The goal of this study was to determine the spatiotemporal characteristics of mangrove distribution and fragmentation patterns from 1988 through 2019 in Dongzhaigang.Land cover datasets were generated for Dongzhaigang...The goal of this study was to determine the spatiotemporal characteristics of mangrove distribution and fragmentation patterns from 1988 through 2019 in Dongzhaigang.Land cover datasets were generated for Dongzhaigang for multiple years via a decision tree method based on a classification and regression tree(CART)algorithm using Landsat time series images.Spatiotemporal transform and fragmentation patterns of mangrove distribution were separately assessed with a transfer matrix of land cover types and a landscape pattern index.The classification method combined with multi-band images showed good accuracy,with overall accuracy higher than 90%.Mangrove areas in 1988,1999,2009,and 2019 were 2050,1875,1818,and 1750 ha,respectively,with decreases mainly due to conversion to aquaculture ponds and farmland.A mangrove growth index(MGI)was proposed,reflecting the water-mangrove relationship,showing positive mangrove growth from 1988–2009 and negative growth from 2009–2019.Study results indicated anthropogenic factors play a leading role in the extent and scale of mangrove effects over the past 30 years.According to the analysis results,corresponding management and protection measures are proposed to provide reference for the sustainable development of Dongzhaigang Mangrove Wetland ecosystem.展开更多
Transit managers can use Intelligent Transportation System technologies to access large amounts of data to monitor network status.However,the presentation of the data lacks structural information.Existing single-netwo...Transit managers can use Intelligent Transportation System technologies to access large amounts of data to monitor network status.However,the presentation of the data lacks structural information.Existing single-network description technologies are ineffective in representing the temporal and spatial characteristics simultaneously.Therefore,there is a need for complementary methods to address these deficiencies.To address these limitations,this paper proposes an approach that combines Network Snapshots and Temporal Paths for the scheduled system.A dual information network is constructed to assess the degree of operational deviation considering the planning tasks.To validate the effectiveness,discussions are conducted through a modified cosine similarity calculation on theoretical analysis,delay level description,and the ability to identify abnormal dates.Compared to some state-of-the-art methods,the proposed method achieves an average Spearman delay correlation of 0.847 and a relative distance of 3.477.Furthermore,case analyses are invested in regions of China's Mainland,Europe,and the United States,investigating both the overall and sub-regional network fluctuations.To represent the impact of network fluctuations in sub-regions,a response loss value was developed.The times that are prone to fluctuations are also discussed through the classification of time series data.The research can offer a novel approach to system monitoring,providing a research direction that utilizes individual data combined to represent macroscopic states.Our code will be released at https://github.com/daozhong/STPN.git.展开更多
As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limite...As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants.To address this,this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022.The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data.Temporally,there were pronounced seasonal variations in air pollutants.Spatially,high concentration of HCHO and NO_(2)were closely associated with traffic congestion on roadways,while heightened SO_(2)levels were attributed to winter heating and industrial emissions.The study also revealed that with the implementation of road policies,the average vehicle speed increased by 95.4%,while the NO concentration decreased by 54.4%.In the estimation of urban NO_(x)emission flux,it was observed that in temporal terms,compared with inventory data,the emissions calculated viamobile measurements exhibitedmore distinct seasonal patterns,with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer.In spatial terms,the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city’s primary NO_(x)emission sources in the area between these two rings.This study offers data support for formulating the next phase of air pollution control measures in urban areas.展开更多
In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed p...In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed panel data from the Yellow River(YR)region from 2013 to 2021 and discovered notable spatial variances in the composite index and coupling coordination of the two systems.Specifically,the downstream region exhibited the highest coupling coordination,while the upstream region had the lowest.We identified that favorable factors such as economic development,innovation,industrial upgrading,and government intervention can bolster the coupling.Our findings provide a valuable framework for promoting DE and HQD in the YR region.展开更多
Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address ...Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a T-GCN module. Thirdly, a transformer layer is introduced to learn the long-term dependence in time. A position embedding mechanism is introduced to label position information for all traffic sequences. Thus, this multi-head self-attention mechanism can recognize the sequence order and allocate weights for different time nodes. Experimental results on four real-world datasets show that the MSSTGCN performs better than the baseline methods and can be successfully adapted to traffic prediction tasks.展开更多
Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaboratio...Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaborations,and edge computing,spatial-temporal traffic data has taken on a distributed nature.Consequently,noncentralized spatial-temporal traffic prediction solutions have emerged as a recent research focus.Currently,the majority of research typically adopts federated learning methods to train traffic prediction models distributed on each base station.This method reduces additional burden on communication systems.However,this method has a drawback:it cannot handle irregular traffic data.Due to unstable wireless network environments,device failures,insufficient storage resources,etc.,data missing inevitably occurs during the process of collecting traffic data.This results in the irregular nature of distributed traffic data.Yet,commonly used traffic prediction models such as Recurrent Neural Networks(RNN)and Long Short-Term Memory(LSTM)typically assume that the data is complete and regular.To address the challenge of handling irregular traffic data,this paper transforms irregular traffic prediction into problems of estimating latent variables and generating future traffic.To solve the aforementioned problems,this paper introduces split learning to design a structured distributed learning framework.The framework comprises a Global-level Spatial structure mining Model(GSM)and several Nodelevel Generative Models(NGMs).NGM and GSM represent Seq2Seq models deployed on the base station and graph neural network models deployed on the cloud or central controller.Firstly,the time embedding layer in NGM establishes the mapping relationship between irregular traffic data and regular latent temporal feature variables.Secondly,GSM collects statistical feature parameters of latent temporal feature variables from various nodes and executes graph embedding for spatial-temporal traffic data.Finally,NGM generates future traffic based on latent temporal and spatial feature variables.The introduction of the time attention mechanism enhances the framework’s capability to handle irregular traffic data.Graph attention network introduces spatially correlated base station traffic feature information into local traffic prediction,which compensates for missing information in local irregular traffic data.The proposed framework effectively addresses the distributed prediction issues of irregular traffic data.By testing on real world datasets,the proposed framework improves traffic prediction accuracy by 35%compared to other commonly used distributed traffic prediction methods.展开更多
Behavior recognition of Hu sheep contributes to their intensive and intelligent farming.Due to the generally high density of Hu sheep farming,severe occlusion occurs among different behaviors and even among sheep perf...Behavior recognition of Hu sheep contributes to their intensive and intelligent farming.Due to the generally high density of Hu sheep farming,severe occlusion occurs among different behaviors and even among sheep performing the same behavior,leading to missing and false detection issues in existing behavior recognition methods.A high-low frequency aggregated attention and negative sample comprehensive score loss and comprehensive score soft non-maximum suppression-YOLO(HLNC-YOLO)was proposed for identifying the behavior of Hu sheep,addressing the issues of missed and erroneous detections caused by occlusion between Hu sheep in intensive farming.Firstly,images of four typical behaviors-standing,lying,eating,and drinking-were collected from the sheep farm to construct the Hu sheep behavior dataset(HSBD).Next,to solve the occlusion issues,during the training phase,the C2F-HLAtt module was integrated,which combined high-low frequency aggregation attention,into the YOLO v8 Backbone to perceive occluded objects and introduce an auxiliary reversible branch to retain more effective features.Using comprehensive score regression loss(CSLoss)to reduce the scores of suboptimal boxes and enhance the comprehensive scores of occluded object boxes.Finally,the soft comprehensive score non-maximal suppression(Soft-CS-NMS)algorithm filtered prediction boxes during the inferencing.Testing on the HSBD,HLNC-YOLO achieved a mean average precision(mAP@50)of 87.8%,with a memory footprint of 17.4 MB.This represented an improvement of 7.1,2.2,4.6,and 11 percentage points over YOLO v8,YOLO v9,YOLO v10,and Faster R-CNN,respectively.Research indicated that the HLNC-YOLO accurately identified the behavior of Hu sheep in intensive farming and possessed generalization capabilities,providing technical support for smart farming.展开更多
To investigate the influence of Al-Zn-Mg-Cu alloy with as-homogenized and as-rolled initial microstructures on the tensile flow behavior,isothermal tensile tests were conducted on a GLEEBLE-3500 isothermal simulator a...To investigate the influence of Al-Zn-Mg-Cu alloy with as-homogenized and as-rolled initial microstructures on the tensile flow behavior,isothermal tensile tests were conducted on a GLEEBLE-3500 isothermal simulator at temperatures of 380-440℃and strain rates of 0.05-1 s^(−1).The Johnson-Cook model,Hensel-Spittel model,strain-compensated Arrhenius model,and critical fracture strain model were established.Results show that through the evaluation of the models using the correlation coefficient(R)and the average absolute relative error,the strain-compensated Arrhenius model can represent the flow behavior of the alloy more accurately.Shear bands are more pronounced in the as-homogenized specimens,whereas dynamic recrystallization is predominantly observed in as-rolled specimens.Fracture morphology analysis reveals that a mixed fracture mechanism is prevalent in the as-homogenized specimen,whereas a ductile fracture mechanism is predominant in the as-rolled specimen.The processing maps indicate that the unstable region is reduced in the as-rolled specimens compared with that in the as-homogenized specimens.The optimal hot working windows for the as-homogenized and as-rolled specimens are determined as 410-440℃/0.14-1 s^(−1)and 380-400℃/0.05-0.29 s^(−1),respectively.展开更多
In this article,by employing the Hirota bilinear approach and the long wave limit method,we not only derive soliton solutions,lump solutions,and hybrid solutions for the(2+1)-dimensional Yu-Toda-Sasa-Fukuyama(YTSF)equ...In this article,by employing the Hirota bilinear approach and the long wave limit method,we not only derive soliton solutions,lump solutions,and hybrid solutions for the(2+1)-dimensional Yu-Toda-Sasa-Fukuyama(YTSF)equation,but also analyze the dynamical behaviors of nonlinear local wave propagation in shallow water.Firstly,based on the Hirota bilinear approach,one to four-order soliton solutions of the YTSF equation are obtained,and the effects of different parameters on the amplitude,propagation trajectory,and displacement of solitons are investigated.Secondly,using the long wave limit approach,one to three-order lump solutions and various physical quantities of the YTSF equation are derived.It is found that the real and imaginary parts of the parameter pi dominate the propagation trajectory and the shape of lump waves,respectively.Furthermore,we construct the hybrid solution for the YTSF equation,leading to the conclusion that the interaction between lumps and solitons constitutes an elastic collision.To intuitively understand the dynamic behaviors of these solutions,we conduct numerical simulations to present vivid three-dimensional visualizations.展开更多
Correction to:Nano-Micro Letters(2026)18:10.https://doi.org/10.1007/s40820-025-01852-8 Following publication of the original article[1],the authors reported that the last author’s name was inadvertently misspelled.Th...Correction to:Nano-Micro Letters(2026)18:10.https://doi.org/10.1007/s40820-025-01852-8 Following publication of the original article[1],the authors reported that the last author’s name was inadvertently misspelled.The published version showed“Hongzhen Chen”,whereas the correct spelling should be“Hongzheng Chen”.The correct author name has been provided in this Correction,and the original article[1]has been corrected.展开更多
Background:Adolescent suicide remains a pressing public health concern in South Korea and worldwide,ranking as one of the leading causes of death among youth.Identifying modifiable risk and protective factors is criti...Background:Adolescent suicide remains a pressing public health concern in South Korea and worldwide,ranking as one of the leading causes of death among youth.Identifying modifiable risk and protective factors is critical for prevention strategies.Physical activity has been suggested as one such factor due to its potential mental health benefits.This study aimed to examine whether associations between physical activity and suicidality differ by activity type and by stage of suicidal behavior,distinguishing suicidal ideation,planning,and attempts among Korean adolescents.Methods:This cross-sectional secondary analysis used data from the 20th Korea Youth Risk Behavior Web-based Survey(KYRBS)conducted in 2024,a nationally representative survey of Korean adolescents.The study included 54,653 middle and high school students with complete data on physical activity,suicidal ideation,planning,and attempts.Three types of physical activity(vigorous activity,muscle-strengthening activity,and≥60 min of daily physical activity)were examined.Associations with suicidal behaviors were analyzed using multivariable logistic regression models,adjusting for psychological,behavioral,and sociodemographic covariates.Results:In this nationally representative sample of Korean adolescents,engaging in at least 60 min of daily physical activity was significantly associated with lower odds of suicide planning,but not ideation or attempts.In contrast,muscle-strengthening activity was linked to increased odds of both suicide planning and attempts,whereas vigorous activity showed no significant associations.Psychological factors,including generalized anxiety,sadness,stress,and loneliness,showed strong associations with suicidal behaviors and were included as covariates in the adjusted models.Female students,low academic performance,and unstable residential status were also associated with higher odds of suicidal behaviors.Conclusion:The associations between physical activity and suicidality differed by activity type and suicidal outcome;muscle-strengthening activity was positively associated with suicide planning and attempts in adjusted models.展开更多
Residential energy-use behavior and energy-saving awareness play a crucial role in sustainable urban energy planning and building energy efficiency,particularly under the pressures of climate change.However,existing s...Residential energy-use behavior and energy-saving awareness play a crucial role in sustainable urban energy planning and building energy efficiency,particularly under the pressures of climate change.However,existing studies often lack comparative analysis of urban-rural differences and tend to focus excessively on behavior patterns while neglecting the dimension of energysaving awareness.With China’s urbanization rate reaching 66.16%,understanding such regional disparities has become increasingly important.To address these research gaps,this study conducts a large-scale survey on space cooling behaviors among residents in Beijing,a representative Chinese megacity.It should be noted that living standards in such megacities are generally higher than the national average,which may shape distinctive energy-use profiles.Analyzing 1573valid samples(1064 urban/442 rural)in 2024,this study employed K-Prototypes and K-Modes clustering to identify typical cooling behavior and energy-saving awareness pattems,followed by Kendall/Chi-square correlation tests and XGBoost importance analysis to determine key influencing factors,with subsequent urban-rural comparative analysis.Results indicate that urban residents are primarily heat-sensitive or heat-tolerant,with a secondary patten of mid-low temperature preference,and generally exhibit long cooling durations;rural behavior is dominated by heat-tolerant type,followed by heat-sensitive,mid-low temperature preference,and never-on types as secondary patterns;both urban and rural areas exhibit energy-savingawareness characterized by low consumption-lowwillingness,though urban areas show marginally higher motivation;energy-saving awareness correlates with cooling behavior in rural areas,but this relationship weakens significantly in urban contexts.展开更多
Eco-driving behaviors have been recommended around the world because the transport is a key factor of energy use and pollution emissions.Therefore,based on the driving decision model,this paper introduces three aspect...Eco-driving behaviors have been recommended around the world because the transport is a key factor of energy use and pollution emissions.Therefore,based on the driving decision model,this paper introduces three aspects of the driving decisions(strategic decision,tactical decision and operation decision)to analyze the economy of vehicle energy.The analytic hierarchy process(AHP)is used to assign the weight of the internal evaluation indexes,so as to form a complete assessment for drivers'eco-driving behaviors.The research result can not only quantitatively describe the energy-saving effect of drivers'decisions,but also put forward targeted driving suggestions to optimize drivers'eco-driving behaviors.This assessment model helps to clarify the potential of eco-driving on energy economy of transportation in a hierarchical way,and provides a valuable theoretical basis for the further promotion and application of eco-driving education.展开更多
The partial discharge occurring in the weak part of the insulation of a converter transformer results in the formation of a large number of bubbles in the insulating oil.The migration,deformation,and other dynamic beh...The partial discharge occurring in the weak part of the insulation of a converter transformer results in the formation of a large number of bubbles in the insulating oil.The migration,deformation,and other dynamic behaviors of bubbles in the region of a strong electric field can cause them to easily accumulate into“small bridges”of impurities that can lead to breakdown of the oil gap.The authors of this study experimentally investigate and discuss the mechanisms of migration and deformation of bubbles in oil during partial discharge under composite AC/DC voltage to clarify their dynamic behaviors.The influence of the initial position of the bubbles on their trajectory of migration and velocity as well as the morphological changes occurring in them are analyzed using numerical simulations.The results show that the bubbles move away from the strong electric field due to the action of the dielectrophoretic force.The interface of the bubbles is longitudinally stretched under the action of the electrostrictive force and the vertical component of the drag force and gradually recovers to assume a spherical shape under the influence of surface tension and the horizontal component of the drag force.展开更多
With the rapid development of smart manufacturing,intelligent safety monitoring in industrial workshops has become increasingly important.To address the challenges of complex backgrounds,target scale variation,and exc...With the rapid development of smart manufacturing,intelligent safety monitoring in industrial workshops has become increasingly important.To address the challenges of complex backgrounds,target scale variation,and excessive model parameters in worker violation detection,this study proposes ADCP-YOLO,an enhanced lightweight model based on YOLOv8.Here,“ADCP”represents four key improvements:Alterable Kernel Convolution(AKConv),Dilated-Wise Residual(DWR)module,Channel Reconstruction Global Attention Mechanism(CRGAM),and Powerful-IoU loss.These components collaboratively enhance feature extraction,multi-scale perception,and localization accuracy while effectively reducing model complexity and computational cost.Experimental results show that ADCP-YOLO achieves a mAP of 90.6%,surpassing YOLOv8 by 3.0%with a 6.6%reduction in parameters.These findings demonstrate that ADCP-YOLO successfully balances accuracy and efficiency,offering a practical solution for intelligent safety monitoring in smart factory workshops.展开更多
Loess landslides are major hazards in the Chinese Loess Plateau(CLP).The loess in this region is frequently subjected to repeated wetting–drying(W-D)cycles due to climatic factors,which significantly increases the li...Loess landslides are major hazards in the Chinese Loess Plateau(CLP).The loess in this region is frequently subjected to repeated wetting–drying(W-D)cycles due to climatic factors,which significantly increases the likelihood of landslides.Therefore,investigating the shear behavior and microstructural evolution of loess under climate-induced W-D cycles is crucial to understanding the mechanisms of loess landslides.In this study,Malan loess is analyzed using unsaturated triaxial tests,resistivity tests,scanning electron microscopy,and mercury intrusion porosimetry.The test results show that shear strength decreases with increased W-D cycles,and the degradation effect is more pronounced under lower confining pressure.The variations in conductive pathways indicate that electrical resistivity can effectively reflect the structural damage of loess during W-D cycles,which is associated with increased direct point contacts and spaced pores.Aggregation of clay particles and growth of cracks during the W-D cycles can further destabilize the loess microstructure.As the confining pressure increases,crushed particles rearrange and convert spaced pores into intergranular pores.The number and peak intensity of dominant spaced pores decrease,resulting in a more stable structure.This study clarifies the mechanisms of loess landslides under W-D cycles and provides theoretical support for landslide prevention and control in the CLP.展开更多
Objective: To understand the current status of peer caring behavior and empathy among undergraduate nursing students and to explore the relationship between the two. Method: Using the convenience sampling method, a qu...Objective: To understand the current status of peer caring behavior and empathy among undergraduate nursing students and to explore the relationship between the two. Method: Using the convenience sampling method, a questionnaire survey was conducted among 292 nursing students from a medical college in Jiangxi Province, using the Peer Caring Behavior Scale and the Jefferson Scale of Empathy. Results: The score for peer caring behavior among undergraduate nursing students was 85.00 (78.00-92.00), and the score for empathy was 101.00 (92.00-110.00). A positive correlation was found between the two (r = 0.362, p < 0.05). Conclusion: The level of peer caring behavior among undergraduate nursing students is above average, while their empathy level is moderate, with a positive correlation between the two. This suggests that nursing educators should strengthen the development of peer caring behavior, which may help enhance the empathy of undergraduate nursing students.展开更多
This study utilizes wet/dry cyclic corrosion testing combined with corrosion big data technology to investigate the mechanism by which chloride ions(Cl^(-))influence the corrosion behavior of 650 MPa high-strength low...This study utilizes wet/dry cyclic corrosion testing combined with corrosion big data technology to investigate the mechanism by which chloride ions(Cl^(-))influence the corrosion behavior of 650 MPa high-strength low-alloy(HSLA)steel in industrially polluted environments.The corrosion process of 650 MPa HSLA steel occurred in two distinct stages:an initial corrosion stage and a stable corrosion stage.During the initial phase,the weight loss rate increased rapidly owing to the instability of the rust layer.Notably,this study demonstrated that 650 MPa HSLA steel exhibited superior corrosion resistance in Cl-containing environments.The formation of a corrosion-product film eventually reduced the weight-loss rate.However,the intrusion of Cl^(-)at increasing concentrations gradually destabilized theα/γ^(*)phases of the rust layer,leading to a looser structure and lower polarization resistance(R_(p)).The application of corrosion big data technology in this study facilitated the validation and analysis of the experimental results,offering new insights into the corrosion mechanisms of HSLA steel in chloride-rich environments.展开更多
The volume change behavior of natural gas hydrate-bearing sediment is essential as it influences settlement,strength,and stiffness,which directly affect the stability of hydrate reservoirs during hydrate extraction or...The volume change behavior of natural gas hydrate-bearing sediment is essential as it influences settlement,strength,and stiffness,which directly affect the stability of hydrate reservoirs during hydrate extraction or in response to environmental changes.The volume change is influenced not only by stress but also by the formation and dissociation of hydrates.This study adopted a customized apparatus for one-dimensional compression tests,allowing independent control of gas pressure and effective stress.Tests were conducted on samples with different hydrate saturations along various temperature-gas pressure-effective stress paths,yielding some conclusions related to compressibility and creep.An unusual phenomenon was observed under low-stress conditions:hydrate formation led to shrinkage rather than expansion.Three potential mechanisms behind this occurrence were discussed.As hydrate saturation increases,the yield stress rises while the compression and swelling indexes remain minimally affected.After hydrate dissociation,the compression curve of hydrate-bearing sediment drops to that of hydrate-free sediment.Once hydrate is formed,the compression curve of hydrate-free sediment gradually approaches that of hydrate-bearing sediment during the subsequent loading.Under low-stress conditions,the creep of both hydrate-free and hydrate-bearing sediments is very weak.However,when stress increases,significantly beyond the yield stress,the creep of both sediments increases significantly,with hydrate-bearing sediment exhibiting much greater creep than hydrate-free sediment.展开更多
Objective: To analyze the impact of motivational nursing under the solution-focused approach on health behaviors in surgical care for bladder cancer patients. Methods: A sample of 72 bladder cancer patients who underw...Objective: To analyze the impact of motivational nursing under the solution-focused approach on health behaviors in surgical care for bladder cancer patients. Methods: A sample of 72 bladder cancer patients who underwent surgical treatment from September 2024 to September 2025 was randomly divided into groups using a random number table. Group A received motivational nursing under the solution-focused approach, while Group B received conventional nursing. Health behavior scores and complication indicators were compared between the two groups. Results: Group A had higher scores on the Health-Promoting Lifestyle Profile II (HPLP-Ⅱ) than Group B, with p < 0.05. The postoperative complication rate in Group A was lower than that in Group B, with p < 0.05. Conclusion: For bladder cancer patients undergoing surgery, receiving motivational nursing under the solution-focused approach can improve health behaviors, alleviate negative emotions, and is highly feasible and effective.展开更多
基金financially supported by the National Natural Science Foundation of China(Nos.U2244225 and 42020104005)the Ministry of Education of China(111 Project)the Fundamental Research Funds for the Central Universities,China University of Geosciences(Wuhan)and China Geological Survey(No.DD20211391)。
文摘The goal of this study was to determine the spatiotemporal characteristics of mangrove distribution and fragmentation patterns from 1988 through 2019 in Dongzhaigang.Land cover datasets were generated for Dongzhaigang for multiple years via a decision tree method based on a classification and regression tree(CART)algorithm using Landsat time series images.Spatiotemporal transform and fragmentation patterns of mangrove distribution were separately assessed with a transfer matrix of land cover types and a landscape pattern index.The classification method combined with multi-band images showed good accuracy,with overall accuracy higher than 90%.Mangrove areas in 1988,1999,2009,and 2019 were 2050,1875,1818,and 1750 ha,respectively,with decreases mainly due to conversion to aquaculture ponds and farmland.A mangrove growth index(MGI)was proposed,reflecting the water-mangrove relationship,showing positive mangrove growth from 1988–2009 and negative growth from 2009–2019.Study results indicated anthropogenic factors play a leading role in the extent and scale of mangrove effects over the past 30 years.According to the analysis results,corresponding management and protection measures are proposed to provide reference for the sustainable development of Dongzhaigang Mangrove Wetland ecosystem.
文摘Transit managers can use Intelligent Transportation System technologies to access large amounts of data to monitor network status.However,the presentation of the data lacks structural information.Existing single-network description technologies are ineffective in representing the temporal and spatial characteristics simultaneously.Therefore,there is a need for complementary methods to address these deficiencies.To address these limitations,this paper proposes an approach that combines Network Snapshots and Temporal Paths for the scheduled system.A dual information network is constructed to assess the degree of operational deviation considering the planning tasks.To validate the effectiveness,discussions are conducted through a modified cosine similarity calculation on theoretical analysis,delay level description,and the ability to identify abnormal dates.Compared to some state-of-the-art methods,the proposed method achieves an average Spearman delay correlation of 0.847 and a relative distance of 3.477.Furthermore,case analyses are invested in regions of China's Mainland,Europe,and the United States,investigating both the overall and sub-regional network fluctuations.To represent the impact of network fluctuations in sub-regions,a response loss value was developed.The times that are prone to fluctuations are also discussed through the classification of time series data.The research can offer a novel approach to system monitoring,providing a research direction that utilizes individual data combined to represent macroscopic states.Our code will be released at https://github.com/daozhong/STPN.git.
基金supported by the National Natural Science Foundation of China(Nos.U19A2044,42105132,42030609,41975037,and 42105133)the National Key Research and Development Program of China(No.2022YFC3703502)+1 种基金the Plan for Anhui Major Provincial Science&Technology Project(No.202203a07020003)Hefei Ecological Environment Bureau Project(No.2020BFFFD01804).
文摘As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants.To address this,this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022.The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data.Temporally,there were pronounced seasonal variations in air pollutants.Spatially,high concentration of HCHO and NO_(2)were closely associated with traffic congestion on roadways,while heightened SO_(2)levels were attributed to winter heating and industrial emissions.The study also revealed that with the implementation of road policies,the average vehicle speed increased by 95.4%,while the NO concentration decreased by 54.4%.In the estimation of urban NO_(x)emission flux,it was observed that in temporal terms,compared with inventory data,the emissions calculated viamobile measurements exhibitedmore distinct seasonal patterns,with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer.In spatial terms,the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city’s primary NO_(x)emission sources in the area between these two rings.This study offers data support for formulating the next phase of air pollution control measures in urban areas.
基金supported by the National Office for Philosophy and Social Sciences(grant reference 22&ZD067).
文摘In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed panel data from the Yellow River(YR)region from 2013 to 2021 and discovered notable spatial variances in the composite index and coupling coordination of the two systems.Specifically,the downstream region exhibited the highest coupling coordination,while the upstream region had the lowest.We identified that favorable factors such as economic development,innovation,industrial upgrading,and government intervention can bolster the coupling.Our findings provide a valuable framework for promoting DE and HQD in the YR region.
基金supported by the National Natural Science Foundation of China(Grant Nos.62472149,62376089,62202147)Hubei Provincial Science and Technology Plan Project(2023BCB04100).
文摘Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a T-GCN module. Thirdly, a transformer layer is introduced to learn the long-term dependence in time. A position embedding mechanism is introduced to label position information for all traffic sequences. Thus, this multi-head self-attention mechanism can recognize the sequence order and allocate weights for different time nodes. Experimental results on four real-world datasets show that the MSSTGCN performs better than the baseline methods and can be successfully adapted to traffic prediction tasks.
基金supported by the Beijing Natural Science Foundation(Certificate Number:L234025).
文摘Spatial-temporal traffic prediction technology is crucial for network planning,resource allocation optimizing,and user experience improving.With the development of virtual network operators,multi-operator collaborations,and edge computing,spatial-temporal traffic data has taken on a distributed nature.Consequently,noncentralized spatial-temporal traffic prediction solutions have emerged as a recent research focus.Currently,the majority of research typically adopts federated learning methods to train traffic prediction models distributed on each base station.This method reduces additional burden on communication systems.However,this method has a drawback:it cannot handle irregular traffic data.Due to unstable wireless network environments,device failures,insufficient storage resources,etc.,data missing inevitably occurs during the process of collecting traffic data.This results in the irregular nature of distributed traffic data.Yet,commonly used traffic prediction models such as Recurrent Neural Networks(RNN)and Long Short-Term Memory(LSTM)typically assume that the data is complete and regular.To address the challenge of handling irregular traffic data,this paper transforms irregular traffic prediction into problems of estimating latent variables and generating future traffic.To solve the aforementioned problems,this paper introduces split learning to design a structured distributed learning framework.The framework comprises a Global-level Spatial structure mining Model(GSM)and several Nodelevel Generative Models(NGMs).NGM and GSM represent Seq2Seq models deployed on the base station and graph neural network models deployed on the cloud or central controller.Firstly,the time embedding layer in NGM establishes the mapping relationship between irregular traffic data and regular latent temporal feature variables.Secondly,GSM collects statistical feature parameters of latent temporal feature variables from various nodes and executes graph embedding for spatial-temporal traffic data.Finally,NGM generates future traffic based on latent temporal and spatial feature variables.The introduction of the time attention mechanism enhances the framework’s capability to handle irregular traffic data.Graph attention network introduces spatially correlated base station traffic feature information into local traffic prediction,which compensates for missing information in local irregular traffic data.The proposed framework effectively addresses the distributed prediction issues of irregular traffic data.By testing on real world datasets,the proposed framework improves traffic prediction accuracy by 35%compared to other commonly used distributed traffic prediction methods.
文摘Behavior recognition of Hu sheep contributes to their intensive and intelligent farming.Due to the generally high density of Hu sheep farming,severe occlusion occurs among different behaviors and even among sheep performing the same behavior,leading to missing and false detection issues in existing behavior recognition methods.A high-low frequency aggregated attention and negative sample comprehensive score loss and comprehensive score soft non-maximum suppression-YOLO(HLNC-YOLO)was proposed for identifying the behavior of Hu sheep,addressing the issues of missed and erroneous detections caused by occlusion between Hu sheep in intensive farming.Firstly,images of four typical behaviors-standing,lying,eating,and drinking-were collected from the sheep farm to construct the Hu sheep behavior dataset(HSBD).Next,to solve the occlusion issues,during the training phase,the C2F-HLAtt module was integrated,which combined high-low frequency aggregation attention,into the YOLO v8 Backbone to perceive occluded objects and introduce an auxiliary reversible branch to retain more effective features.Using comprehensive score regression loss(CSLoss)to reduce the scores of suboptimal boxes and enhance the comprehensive scores of occluded object boxes.Finally,the soft comprehensive score non-maximal suppression(Soft-CS-NMS)algorithm filtered prediction boxes during the inferencing.Testing on the HSBD,HLNC-YOLO achieved a mean average precision(mAP@50)of 87.8%,with a memory footprint of 17.4 MB.This represented an improvement of 7.1,2.2,4.6,and 11 percentage points over YOLO v8,YOLO v9,YOLO v10,and Faster R-CNN,respectively.Research indicated that the HLNC-YOLO accurately identified the behavior of Hu sheep in intensive farming and possessed generalization capabilities,providing technical support for smart farming.
文摘To investigate the influence of Al-Zn-Mg-Cu alloy with as-homogenized and as-rolled initial microstructures on the tensile flow behavior,isothermal tensile tests were conducted on a GLEEBLE-3500 isothermal simulator at temperatures of 380-440℃and strain rates of 0.05-1 s^(−1).The Johnson-Cook model,Hensel-Spittel model,strain-compensated Arrhenius model,and critical fracture strain model were established.Results show that through the evaluation of the models using the correlation coefficient(R)and the average absolute relative error,the strain-compensated Arrhenius model can represent the flow behavior of the alloy more accurately.Shear bands are more pronounced in the as-homogenized specimens,whereas dynamic recrystallization is predominantly observed in as-rolled specimens.Fracture morphology analysis reveals that a mixed fracture mechanism is prevalent in the as-homogenized specimen,whereas a ductile fracture mechanism is predominant in the as-rolled specimen.The processing maps indicate that the unstable region is reduced in the as-rolled specimens compared with that in the as-homogenized specimens.The optimal hot working windows for the as-homogenized and as-rolled specimens are determined as 410-440℃/0.14-1 s^(−1)and 380-400℃/0.05-0.29 s^(−1),respectively.
基金Supported by the National Natural Science Foundation of China(12001424,12271324)the Natural Science Basic research program of Shaanxi Province(2021JZ-21)+1 种基金the China Postdoctoral Science Foundation(2020M673332)Xi’an University,Xi’an Science and Technology Plan Wutongshu Technology Transfer Action Innovation Team(25WTZD07)。
文摘In this article,by employing the Hirota bilinear approach and the long wave limit method,we not only derive soliton solutions,lump solutions,and hybrid solutions for the(2+1)-dimensional Yu-Toda-Sasa-Fukuyama(YTSF)equation,but also analyze the dynamical behaviors of nonlinear local wave propagation in shallow water.Firstly,based on the Hirota bilinear approach,one to four-order soliton solutions of the YTSF equation are obtained,and the effects of different parameters on the amplitude,propagation trajectory,and displacement of solitons are investigated.Secondly,using the long wave limit approach,one to three-order lump solutions and various physical quantities of the YTSF equation are derived.It is found that the real and imaginary parts of the parameter pi dominate the propagation trajectory and the shape of lump waves,respectively.Furthermore,we construct the hybrid solution for the YTSF equation,leading to the conclusion that the interaction between lumps and solitons constitutes an elastic collision.To intuitively understand the dynamic behaviors of these solutions,we conduct numerical simulations to present vivid three-dimensional visualizations.
文摘Correction to:Nano-Micro Letters(2026)18:10.https://doi.org/10.1007/s40820-025-01852-8 Following publication of the original article[1],the authors reported that the last author’s name was inadvertently misspelled.The published version showed“Hongzhen Chen”,whereas the correct spelling should be“Hongzheng Chen”.The correct author name has been provided in this Correction,and the original article[1]has been corrected.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2023-NR076968)the Chung-Ang University Graduate Research Scholarship in 2024.
文摘Background:Adolescent suicide remains a pressing public health concern in South Korea and worldwide,ranking as one of the leading causes of death among youth.Identifying modifiable risk and protective factors is critical for prevention strategies.Physical activity has been suggested as one such factor due to its potential mental health benefits.This study aimed to examine whether associations between physical activity and suicidality differ by activity type and by stage of suicidal behavior,distinguishing suicidal ideation,planning,and attempts among Korean adolescents.Methods:This cross-sectional secondary analysis used data from the 20th Korea Youth Risk Behavior Web-based Survey(KYRBS)conducted in 2024,a nationally representative survey of Korean adolescents.The study included 54,653 middle and high school students with complete data on physical activity,suicidal ideation,planning,and attempts.Three types of physical activity(vigorous activity,muscle-strengthening activity,and≥60 min of daily physical activity)were examined.Associations with suicidal behaviors were analyzed using multivariable logistic regression models,adjusting for psychological,behavioral,and sociodemographic covariates.Results:In this nationally representative sample of Korean adolescents,engaging in at least 60 min of daily physical activity was significantly associated with lower odds of suicide planning,but not ideation or attempts.In contrast,muscle-strengthening activity was linked to increased odds of both suicide planning and attempts,whereas vigorous activity showed no significant associations.Psychological factors,including generalized anxiety,sadness,stress,and loneliness,showed strong associations with suicidal behaviors and were included as covariates in the adjusted models.Female students,low academic performance,and unstable residential status were also associated with higher odds of suicidal behaviors.Conclusion:The associations between physical activity and suicidality differed by activity type and suicidal outcome;muscle-strengthening activity was positively associated with suicide planning and attempts in adjusted models.
文摘Residential energy-use behavior and energy-saving awareness play a crucial role in sustainable urban energy planning and building energy efficiency,particularly under the pressures of climate change.However,existing studies often lack comparative analysis of urban-rural differences and tend to focus excessively on behavior patterns while neglecting the dimension of energysaving awareness.With China’s urbanization rate reaching 66.16%,understanding such regional disparities has become increasingly important.To address these research gaps,this study conducts a large-scale survey on space cooling behaviors among residents in Beijing,a representative Chinese megacity.It should be noted that living standards in such megacities are generally higher than the national average,which may shape distinctive energy-use profiles.Analyzing 1573valid samples(1064 urban/442 rural)in 2024,this study employed K-Prototypes and K-Modes clustering to identify typical cooling behavior and energy-saving awareness pattems,followed by Kendall/Chi-square correlation tests and XGBoost importance analysis to determine key influencing factors,with subsequent urban-rural comparative analysis.Results indicate that urban residents are primarily heat-sensitive or heat-tolerant,with a secondary patten of mid-low temperature preference,and generally exhibit long cooling durations;rural behavior is dominated by heat-tolerant type,followed by heat-sensitive,mid-low temperature preference,and never-on types as secondary patterns;both urban and rural areas exhibit energy-savingawareness characterized by low consumption-lowwillingness,though urban areas show marginally higher motivation;energy-saving awareness correlates with cooling behavior in rural areas,but this relationship weakens significantly in urban contexts.
文摘Eco-driving behaviors have been recommended around the world because the transport is a key factor of energy use and pollution emissions.Therefore,based on the driving decision model,this paper introduces three aspects of the driving decisions(strategic decision,tactical decision and operation decision)to analyze the economy of vehicle energy.The analytic hierarchy process(AHP)is used to assign the weight of the internal evaluation indexes,so as to form a complete assessment for drivers'eco-driving behaviors.The research result can not only quantitatively describe the energy-saving effect of drivers'decisions,but also put forward targeted driving suggestions to optimize drivers'eco-driving behaviors.This assessment model helps to clarify the potential of eco-driving on energy economy of transportation in a hierarchical way,and provides a valuable theoretical basis for the further promotion and application of eco-driving education.
基金supported by the National Natural Science Foundation of China(No.U1966209)the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(NCEPU,LAPS22001).
文摘The partial discharge occurring in the weak part of the insulation of a converter transformer results in the formation of a large number of bubbles in the insulating oil.The migration,deformation,and other dynamic behaviors of bubbles in the region of a strong electric field can cause them to easily accumulate into“small bridges”of impurities that can lead to breakdown of the oil gap.The authors of this study experimentally investigate and discuss the mechanisms of migration and deformation of bubbles in oil during partial discharge under composite AC/DC voltage to clarify their dynamic behaviors.The influence of the initial position of the bubbles on their trajectory of migration and velocity as well as the morphological changes occurring in them are analyzed using numerical simulations.The results show that the bubbles move away from the strong electric field due to the action of the dielectrophoretic force.The interface of the bubbles is longitudinally stretched under the action of the electrostrictive force and the vertical component of the drag force and gradually recovers to assume a spherical shape under the influence of surface tension and the horizontal component of the drag force.
基金TheNationalNatural Science Foundation ofChina(Nos.62272418,62102058)Zhejiang Provincial Natural Science Foundation Major Project(No.LD24F020004)the Major Open Project of Key Laboratory for Advanced Design and Intelligent Computing of the Ministry of Education(No.ADIC2023ZD001).
文摘With the rapid development of smart manufacturing,intelligent safety monitoring in industrial workshops has become increasingly important.To address the challenges of complex backgrounds,target scale variation,and excessive model parameters in worker violation detection,this study proposes ADCP-YOLO,an enhanced lightweight model based on YOLOv8.Here,“ADCP”represents four key improvements:Alterable Kernel Convolution(AKConv),Dilated-Wise Residual(DWR)module,Channel Reconstruction Global Attention Mechanism(CRGAM),and Powerful-IoU loss.These components collaboratively enhance feature extraction,multi-scale perception,and localization accuracy while effectively reducing model complexity and computational cost.Experimental results show that ADCP-YOLO achieves a mAP of 90.6%,surpassing YOLOv8 by 3.0%with a 6.6%reduction in parameters.These findings demonstrate that ADCP-YOLO successfully balances accuracy and efficiency,offering a practical solution for intelligent safety monitoring in smart factory workshops.
基金supported by the National Natural Science Foundation of China(Grant Nos.42177138 and 41907239)the Central Guidance Funds for Local Science and Technology Development of China(Grant No.YDZJSX2025D031).
文摘Loess landslides are major hazards in the Chinese Loess Plateau(CLP).The loess in this region is frequently subjected to repeated wetting–drying(W-D)cycles due to climatic factors,which significantly increases the likelihood of landslides.Therefore,investigating the shear behavior and microstructural evolution of loess under climate-induced W-D cycles is crucial to understanding the mechanisms of loess landslides.In this study,Malan loess is analyzed using unsaturated triaxial tests,resistivity tests,scanning electron microscopy,and mercury intrusion porosimetry.The test results show that shear strength decreases with increased W-D cycles,and the degradation effect is more pronounced under lower confining pressure.The variations in conductive pathways indicate that electrical resistivity can effectively reflect the structural damage of loess during W-D cycles,which is associated with increased direct point contacts and spaced pores.Aggregation of clay particles and growth of cracks during the W-D cycles can further destabilize the loess microstructure.As the confining pressure increases,crushed particles rearrange and convert spaced pores into intergranular pores.The number and peak intensity of dominant spaced pores decrease,resulting in a more stable structure.This study clarifies the mechanisms of loess landslides under W-D cycles and provides theoretical support for landslide prevention and control in the CLP.
基金2024 University-level Research Project of Fuzhou Medical College,Fuzhou Medical College of Nanchang University(Project No.:fykj202406)。
文摘Objective: To understand the current status of peer caring behavior and empathy among undergraduate nursing students and to explore the relationship between the two. Method: Using the convenience sampling method, a questionnaire survey was conducted among 292 nursing students from a medical college in Jiangxi Province, using the Peer Caring Behavior Scale and the Jefferson Scale of Empathy. Results: The score for peer caring behavior among undergraduate nursing students was 85.00 (78.00-92.00), and the score for empathy was 101.00 (92.00-110.00). A positive correlation was found between the two (r = 0.362, p < 0.05). Conclusion: The level of peer caring behavior among undergraduate nursing students is above average, while their empathy level is moderate, with a positive correlation between the two. This suggests that nursing educators should strengthen the development of peer caring behavior, which may help enhance the empathy of undergraduate nursing students.
基金financially supported by the National Natural Science Foundation of China(Nos.52104319 and 52374323)。
文摘This study utilizes wet/dry cyclic corrosion testing combined with corrosion big data technology to investigate the mechanism by which chloride ions(Cl^(-))influence the corrosion behavior of 650 MPa high-strength low-alloy(HSLA)steel in industrially polluted environments.The corrosion process of 650 MPa HSLA steel occurred in two distinct stages:an initial corrosion stage and a stable corrosion stage.During the initial phase,the weight loss rate increased rapidly owing to the instability of the rust layer.Notably,this study demonstrated that 650 MPa HSLA steel exhibited superior corrosion resistance in Cl-containing environments.The formation of a corrosion-product film eventually reduced the weight-loss rate.However,the intrusion of Cl^(-)at increasing concentrations gradually destabilized theα/γ^(*)phases of the rust layer,leading to a looser structure and lower polarization resistance(R_(p)).The application of corrosion big data technology in this study facilitated the validation and analysis of the experimental results,offering new insights into the corrosion mechanisms of HSLA steel in chloride-rich environments.
基金supported by the National Natural Science Foundation of China(Grant No.42171135)the Science and Technology Program of CNOOC Research Institute(Grant No.2023OTKK03)the“CUG Scholar”Scientific Research Funds at China University of Geosciences(Project No.2022098).
文摘The volume change behavior of natural gas hydrate-bearing sediment is essential as it influences settlement,strength,and stiffness,which directly affect the stability of hydrate reservoirs during hydrate extraction or in response to environmental changes.The volume change is influenced not only by stress but also by the formation and dissociation of hydrates.This study adopted a customized apparatus for one-dimensional compression tests,allowing independent control of gas pressure and effective stress.Tests were conducted on samples with different hydrate saturations along various temperature-gas pressure-effective stress paths,yielding some conclusions related to compressibility and creep.An unusual phenomenon was observed under low-stress conditions:hydrate formation led to shrinkage rather than expansion.Three potential mechanisms behind this occurrence were discussed.As hydrate saturation increases,the yield stress rises while the compression and swelling indexes remain minimally affected.After hydrate dissociation,the compression curve of hydrate-bearing sediment drops to that of hydrate-free sediment.Once hydrate is formed,the compression curve of hydrate-free sediment gradually approaches that of hydrate-bearing sediment during the subsequent loading.Under low-stress conditions,the creep of both hydrate-free and hydrate-bearing sediments is very weak.However,when stress increases,significantly beyond the yield stress,the creep of both sediments increases significantly,with hydrate-bearing sediment exhibiting much greater creep than hydrate-free sediment.
文摘Objective: To analyze the impact of motivational nursing under the solution-focused approach on health behaviors in surgical care for bladder cancer patients. Methods: A sample of 72 bladder cancer patients who underwent surgical treatment from September 2024 to September 2025 was randomly divided into groups using a random number table. Group A received motivational nursing under the solution-focused approach, while Group B received conventional nursing. Health behavior scores and complication indicators were compared between the two groups. Results: Group A had higher scores on the Health-Promoting Lifestyle Profile II (HPLP-Ⅱ) than Group B, with p < 0.05. The postoperative complication rate in Group A was lower than that in Group B, with p < 0.05. Conclusion: For bladder cancer patients undergoing surgery, receiving motivational nursing under the solution-focused approach can improve health behaviors, alleviate negative emotions, and is highly feasible and effective.
