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
Northeast China(NEC),a critical agricultural and ecological zone,has experienced intensified hydrological variability under global warming,with cascading impacts on food security and ecosystem resilience.This study ut...Northeast China(NEC),a critical agricultural and ecological zone,has experienced intensified hydrological variability under global warming,with cascading impacts on food security and ecosystem resilience.This study utilized observational data and two new generation reanalysis products(i.e.,the fifth major global reanalysis produced by ECMWF(ERA5)and the Japanese Reanalysis for Three Quarters of a Century(JRA-3Q))to investigate the shift changes in precipitation in NEC around 2000 and associated water vapor transport.The analysis identified a pivotal interdecadal shift in 1998/99,transitioning from moderate increases(17.5 mm/10 yr during 1980-1998)to accelerated but more variable precipitation growth(85.4 mm/10 yr post-1999).While the mean precipitation during the post-shift period decreased,enhanced anticyclonic circulation amplified moisture divergence over continental NEC,redirecting vapor flux toward coastal regions.Crucially,trajectory analysis demonstrated regime-dependent moisture sourcing:midlatitude westerlies dominated during wet extremes(44% of trajectories in 1998),whereas East Asian monsoon flows prevailed in drought years(36% of trajectories in 2007).The post-1998 period exhibited increased reliance on localized recycling(45%of mid-tropospheric trajectories),reflecting weakened monsoonal inflow.These findings highlight NEC’s growing vulnerability to competing moisture pathways and atmospheric blocking-a dual mechanism that explains rising extremes despite declining mean precipitation.By reconciling dataset discrepancies(ERA5 vs.JRA-3Q trends)and elucidating circulation-precipitation linkages,this work provides actionable insights for climate-resilient agriculture in NEC’s water-stressed ecosystems.展开更多
Data center industries have been facing huge energy challenges due to escalating power consumption and associated carbon emissions.In the context of carbon neutrality,the integration of data centers with renewable ene...Data center industries have been facing huge energy challenges due to escalating power consumption and associated carbon emissions.In the context of carbon neutrality,the integration of data centers with renewable energy has become a prevailing trend.To advance the renewable energy integration in data centers,it is imperative to thoroughly explore the data centers’operational flexibility.Computing workloads and refrigeration systems are recognized as two promising flexible resources for power regulationwithin data centermicro-grids.This paper identifies and categorizes delay-tolerant computing workloads into three types(long-running non-interruptible,long-running interruptible,and short-running)and develops mathematical time-shifting models for each.Additionally,this paper examines the thermal dynamics of the computer room and derives a time-varying temperature model coupled to refrigeration power.Building on these models,this paper proposes a two-stage,multi-time scale optimization scheduling framework that jointly coordinates computing workloads time-shift in day-ahead scheduling and refrigeration power control in intra-day dispatch to mitigate renewable variability.A case study demonstrates that the framework effectively enhances the renewable-energy utilization,improves the operational economy of the data center microgrid,and mitigates the impact of renewable power uncertainty.The results highlight the potential of coordinated computing workloads and thermal system flexibility to support greener,more cost-effective data center operation.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
Potassium(K)is known to enhance the catalytic performance of Fe-based catalysts in the reverse water-gas shift(rWGS)reaction,which is highly relevant during Fischer-Tropsch(FT)synthesis of CO_(2)-H_(2) mixtures.To elu...Potassium(K)is known to enhance the catalytic performance of Fe-based catalysts in the reverse water-gas shift(rWGS)reaction,which is highly relevant during Fischer-Tropsch(FT)synthesis of CO_(2)-H_(2) mixtures.To elucidate the mechanistic role of K promoter,we employed density functional theory(DFT)calculations in conjunction with microkinetic modelling for two representative surface terminations of Hägg carbide(χ-Fe_(5)C_(2)),i.e.,(010)and(510).K_(2)O results in stronger adsorption of CO_(2)and H_(2) on Hägg carbide and promotes C–O bond dissociation of adsorbed CO_(2)by increasing the electron density on Fe atoms close to the promoter oxide.The increased electron density of the surface Fe atoms results in an increased electron-electron repulsion with bonding orbitals of adsorbed CO_(2).Microkinetics simulations predict that K_(2)O increases the CO_(2)conversion during CO_(2)-FT synthesis.K_(2)O also enhances CO adsorption and dissociation,facilitating the formation of methane,used here as a proxy for hydrocarbons formation during CO_(2)-FT synthesis.CO dissociation and O removal via H_(2)O compete as the rate-controlling steps in CO_(2)-FT.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 current dialogue system can be sensitive to the emotions in the user's words,generating an empathetic response to help calm the user's emotions.But in some cases,eliciting empathetic responses may not adeq...The current dialogue system can be sensitive to the emotions in the user's words,generating an empathetic response to help calm the user's emotions.But in some cases,eliciting empathetic responses may not adequately mitigate the adverse effects that the current conversation topic is having on users.The dialogue system will continue the conversation with the user under this uncomfortable topic,which will lead to a worse chat situation or even an impasse.To solve this problem,a dialogue system that can change the topic autonomously according to the user's emotions is proposed in this paper.Specifically,the dialogue system first collects the emotional semantic information of the users and then detects it according to the emotion classification module.Once the detection results show that the user is in a bad mood,the topic change module selects a new topic from the context to shift to and generates a response.This not only helps to calm the user's mood but also move the conversation to a new area,steering the user away from the uncomfortable topic.The experimental results show that the proposed method incurs less cost in terms of content quality,but improves the emotional perception ability.Additionally,it endows the dialogue system with the ability to change the topic,and improves the user's dialogue experience.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
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
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
The transition energies of the 1s^(2)2s^(2)S_(1/2)→1s^(2)2p^(2)p_(1/2,3/2)transitions in Li-like Th87+ions were calculated by combining the multi-configuration Dirac-Hartree-Fock(MCDHF)method with the model-quantum e...The transition energies of the 1s^(2)2s^(2)S_(1/2)→1s^(2)2p^(2)p_(1/2,3/2)transitions in Li-like Th87+ions were calculated by combining the multi-configuration Dirac-Hartree-Fock(MCDHF)method with the model-quantum electrodynamics(modelQED)approach.The effects of electron correlation,Breit interaction,and QED effects were analyzed in detail.The isotope shifts,including the mass shifts and field shifts,due to the 2s2S_(1/2)→2p^(2)P_(1/2,3/2)transitions were then calculated using two different methods,namely,the MCDHF method and the finite-field method.The results show that these two methods are in excellent agreement.展开更多
With the continuous improvement of the medical industry’s requirements for the professional capabilities of nursing talents,traditional nursing teaching models can hardly meet the needs of complex nursing work in neu...With the continuous improvement of the medical industry’s requirements for the professional capabilities of nursing talents,traditional nursing teaching models can hardly meet the needs of complex nursing work in neurology.This paper focuses on nursing education for neurology nursing students and explores the construction of the“one-on-one”teaching model,aiming to achieve a paradigm shift in nursing education.By analyzing the current status of neurology nursing education,this paper identifies the problems in traditional teaching models.Combining the advantages of the“one-on-one”teaching model,it elaborates on the construction path of this model from aspects such as the selection and training of teaching instructors,the design of teaching content,the innovation of teaching methods,and the improvement of the teaching evaluation system.The research shows that the“one-on-one”teaching model can significantly enhance nursing students’mastery of professional knowledge,clinical operation skills,communication skills,and emergency response capabilities,as well as strengthen their professional identity and sense of responsibility.It provides an effective way to cultivate high-quality nursing talents who can meet the needs of neurology nursing work and promotes the innovative development of nursing education.展开更多
National Fire codes,mandated by government authorities to tackle technical challenges in fire prevention and control,establish fundamental standards for construction practices.International collaboration in fire prote...National Fire codes,mandated by government authorities to tackle technical challenges in fire prevention and control,establish fundamental standards for construction practices.International collaboration in fire protection technologies has opened avenues for China to access a wealth of documents and codes,which are crucial in crafting regulations and developing a robust,scientific framework for fire code formulation.However,the translation of these codes into Chinese has been inadequate,thereby diminishing the benefits of technological exchange and collaborative learning.This underscores the necessity for comprehensive research into code translation,striving for higher-quality translations guided by established translation theories.In this study,we translated the initial segment of the NFPA 1 Fire Code into Chinese and examined both the source text and target text through the lens of Translation Shift Theory,a concept introduced by Catford.The conclusion culminated in identifying four key shifts across various linguistic levels:lexis,sentences,and groups,to ensure an accurate and precise translation of fire codes.This study offers a through and lucid explanation of how the translator integrates Catford’s theories to solve technical challenges in NFPA 1 Fire Code translation,and establish essential standards for construction translation practices.展开更多
Highly accurate international height reference frames with long-term stability,global consistency,and homogeneity are crucial for monitoring sea level variations,understanding climate change,managing disasters,and sup...Highly accurate international height reference frames with long-term stability,global consistency,and homogeneity are crucial for monitoring sea level variations,understanding climate change,managing disasters,and supporting other applications that benefit scientific research and societal well-being.Currently,there are over 100 local height reference systems worldwide.Unifying these systems is a pivotal step toward constructing international height reference frames.The method introduced in this study-the gravity frequency shift via Satellite Frequency Signal Transfer(SFST)-represents a groundbreaking relativistic geodetic approach,demonstrating its potential to surpass the constraints of conventional techniques.The advent of high-precision optical atomic clocks(OAC)with an accuracy level of 1×10^(-18) has facilitated this method's implementation.The International Association of Geodesy(IAG)has established the International Height Reference System(IHRS)and its practical realization,the International Height Reference Frame(IHRF).Our study focuses on two neighbouring height systems:the China Height System(CHS)and the Nepal Height System(NHS),separated by the Himalayas and the Xizang plateau.We aim to unify these two systems by determining the geopotential and orthometric height differences between their respective height datum stations:the Qingdao Height Datum Station(QHDS)and the Madar Height Datum Station(MHDS)using a simulation experiment with the method mentioned above.Using an OAC with an accuracy of 1×10^(-18),we identified a geopotential difference of-8.348±0.464 m^(2)s^(-2) and an orthometric height difference of 0.786±0.047 m between QHDS and MHDS.These results suggest that the introduced method could unify any two height systems with fewcentimeter-level precision,emphasizing its significance in contributing to the construction of the IHRS/IHRF with today's required precision.In summary,the SFST technique is a novel geodetic method that offers an alternative for height system unification,delivering centimeter-level precision,surpassing traditional methods,and supporting the development of the IHRF.展开更多
The degradation and nonlinear interactions of a two-breather solution of the Mel’nikov equation are analyzed.By modulating the phase shift and limit method,we prove that in different regions near the non-singular bou...The degradation and nonlinear interactions of a two-breather solution of the Mel’nikov equation are analyzed.By modulating the phase shift and limit method,we prove that in different regions near the non-singular boundaries,there are four kinds of solutions with repulsive interaction or attractive interaction in addition to the two-breather solution.They are the interaction solution between soliton and breather,the two-soliton solution,and the two-breather solution with small amplitude,which all exhibit repulsive interactions;and the two-breather solution with small amplitude,which exhibits attractive interaction.Interestingly,a new breather acts as a messenger to transfer energy during the interaction between two breather solutions with small amplitude.展开更多
The phenomenon of verbal-to-nominal shift(hereafter referred to as“V-N shift”)exists in both English and Chinese.It reflects both the universal conceptual metonymic thinking and the principle of linguistic economy.F...The phenomenon of verbal-to-nominal shift(hereafter referred to as“V-N shift”)exists in both English and Chinese.It reflects both the universal conceptual metonymic thinking and the principle of linguistic economy.Focusing on conceptual metonymy theory and combined with the Event Idealized Cognitive Model(ICM),this paper systematically compares the V-N shift phenomenon in English and Chinese.The study shows that English and Chinese V-N shifts share the core cognitive mechanism of“conceptual proximity within the Event ICM”,while significant differences exist in type distribution and usage frequency.This analysis not only helps deepen the understanding of the cognitive logic behind English and Chinese V-N shifts but also provides a new perspective for the study of word-class conversion and the relationship between language and thinking.展开更多
Standard perturbation theory is employed to calculate the mass shifts of the 2^(1)S_(0)-^(3)S_(1)and 2^(3)S_(1)-2^(3)P_(J)transitions for^(4,6,8)He.High-precision results are obtained for the mass shifts in the isotop...Standard perturbation theory is employed to calculate the mass shifts of the 2^(1)S_(0)-^(3)S_(1)and 2^(3)S_(1)-2^(3)P_(J)transitions for^(4,6,8)He.High-precision results are obtained for the mass shifts in the isotope pairs 6He-4He and 8He-4He,with uncertainties below 1 part per million(ppm).Our analysis provides a complete set of isotope-shift results and systematically examines their sensitivity to nuclear charge-radius differences.Once experimental measurements reach a precision comparable to that of the calculated mass shifts,the squared differences of nuclear charge radii can be determined with an accuracy of approximately 0.4%-0.6%,representing an order-of-magnitude improvement over current values.展开更多
Anthropogenic climate change is altering species distributions globally.While species distributions are expected to shift to higher latitudes and elevations under global warming,empirical evidence on distribution shif...Anthropogenic climate change is altering species distributions globally.While species distributions are expected to shift to higher latitudes and elevations under global warming,empirical evidence on distribution shifts is mixed,and factors mediating the direction and magnitude of range shifts remain unclear.Using a dataset of 132new provincial records for 96 resident bird species from 2000 to 2023,we measured geographic distance,latitudinal shift,and temperature shift from each new record to the historical range for each species to test for poleward shifts.We assessed taxonomic variation in the magnitude of range shifts and used phylogenetic generalized linear mixed models to quantify relationships between species traits and the extent of range shifts.Our results revealed that new records occurred at a mean geographic distance of 420 km from historical ranges,with mean latitudinal shifts of+1.68°(poleward)and temperature shifts of-1.33℃(toward colder climates).The magnitude of geographic range shifts was strongly constrained by phylogenetic relatedness.Habitat breadth,habitat openness,and centroid latitude of historical ranges emerged as significant predictors of range shifts.Our results suggest that resident bird species'geographic ranges in China are shifting poleward,but the magnitude of these shifts is non-random across lineages.Species with broader habitat preferences and those from warmer climates are more likely to shift farther from their historical ranges and toward higher latitudes.This study emphasizes taxonomic variation in species range shifts and highlights the need for species-and site-specific conservation strategies under global warming.展开更多
Gait recognition,a promising biometric technology,relies on analyzing individuals' walking patterns and offers a non-intrusive and convenient approach to identity verification.However,gait recognition accuracy is ...Gait recognition,a promising biometric technology,relies on analyzing individuals' walking patterns and offers a non-intrusive and convenient approach to identity verification.However,gait recognition accuracy is often compromised by external factors such as changes in viewpoint and attire,which present substantial challenges in practical applications.To enhance gait recognition performance under diverse viewpoints and complex conditions,a global-local part-shift network is proposed in this paper.This framework integrates two novel modules:the part-shift feature extractor and the dynamic feature aggregator.The part-shift feature extractor strategically shifts body parts to capture the intrinsic relationships between non-adjacent regions,enriching the recognition process with both global and local spatial features.The dynamic feature aggregator addresses long-range dependency issues by incorporating multi-range temporal modeling,effectively aggregating information across parts and time steps to achieve a more robust recognition outcome.Comprehensive experiments on the CASIA-B dataset demonstrate that the proposed global-local part-shift network delivers superior performance compared with state-of-the-art methods,highlighting its potential for practical deployment.展开更多
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supported by the National Natural Science Foundation of China[grant numbers 42275185 and 42205032]the Fundamental Research Funds for the Central Universities[grant number B250201118]。
文摘Northeast China(NEC),a critical agricultural and ecological zone,has experienced intensified hydrological variability under global warming,with cascading impacts on food security and ecosystem resilience.This study utilized observational data and two new generation reanalysis products(i.e.,the fifth major global reanalysis produced by ECMWF(ERA5)and the Japanese Reanalysis for Three Quarters of a Century(JRA-3Q))to investigate the shift changes in precipitation in NEC around 2000 and associated water vapor transport.The analysis identified a pivotal interdecadal shift in 1998/99,transitioning from moderate increases(17.5 mm/10 yr during 1980-1998)to accelerated but more variable precipitation growth(85.4 mm/10 yr post-1999).While the mean precipitation during the post-shift period decreased,enhanced anticyclonic circulation amplified moisture divergence over continental NEC,redirecting vapor flux toward coastal regions.Crucially,trajectory analysis demonstrated regime-dependent moisture sourcing:midlatitude westerlies dominated during wet extremes(44% of trajectories in 1998),whereas East Asian monsoon flows prevailed in drought years(36% of trajectories in 2007).The post-1998 period exhibited increased reliance on localized recycling(45%of mid-tropospheric trajectories),reflecting weakened monsoonal inflow.These findings highlight NEC’s growing vulnerability to competing moisture pathways and atmospheric blocking-a dual mechanism that explains rising extremes despite declining mean precipitation.By reconciling dataset discrepancies(ERA5 vs.JRA-3Q trends)and elucidating circulation-precipitation linkages,this work provides actionable insights for climate-resilient agriculture in NEC’s water-stressed ecosystems.
基金supported by Science and Technology Standard Project of Guangdong Electric Power Design Institute(ER11301W,ER11811W).
文摘Data center industries have been facing huge energy challenges due to escalating power consumption and associated carbon emissions.In the context of carbon neutrality,the integration of data centers with renewable energy has become a prevailing trend.To advance the renewable energy integration in data centers,it is imperative to thoroughly explore the data centers’operational flexibility.Computing workloads and refrigeration systems are recognized as two promising flexible resources for power regulationwithin data centermicro-grids.This paper identifies and categorizes delay-tolerant computing workloads into three types(long-running non-interruptible,long-running interruptible,and short-running)and develops mathematical time-shifting models for each.Additionally,this paper examines the thermal dynamics of the computer room and derives a time-varying temperature model coupled to refrigeration power.Building on these models,this paper proposes a two-stage,multi-time scale optimization scheduling framework that jointly coordinates computing workloads time-shift in day-ahead scheduling and refrigeration power control in intra-day dispatch to mitigate renewable variability.A case study demonstrates that the framework effectively enhances the renewable-energy utilization,improves the operational economy of the data center microgrid,and mitigates the impact of renewable power uncertainty.The results highlight the potential of coordinated computing workloads and thermal system flexibility to support greener,more cost-effective data center operation.
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.
文摘Potassium(K)is known to enhance the catalytic performance of Fe-based catalysts in the reverse water-gas shift(rWGS)reaction,which is highly relevant during Fischer-Tropsch(FT)synthesis of CO_(2)-H_(2) mixtures.To elucidate the mechanistic role of K promoter,we employed density functional theory(DFT)calculations in conjunction with microkinetic modelling for two representative surface terminations of Hägg carbide(χ-Fe_(5)C_(2)),i.e.,(010)and(510).K_(2)O results in stronger adsorption of CO_(2)and H_(2) on Hägg carbide and promotes C–O bond dissociation of adsorbed CO_(2)by increasing the electron density on Fe atoms close to the promoter oxide.The increased electron density of the surface Fe atoms results in an increased electron-electron repulsion with bonding orbitals of adsorbed CO_(2).Microkinetics simulations predict that K_(2)O increases the CO_(2)conversion during CO_(2)-FT synthesis.K_(2)O also enhances CO adsorption and dissociation,facilitating the formation of methane,used here as a proxy for hydrocarbons formation during CO_(2)-FT synthesis.CO dissociation and O removal via H_(2)O compete as the rate-controlling steps in CO_(2)-FT.
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Sponsored by Natural Science Foundation of Heilongjiang Provincial(Grant No.LH2023F033)Science and Technology Innovation Talent Project of Harbin(Grant No.2022CXRCCG006).
文摘The current dialogue system can be sensitive to the emotions in the user's words,generating an empathetic response to help calm the user's emotions.But in some cases,eliciting empathetic responses may not adequately mitigate the adverse effects that the current conversation topic is having on users.The dialogue system will continue the conversation with the user under this uncomfortable topic,which will lead to a worse chat situation or even an impasse.To solve this problem,a dialogue system that can change the topic autonomously according to the user's emotions is proposed in this paper.Specifically,the dialogue system first collects the emotional semantic information of the users and then detects it according to the emotion classification module.Once the detection results show that the user is in a bad mood,the topic change module selects a new topic from the context to shift to and generates a response.This not only helps to calm the user's mood but also move the conversation to a new area,steering the user away from the uncomfortable topic.The experimental results show that the proposed method incurs less cost in terms of content quality,but improves the emotional perception ability.Additionally,it endows the dialogue system with the ability to change the topic,and improves the user's dialogue experience.
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.
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Project supported by the National Key Research and Development Program of China(Grant No.2022YFA1602500)the National Natural Science Foundation of China(Grant Nos.1236040286,12474250,12174316,12464036,and12404306)+1 种基金the Young Teachers Scientific Research Ability Promotion Plan of Northwest Normal University(Grant No.NWNU-LKQN2020-10)the Funds for Innovative Fundamental Research Group Project of Gansu Province(Grant No.20JR5RA541)。
文摘The transition energies of the 1s^(2)2s^(2)S_(1/2)→1s^(2)2p^(2)p_(1/2,3/2)transitions in Li-like Th87+ions were calculated by combining the multi-configuration Dirac-Hartree-Fock(MCDHF)method with the model-quantum electrodynamics(modelQED)approach.The effects of electron correlation,Breit interaction,and QED effects were analyzed in detail.The isotope shifts,including the mass shifts and field shifts,due to the 2s2S_(1/2)→2p^(2)P_(1/2,3/2)transitions were then calculated using two different methods,namely,the MCDHF method and the finite-field method.The results show that these two methods are in excellent agreement.
文摘With the continuous improvement of the medical industry’s requirements for the professional capabilities of nursing talents,traditional nursing teaching models can hardly meet the needs of complex nursing work in neurology.This paper focuses on nursing education for neurology nursing students and explores the construction of the“one-on-one”teaching model,aiming to achieve a paradigm shift in nursing education.By analyzing the current status of neurology nursing education,this paper identifies the problems in traditional teaching models.Combining the advantages of the“one-on-one”teaching model,it elaborates on the construction path of this model from aspects such as the selection and training of teaching instructors,the design of teaching content,the innovation of teaching methods,and the improvement of the teaching evaluation system.The research shows that the“one-on-one”teaching model can significantly enhance nursing students’mastery of professional knowledge,clinical operation skills,communication skills,and emergency response capabilities,as well as strengthen their professional identity and sense of responsibility.It provides an effective way to cultivate high-quality nursing talents who can meet the needs of neurology nursing work and promotes the innovative development of nursing education.
基金Hangzhou Philosophy and Social Science Planning Program(24JD15)。
文摘National Fire codes,mandated by government authorities to tackle technical challenges in fire prevention and control,establish fundamental standards for construction practices.International collaboration in fire protection technologies has opened avenues for China to access a wealth of documents and codes,which are crucial in crafting regulations and developing a robust,scientific framework for fire code formulation.However,the translation of these codes into Chinese has been inadequate,thereby diminishing the benefits of technological exchange and collaborative learning.This underscores the necessity for comprehensive research into code translation,striving for higher-quality translations guided by established translation theories.In this study,we translated the initial segment of the NFPA 1 Fire Code into Chinese and examined both the source text and target text through the lens of Translation Shift Theory,a concept introduced by Catford.The conclusion culminated in identifying four key shifts across various linguistic levels:lexis,sentences,and groups,to ensure an accurate and precise translation of fire codes.This study offers a through and lucid explanation of how the translator integrates Catford’s theories to solve technical challenges in NFPA 1 Fire Code translation,and establish essential standards for construction translation practices.
基金the National Natural Science Foundation of China(NSFC)(Grant Nos.42030105,42274011,42074019,41974034,42204006)。
文摘Highly accurate international height reference frames with long-term stability,global consistency,and homogeneity are crucial for monitoring sea level variations,understanding climate change,managing disasters,and supporting other applications that benefit scientific research and societal well-being.Currently,there are over 100 local height reference systems worldwide.Unifying these systems is a pivotal step toward constructing international height reference frames.The method introduced in this study-the gravity frequency shift via Satellite Frequency Signal Transfer(SFST)-represents a groundbreaking relativistic geodetic approach,demonstrating its potential to surpass the constraints of conventional techniques.The advent of high-precision optical atomic clocks(OAC)with an accuracy level of 1×10^(-18) has facilitated this method's implementation.The International Association of Geodesy(IAG)has established the International Height Reference System(IHRS)and its practical realization,the International Height Reference Frame(IHRF).Our study focuses on two neighbouring height systems:the China Height System(CHS)and the Nepal Height System(NHS),separated by the Himalayas and the Xizang plateau.We aim to unify these two systems by determining the geopotential and orthometric height differences between their respective height datum stations:the Qingdao Height Datum Station(QHDS)and the Madar Height Datum Station(MHDS)using a simulation experiment with the method mentioned above.Using an OAC with an accuracy of 1×10^(-18),we identified a geopotential difference of-8.348±0.464 m^(2)s^(-2) and an orthometric height difference of 0.786±0.047 m between QHDS and MHDS.These results suggest that the introduced method could unify any two height systems with fewcentimeter-level precision,emphasizing its significance in contributing to the construction of the IHRS/IHRF with today's required precision.In summary,the SFST technique is a novel geodetic method that offers an alternative for height system unification,delivering centimeter-level precision,surpassing traditional methods,and supporting the development of the IHRF.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.52171251 and U21062251)Program of Science and Technology Innovation of Dalian(Grant No.2022JJ12GX036).
文摘The degradation and nonlinear interactions of a two-breather solution of the Mel’nikov equation are analyzed.By modulating the phase shift and limit method,we prove that in different regions near the non-singular boundaries,there are four kinds of solutions with repulsive interaction or attractive interaction in addition to the two-breather solution.They are the interaction solution between soliton and breather,the two-soliton solution,and the two-breather solution with small amplitude,which all exhibit repulsive interactions;and the two-breather solution with small amplitude,which exhibits attractive interaction.Interestingly,a new breather acts as a messenger to transfer energy during the interaction between two breather solutions with small amplitude.
文摘The phenomenon of verbal-to-nominal shift(hereafter referred to as“V-N shift”)exists in both English and Chinese.It reflects both the universal conceptual metonymic thinking and the principle of linguistic economy.Focusing on conceptual metonymy theory and combined with the Event Idealized Cognitive Model(ICM),this paper systematically compares the V-N shift phenomenon in English and Chinese.The study shows that English and Chinese V-N shifts share the core cognitive mechanism of“conceptual proximity within the Event ICM”,while significant differences exist in type distribution and usage frequency.This analysis not only helps deepen the understanding of the cognitive logic behind English and Chinese V-N shifts but also provides a new perspective for the study of word-class conversion and the relationship between language and thinking.
基金supported by the National Natural Science Foundation of China(Grant Nos.12204412,12274423,12174402,12393821,and 12004124)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant Nos.XDB0920100 and XDB0920101)support from the Natural Sciences and Engineering Research Council of Canada.All calculations were performed on the APM-Theoretical Computing Cluster(APM-TCC).
文摘Standard perturbation theory is employed to calculate the mass shifts of the 2^(1)S_(0)-^(3)S_(1)and 2^(3)S_(1)-2^(3)P_(J)transitions for^(4,6,8)He.High-precision results are obtained for the mass shifts in the isotope pairs 6He-4He and 8He-4He,with uncertainties below 1 part per million(ppm).Our analysis provides a complete set of isotope-shift results and systematically examines their sensitivity to nuclear charge-radius differences.Once experimental measurements reach a precision comparable to that of the calculated mass shifts,the squared differences of nuclear charge radii can be determined with an accuracy of approximately 0.4%-0.6%,representing an order-of-magnitude improvement over current values.
基金supported by grants from the National Natural Science Foundation of China(Grant No.32271733)Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515011045)+1 种基金Science and Technology Projects in Guangzhou(Grant No.2023A04J0121)SCNU Training Program of Innovation for Undergraduates,China。
文摘Anthropogenic climate change is altering species distributions globally.While species distributions are expected to shift to higher latitudes and elevations under global warming,empirical evidence on distribution shifts is mixed,and factors mediating the direction and magnitude of range shifts remain unclear.Using a dataset of 132new provincial records for 96 resident bird species from 2000 to 2023,we measured geographic distance,latitudinal shift,and temperature shift from each new record to the historical range for each species to test for poleward shifts.We assessed taxonomic variation in the magnitude of range shifts and used phylogenetic generalized linear mixed models to quantify relationships between species traits and the extent of range shifts.Our results revealed that new records occurred at a mean geographic distance of 420 km from historical ranges,with mean latitudinal shifts of+1.68°(poleward)and temperature shifts of-1.33℃(toward colder climates).The magnitude of geographic range shifts was strongly constrained by phylogenetic relatedness.Habitat breadth,habitat openness,and centroid latitude of historical ranges emerged as significant predictors of range shifts.Our results suggest that resident bird species'geographic ranges in China are shifting poleward,but the magnitude of these shifts is non-random across lineages.Species with broader habitat preferences and those from warmer climates are more likely to shift farther from their historical ranges and toward higher latitudes.This study emphasizes taxonomic variation in species range shifts and highlights the need for species-and site-specific conservation strategies under global warming.
文摘Gait recognition,a promising biometric technology,relies on analyzing individuals' walking patterns and offers a non-intrusive and convenient approach to identity verification.However,gait recognition accuracy is often compromised by external factors such as changes in viewpoint and attire,which present substantial challenges in practical applications.To enhance gait recognition performance under diverse viewpoints and complex conditions,a global-local part-shift network is proposed in this paper.This framework integrates two novel modules:the part-shift feature extractor and the dynamic feature aggregator.The part-shift feature extractor strategically shifts body parts to capture the intrinsic relationships between non-adjacent regions,enriching the recognition process with both global and local spatial features.The dynamic feature aggregator addresses long-range dependency issues by incorporating multi-range temporal modeling,effectively aggregating information across parts and time steps to achieve a more robust recognition outcome.Comprehensive experiments on the CASIA-B dataset demonstrate that the proposed global-local part-shift network delivers superior performance compared with state-of-the-art methods,highlighting its potential for practical deployment.
