier,but also significantly influences the visual integrity and aesthetic value of the core area’s landscape.Given the rapid development of transportation infrastructure,particularly the growing number of high-speed railways traversing ecologically sensitive regions,the scientific assessment of their impact on the landscape environment of heritage sites has emerged as a pivotal concern in heritage conservation and regional development.This study focused on the section of the Guiyang-Nanning High-Speed Railway that traverses the buffer zone of the Libo World Natural Heritage Site in Guizhou Province.Beginning with five primary indicators,including natural landscape and aesthetic value,geological geomorphology and Earth history value,biodiversity value,integrity and protection management,and impact on ecological environment,a visual landscape impact assessment system for high-speed railways was developed based on the analytic hierarchy process(AHP)and the fuzzy comprehensive evaluation method(FCE).Through expert scoring,hierarchical weight calculation,and fuzzy membership degree analysis,a comprehensive assessment was conducted on the landscape ecological quality,visual coordination,and aesthetic perception within the buffer zone following the construction of high-speed railways.The findings indicate that the construction of the Guiyang-Nanning High-Speed Railway generally harmonizes well with the landscape environment of the heritage site.The level of visual disturbance remains within an acceptable range and has not significantly damaged the overall aesthetic value or authenticity of the heritage site.Although the integrity of the landscape in certain local areas has experienced a slight decline due to the exposure of bridge and slope structures,the adverse effects have been effectively mitigated through engineering interventions such as vegetation restoration and color coordination.This study innovatively integrates the AHP with fuzzy mathematics methods to achieve a comprehensive evaluation that combines both qualitative and quantitative approaches.This integration provides a scientifically grounded analytical path and a practical technical framework for assessing the visual impact of linear infrastructure projects,such as high-speed railways,within the buffer zones of World Heritage Sites.The findings offer valuable insights for the protection of landscapes and the sustainable development of infrastructure in heritage sites.展开更多
Optimizing the orientation of β-Ga_(2)O_(3) has emerged as an effective strategy to design high-performance β-Ga_(2)O_(3) device,but the orientation growth mechanism and approach have not been revealed yet.Herein,by...Optimizing the orientation of β-Ga_(2)O_(3) has emerged as an effective strategy to design high-performance β-Ga_(2)O_(3) device,but the orientation growth mechanism and approach have not been revealed yet.Herein,by employing AlN buffer layer,the highly preferred orientation of β-Ga_(2)O_(3)(100)film rather than(-201)film is realized on 4H-SiC substrate at low sputtering power and temperature.Because β-Ga_(2)O_(3)(100)film exhibits a slower growth speed than(-201)film,the former possesses the higher dangling bond density and the lower nucleation energy,and a large conversion barrier exists between these two ori-entations.Moreover,the AlN buffer layer can suppress the surface oxidation of the 4H-SiC substrate and eliminate the strain of β-Ga_(2)O_(3)(100)film,which further reduces the nucleation energy and en-larges the conversion barrier.Meanwhile,the AlN buffer layer can increase the oxygen vacancy formation energy and decrease the oxygen vacancy concentration of β-Ga_(2)O_(3)(100)film.Consequently,the solar-blind photodetector based on the oriented film exhibits the outstanding detectivity of 1.22×10^(12) Jones and photo-to-dark current ratio of 1.11×10^(5),which are the highest among the reported β-Ga_(2)O_(3) solar-blind photodetector on the SiC substrate.Our results offer in-depth insights into the preferred orientation growth mechanism,and provide an effective way to design high-quality β-Ga_(2)O_(3)(100)orientation film and high-performance solar-blind photodetector.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant No.52175490.
文摘The shop scheduling problem with limited buffers has broad applications in real-world production scenarios,so this research direction is of great practical significance.However,there is currently little research on the hybrid flow shop scheduling problem with limited buffers(LBHFSP).This paper deeply investigates the LBHFSP to optimize the goal of the total completion time.To better solve the LBHFSP,a multi-level subpopulation-based particle swarm optimization algorithm(MLPSO)is proposed,which is founded on the attributes of the LBHFSP and the shortcomings of the basic PSO(particle swarm optimization)algorithm.In MLPSO,firstly,considering the impact of the limited buffers on the process of subsequent operations,a specific circular decoding strategy is developed to accommodate the characteristics of limited buffers.Secondly,an initialization strategy based on blocking time is designed to enhance the quality and diversity of the initial population.Afterward,a multi-level subpopulation collaborative search is developed to prevent being trapped in a local optimum and improve the global exploration capability.Additionally,a local search strategy based on the first blocked job is designed to enhance the MLPSO algorithm’s exploitation capability.Lastly,numerous experiments are carried out to test the performance of the proposed MLPSO by comparing it with classical intelligent optimization and popular algorithms in recent years.The results confirm that the proposed MLPSO has an outstanding performance when compared to other algorithms when solving LBHFSP.
基金supported by the National Natural Science Foundation of China(No.52090041).
文摘The influence of different solution and aging conditions on the microstructure,impact toughness,and crack initiation and propagation mechanisms of the novel α+β titanium alloy Ti6422 was systematically investigated.By adjusting the furnace cooling time after solution treatment and the aging temperature,Ti6422 alloy samples were developed with a multi-level lamellar microstructure,in-cluding microscaleαcolonies and α_(p) lamellae,as well as nanoscale α_(s) phases.Extending the furnace cooling time after solution treatment at 920℃ for 1 h from 240 to 540 min,followed by aging at 600℃ for 6 h,increased the α_(p) lamella content,reduced the α_(s) phase content,expanded theαcolonies and α_(p) lamellae size,and improved the impact toughness from 22.7 to 53.8 J/cm^(2).Additionally,under the same solution treatment,raising the aging temperature from 500 to 700℃ resulted in a decrease in the α_(s) phase content and a growth in the thickness of the α_(p) lamella and α_(s) phase.The impact toughness increased significantly with these changes.Samples with high α_(p) lamellae content or large α_(s) phase size exhibited high crack initiation and propagation energies.Impact deformation caused severe kinking of the α_(p) lamellae in crack initiation and propagation areas,leading to a uniform and high-density kernel average misorientation(KAM)distribu-tion,enhancing plastic deformation coordination and uniformity.Moreover,the multidirectional arrangement of coarserαcolonies and α_(p) lamellae continuously deflect the crack propagation direction,inhibiting crack propagation.
基金National Natural Science Foundation of China(Nos.42301473,42271424,42171397)Chinese Postdoctoral Innovation Talents Support Program(No.BX20230299)+2 种基金China Postdoctoral Science Foundation(No.2023M742884)Natural Science Foundation of Sichuan Province(Nos.24NSFSC2264,2025ZNSFSC0322)Key Research and Development Project of Sichuan Province(No.24ZDYF0633).
文摘As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.
基金financially supported by Guangdong Province Basic and Applied Basic Research Fund Project(Grant No.2022B1515250009)Liaoning Provincial Natural Science Foundation-Doctoral Research Start-up Fund Project(Grant No.2024-BSBA-05)+1 种基金Major Science and Technology Innovation Project in Shandong Province(Grant No.2024CXGC010803)the National Natural Science Foundation of China(Grant Nos.52271269 and 12302147).
文摘The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.
基金the support of the National Natural Science Foundation of China(Grant No.42207199)Scientific Research Project of Education of Zhejiang Province(No.Y202351343)+1 种基金Zhejiang Postdoctoral Scientific Research Project(Grant Nos.ZJ2022155,ZJ2022156)Zhejiang Province International Science and Technology Cooperation Base Open Fund Project(IBGDP-2023-01)。
文摘The squeezing deformation of surrounding rock is an important factor restricting the safe construction and long-term operation of tunnels when a tunnel passes through soft strata with high ground stress.Under such soft rock geological conditions,the large deformation of the surrounding rock can easily lead to the failure of supporting structures,including shotcrete cracks,spalling,and steel arch distortion.To improve the lining support performance during the large deformation of squeezed surrounding rock,this work selects aluminum foam with densities of 0.25 g/cm3,0.42 g/cm3 and 0.61 g/cm3 as the buffer layer material and carries out uniaxial confined compression tests.Through the evaluation and analysis of energy absorption and the comparison of the yield pressure of aluminum foam with those of other cushioning materials and yield pressure support systems,the strength,deformation and energy absorption of aluminum foam with a density of 0.25 g/cm3 meet the yield pressure performance requirements.The numerical model of the buffer layer yielding support system is then established via the finite element analysis software ABAQUS,and the influence of the buffer layer setting on the lining support is analyzed.Compared with the conventional support scheme,the addition of an aluminum foam buffer layer can reduce the stress and deformation of the primary support and secondary lining.The maximum and minimum principal stresses of the primary support are reduced by 13%and 15%,respectively.The maximum and minimum principal stresses of the secondary lining are reduced by 15%and 12%,respectively,and the displacement deformation of the secondary lining position is reduced by 15%.In summary,the application of aluminum foam buffer layer can reduce the stress and deformation of the primary support and secondary lining,improve the stress safety of the support and reduce the deformation of the support.
基金the funding support from the National Natural Science Foundation of China(Grant No.52308340)Chongqing Talent Innovation and Entrepreneurship Demonstration Team Project(Grant No.cstc2024ycjh-bgzxm0012)the Science and Technology Projects supported by China Coal Technology and Engineering Chongqing Design and Research Institute(Group)Co.,Ltd.(Grant No.H20230317).
文摘Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,there is limited research on the spatiotemporal characteristics of landslide deformation.This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention(MFA-MRSTGRN)that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion.This model integrates internal seepage factors as data feature enhancements with external triggering factors,allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset.The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules:multilevel feature attention,temporal-residual decomposition,spatial multi-relational graph convolution,and spatiotemporal fusion prediction.This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets,facilitating adaptive exploration of the evolving multi-relational,multi-dimensional spatiotemporal complexities in landslides.When applying this model to predict the displacement of the Liangshuijing landslide,we demonstrate that the MFA-MRSTGRN model surpasses traditional models,such as random forest(RF),long short-term memory(LSTM),and spatial temporal graph convolutional networks(ST-GCN)models in terms of various evaluation metrics including mean absolute error(MAE=1.27 mm),root mean square error(RMSE=1.49 mm),mean absolute percentage error(MAPE=0.026),and R-squared(R^(2)=0.88).Furthermore,feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models.This research provides an advanced and reliable method for landslide displacement prediction.
基金supported by the National Natural Science Foundation of China(Grant No.11804288)the Natural Science Foundation of Henan(Grant No.232300420120)。
文摘The Casimir pressure plays an important role in the adhesion stability of nanofilms at submicro scales.In this work,the Casimir pressure of peptide films deposited on a layered substrate is investigated.Three types of semi-infinite substrates,i.e.,silica,silicon and gold,are considered.The buffer layer between the peptide film and substrate consists of silicon or silica.The switching sign of the Casimir pressure can be controlled in a region ranging from about 130 nm to 1000 nm,depending on the thickness of the buffer layer and the substrate.The results suggest that the critical thickness of peptide films for Casimir equilibrium increases(or decreases)by increasing the thickness of the silicon(or silica)buffer film.The influences of wetting and electrolyte screening on the Casimir pressure are also investigated.Our finding provides a theoretical guide for the adhesion stability of peptide films in organic electronics.
基金co-supported by the National Key Research and Development Program of China(No.2022YFF0503100)the Youth Innovation Project of Pandeng Program of National Space Science Center,Chinese Academy of Sciences(No.E3PD40012S).
文摘As we look ahead to future lunar exploration missions, such as crewed lunar exploration and establishing lunar scientific research stations, the lunar rovers will need to cover vast distances. These distances could range from kilometers to tens of kilometers, and even hundreds and thousands of kilometers. Therefore, it is crucial to develop effective long-range path planning for lunar rovers to meet the demands of lunar patrol exploration. This paper presents a hierarchical map model path planning method that utilizes the existing high-resolution images, digital elevation models and mineral abundance maps. The objective is to address the issue of the construction of lunar rover travel costs in the absence of large-scale, high-resolution digital elevation models. This method models the reference and semantic layers using the middle- and low-resolution remote sensing data. The multi-scale obstacles on the lunar surface are extracted by combining the deep learning algorithm on the high-resolution image, and the obstacle avoidance layer is modeled. A two-stage exploratory path planning decision is employed for long-distance driving path planning on a global–local scale. The proposed method analyzes the long-distance accessibility of various areas of scientific significance, such as Rima Bode. A high-precision digital elevation model is created using stereo images to validate the method. Based on the findings, it can be observed that the entire route spans a distance of 930.32 km. The route demonstrates an impressive ability to avoid meter-level impact craters and linear structures while maintaining an average slope of less than 8°. This paper explores scientific research by traversing at least seven basalt units, uncovering the secrets of lunar volcanic activities, and establishing ‘golden spike’ reference points for lunar stratigraphy. The final result of path planning can serve as a valuable reference for the design, mission demonstration, and subsequent project implementation of the new manned lunar rover.
基金funded by the National Natural Science Foundation of China(No.62305041)the Natural Science Foundation of Liaoning Province(No.2023-MS-103)。
文摘Stochastic optical reconstruction microscopy(STORM),as a typical technique of single-molecule localization microscopy(SMLM),has overcome the diffraction limit by randomly switching fluorophores between fluorescent and dark states,allowing for the precise localization of isolated emission patterns and the super-resolution reconstruction from millions of localized positions of single fluorophores.A critical factor influencing localization precision is the photo-switching behavior of fluorophores,which is affected by the imaging buffer.The imaging buffer typically comprises oxygen scavengers,photo-switching reagents,and refractive index regulators.Oxygen scavengers help prevent photobleaching,photo-switching reagents assist in facilitating the conversion of fluorophores,and refractive index regulators are used to adjust the refractive index of the solution.The synergistic interaction of these components promotes stable blinking of fluorophores,reduces irreversible photobleaching,and thereby ensures high-quality super-resolution imaging.This review provides a comprehensive overview of the essential compositions and functionalities of imaging buffers used in STORM,serving as a valuable resource for researchers seeking to select appropriate imaging buffers for their experiments.
基金supported by the Fund of Key Laboratory of Biomedical Engineering of Hainan Province(No.BME20240001)the STI2030-Major Projects(No.2021ZD0200104)the National Natural Science Foundations of China under Grant 61771437.
文摘Deep learning networks are increasingly exploited in the field of neuronal soma segmentation.However,annotating dataset is also an expensive and time-consuming task.Unsupervised domain adaptation is an effective method to mitigate the problem,which is able to learn an adaptive segmentation model by transferring knowledge from a rich-labeled source domain.In this paper,we propose a multi-level distribution alignment-based unsupervised domain adaptation network(MDA-Net)for segmentation of 3D neuronal soma images.Distribution alignment is performed in both feature space and output space.In the feature space,features from different scales are adaptively fused to enhance the feature extraction capability for small target somata and con-strained to be domain invariant by adversarial adaptation strategy.In the output space,local discrepancy maps that can reveal the spatial structures of somata are constructed on the predicted segmentation results.Then thedistribution alignment is performed on the local discrepancies maps across domains to obtain a superior discrepancy map in the target domain,achieving refined segmentation performance of neuronal somata.Additionally,after a period of distribution align-ment procedure,a portion of target samples with high confident pseudo-labels are selected as training data,which assist in learning a more adaptive segmentation network.We verified the superiority of the proposed algorithm by comparing several domain adaptation networks on two 3D mouse brain neuronal somata datasets and one macaque brain neuronal soma dataset.
基金Project(52202426)supported by the National Natural Science Foundation of ChinaProjects(15205723,15226424)supported by the Research Grants Council of the Hong Kong Special Administrative Region,China。
文摘Maglev trains experience significant aerodynamic effects when passing through tunnels.A moving model test was conducted to explore the practical effects of speed reduction and entrance buffer structures on mitigating tunnel/maglev aerodynamic effects.It is found that both have an overall positive effect on mitigating the aerodynamic environment inside and outside the tunnel.Trains operating at 200 km/h show a 49.8%decrease in peak-to-peak pressure and a 50.7%decrease in transient pressure instability on inner walls compared to those at 280 km/h.Lower speeds resulted in a 65.6%decrease in amplitude and a 24.5%decrease in decay rate,both of which are parameters for exponential fittings of pressure peaks that decay naturally after the train leaves.The buffer structures result in a reduction of up to 25.7%in the maximum positive pressure and a 29.0%decrease in transient pressure instability.Additionally,a reduction in amplitude of up to 21.2%and a 32.2%increase in decay rate were observed with the use of buffer structures.Nevertheless,it is difficult to conclude direct correlations between the maximum pressure,peak-to-peak values,etc.,and the speeds or buffer structures due to the complex wave propagation in tunnels.However,speed reduction and buffer structures are proven to be effective in reducing the micro-pressure wave levels with a simpler monotonic relationship.
文摘Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and treatment.However,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound images.Although existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,etc.To address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule segmentation.The MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding methods.This transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the data.The approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the data.Furthermore,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation accuracy.Experimental results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)dataset.These findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.
基金This work was supported by the German BMBF (No.05P21UMFN2)
文摘Man-made superheavy elements(SHE)are produced as energetic recoils in complete-fusion reactions and need to be thermalized in a gas-filled chamber for chemical studies.The ever-shorter half-lives and decreasing production rates of the elements beyond Fl(atomic number Z=114)-the heaviest element chemically studied today-require the development of novel techniques for quantitative thermalization and fast extraction efficiency.The Universal high-density gas stopping Cell(UniCell),currently under construction,was proposed to achieve this.Within this work,we propose an Ion Transfer by Gas Flow(ITGF)device,which serves as a UniCell ejector to interface with a gas chromatography detector array for chemical studies.Detailed parameter optimizations,using gas dynamics and Monte Carlo ion-trajectory simulations,promise fast(within a few ms)and highly efficient(up to 100%)ion extraction across a wide mass range.These ions can then be transmitted quantitatively through the ITGF into the high-pressure environment needed for further chemical studies.
基金supported by National Key R&D Program of China(Grant No.2024YFD1501600)the National Natural Science Foundation of China(Grants No.42071025,42371075)the Youth Innovation Promotion Association of Chinese Academy of Sciences(Grant No.2023240).
文摘Temperate forests exert significant biogeophysical influences on local and regional climates through modulating the energy and moisture exchanges between the land surface and the atmosphere,thereby serving as crucial barriers with significant buffering impacts on the productivity of adjacent agricultural ecosystems.However,the extent and underlying mechanisms of these biogeophysical and buffering effects of temperate forest barriers remains insufficiently understood.In this study,we integrated the dynamic crop model Noah-MP-Crop with the Weather Research and Forecasting(WRF)model to investigate the biogeophysical climate regulation of temperate forests and its buffering effects on crop yields in adjacent agricultural lands across Northeast China.Our findings revealed that temperate forest barriers induced significant local climate effects by cooling air and surface temperatures and reducing wind speeds within forested areas during the growing season,while also regulating non-local climate,particularly by altering regional precipitation patterns,2 m water vapor mixing ratio(Q2),and soil moisture,predominantly in adjacent cropland areas.Furthermore,these forest barriers were found to modulate climate extremes,through affecting maximum temperature and wind speed on a local scale,as well as both maximum and minimum Q2 in non-local croplands.Our study also observed that temperate forest barriers,through biogeophysical climate regulation,enhanced GPP,NPP,and grain yields across most cropland areas.This productivity boost was especially pronounced,with yield increases up to 20%in certain regions during the extreme drought conditions of 2017,underscoring the critical role of temperate forest barriers in sustaining and enhancing crop yields under severe climatic stress.Our findings underscore the significant buffering effects of temperate forest barriers on regional agricultural production,having important implications for climate adaptation strategies aimed at bolstering agricultural resilience in the face of increasing climate variability and extremes.
基金supported by the Fund of Xuzhou Science and Technology Key R&D Program(Social Development)Project(No.KC22289)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX22_2783).
文摘Aqueous zinc-ion batteries(AZIBs)have developed rapidly in recent years but still face several challenges,including zinc dendrites growth,hydrogen evolution reaction,passivation and corrosion.The pH of the electrolyte plays a crucial role in these processes,significantly impacting the stability and reversibility of Zn^(2+)deposition.Therefore,pH-buffer tris(hydroxymethyl)amino methane(tris)is chosen as a versatile electrolyte additive to address these issues.Tris can buffer electrolyte pH at Zn/electrolyte interface by protonated/deprotonated nature of amino group,optimize the coordination environment of zinc solvate ions by its strong interaction with zinc ions,and simultaneously create an in-situ stable solid electrolyte interface membrane on the zinc anode surface.These synergistic effects effectively restrain dendrite formation and side reactions,resulting in a highly stable and reversible Zn anode,thereby enhancing the electrochemical performance of AZIBs.The Zn||Zn battery with 0.15 wt%tris additives maintains stable cycling for 1500 h at 4 mA·cm^(−2) and 1120 h at 10 mA·cm^(−2).Furthermore,the Coulombic efficiency reaches~99.2%at 4 mA·cm^(−2)@1 mAh·cm^(−2).The Zn||NVO full batteries also demonstrated a stable specific capacity and exceptional capacity retention.
文摘Photocatalytic hydrogen peroxide(H_(2)O_(2))production offers a sustainable route to convert water and oxygen into H_(2)O_(2)using solar energy.However,achieving long-term stability in photocatalysts remains a critical challenge due to mismatched kinetics between oxygen reduction(ORR)and water oxidation(WOR),which leads to hole accumulation and oxidative degradation.Here,we report a redox-mediated strategy to address this bottleneck by designing a hydroquinone-embedded covalent organic framework(Tz-QH-COF)that enables reversible hole buffering and kinetic balance.The hydroquinone(QH)units act as dynamic hole reservoirs,capturing excess holes during ORR and converting to benzoquinone(Q),which is regenerated to QH via WOR,thereby preventing oxidative decomposition.This reversible QH/Q cycle,directly visualized through in situ attenuated total reflection surface-enhanced infrared absorption spectroscopy,ensures unmatched stability,achieving continuous H_(2)O_(2) production for 528 h(22 d)with an accumulated yield of 18.6 mmol L^(–1)—the highest reported duration for organic photocatalysts.Density functional theory calculations reveal that the QH units exhibit a strong oxygen adsorption energy and favorable two-electron ORR/WOR pathways with low energy barriers.The synergy between experimental and theoretical insights elucidates a redox-mediated charge-balance mechanism,advancing the design of robust photocatalysts for solar-driven H_(2)O_(2) synthesis.
基金Sponsored by Guizhou Provincial Key Technology R&D Program“A Study on the Conservation Model with Technology and Sustainable Development Demonstration of the World Natural Heritages in Guizhou”(2202023 QKHZC)the China Overseas Expertise Introduction Project for Discipline Innovation(China 111 Project)(D17016).
文摘The buffer zone of a World Natural Heritage Site constitutes a critical element of the heritage site protection system.It not only functions as an ecological security barrier,but also significantly influences the visual integrity and aesthetic value of the core area’s landscape.Given the rapid development of transportation infrastructure,particularly the growing number of high-speed railways traversing ecologically sensitive regions,the scientific assessment of their impact on the landscape environment of heritage sites has emerged as a pivotal concern in heritage conservation and regional development.This study focused on the section of the Guiyang-Nanning High-Speed Railway that traverses the buffer zone of the Libo World Natural Heritage Site in Guizhou Province.Beginning with five primary indicators,including natural landscape and aesthetic value,geological geomorphology and Earth history value,biodiversity value,integrity and protection management,and impact on ecological environment,a visual landscape impact assessment system for high-speed railways was developed based on the analytic hierarchy process(AHP)and the fuzzy comprehensive evaluation method(FCE).Through expert scoring,hierarchical weight calculation,and fuzzy membership degree analysis,a comprehensive assessment was conducted on the landscape ecological quality,visual coordination,and aesthetic perception within the buffer zone following the construction of high-speed railways.The findings indicate that the construction of the Guiyang-Nanning High-Speed Railway generally harmonizes well with the landscape environment of the heritage site.The level of visual disturbance remains within an acceptable range and has not significantly damaged the overall aesthetic value or authenticity of the heritage site.Although the integrity of the landscape in certain local areas has experienced a slight decline due to the exposure of bridge and slope structures,the adverse effects have been effectively mitigated through engineering interventions such as vegetation restoration and color coordination.This study innovatively integrates the AHP with fuzzy mathematics methods to achieve a comprehensive evaluation that combines both qualitative and quantitative approaches.This integration provides a scientifically grounded analytical path and a practical technical framework for assessing the visual impact of linear infrastructure projects,such as high-speed railways,within the buffer zones of World Heritage Sites.The findings offer valuable insights for the protection of landscapes and the sustainable development of infrastructure in heritage sites.
基金supported by the National Key Research and Development Program of China(No.2021YFA0715600)the National Natural Science Foundation of China(Nos.62274125,52192611)+2 种基金the Guangdong Basic and Applied Basic Research Fund(No.2023A1515030084)the Key Research and Development Program of Shaanxi Province(Grant No.2024GX-YBXM-410)the fund of the State Key Laboratory of Solidification Processing in NWPU(No.SKLSP202220).
文摘Optimizing the orientation of β-Ga_(2)O_(3) has emerged as an effective strategy to design high-performance β-Ga_(2)O_(3) device,but the orientation growth mechanism and approach have not been revealed yet.Herein,by employing AlN buffer layer,the highly preferred orientation of β-Ga_(2)O_(3)(100)film rather than(-201)film is realized on 4H-SiC substrate at low sputtering power and temperature.Because β-Ga_(2)O_(3)(100)film exhibits a slower growth speed than(-201)film,the former possesses the higher dangling bond density and the lower nucleation energy,and a large conversion barrier exists between these two ori-entations.Moreover,the AlN buffer layer can suppress the surface oxidation of the 4H-SiC substrate and eliminate the strain of β-Ga_(2)O_(3)(100)film,which further reduces the nucleation energy and en-larges the conversion barrier.Meanwhile,the AlN buffer layer can increase the oxygen vacancy formation energy and decrease the oxygen vacancy concentration of β-Ga_(2)O_(3)(100)film.Consequently,the solar-blind photodetector based on the oriented film exhibits the outstanding detectivity of 1.22×10^(12) Jones and photo-to-dark current ratio of 1.11×10^(5),which are the highest among the reported β-Ga_(2)O_(3) solar-blind photodetector on the SiC substrate.Our results offer in-depth insights into the preferred orientation growth mechanism,and provide an effective way to design high-quality β-Ga_(2)O_(3)(100)orientation film and high-performance solar-blind photodetector.
