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
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
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
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
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
Drilling and blasting tunneling is a cyclic process in which tunnel rock undergoes repeated blast loading,affecting its dynamic characteristics,energy evolution,and damage progression.To explore the dynamic mechanical...Drilling and blasting tunneling is a cyclic process in which tunnel rock undergoes repeated blast loading,affecting its dynamic characteristics,energy evolution,and damage progression.To explore the dynamic mechanical properties and damage mechanisms of carbonaceous slate under cyclic impact loads of varying intensities,cyclic dynamic tests are conducted using a triaxial split Hopkinson pressure bar.This study analyzes the stress-strain relationship,energy damage evolution,and macro-to-micro failure characteristics.The results show that peak stress and strain are significantly influenced by impact intensity and the number of impacts.The initial dynamic stress is positively correlated with the impact intensity,but with more impact,the dynamic stress decreases while the peak strain increases.Energy evolution follows a pattern of"slow growthfluctuating growthrapid growth,"with the crack initiation stress and its proportion decreasing.CT and SEM analyses reveal that as the impact intensity increases,failure becomes more chaotic,the fracture volume increases,and the fracture mode shifts from interlayer and intergranular to through-layer and trans-granular fractures.These findings provide an experimental basis for soft rock tunnel stability analysis.展开更多
Objectives:24-h movement behaviors(24-HMB),encompassing physical activity,sedentary behavior,and sleep duration,are increasingly regarded as interrelated and important factors for mental health.However,evidence on the...Objectives:24-h movement behaviors(24-HMB),encompassing physical activity,sedentary behavior,and sleep duration,are increasingly regarded as interrelated and important factors for mental health.However,evidence on the comprehensive association of these behaviors with mental health in adults with diabetes in developing countries remains scarce.This study examined the association between 24-HMB guidelines and psychological health among adults with diabetes in developing countries.Methods:Data were retrieved from the World Health Organization’s study on Global Aging and Adult Health Survey dataset.Adults(N=1905)diagnosed with diabetes from five low-and middle-income countries were included.The exposure of interest was adherence to 24-HMB guidelines,depression,cognition,and quality of life(QoL).Multiple logistic and multiple linear regression analyses were used to examine the association between meeting 24-HMB guidelines and depression,cognition,and QoL,respectively.Results:This cross-sectional study revealed that 28.61%complied with all three 24-HMB guidelines.Diabetic patients who met more numbers of 24-HMB guidelines had lower depression risk(OR=0.74,95%CI:0.61 to 0.91,p=0.004),greater cognition(β=0.42,95%CI:0.25 to 0.60,p<0.001),and QoL(β=1.30,95%CI:1.04 to 1.55,p<0.001)with the non-compliant population.For specific combinations,meeting all three guidelines were significantly associated with lower odds of depression,improved cognitive function,and enhanced QoL(all p<0.001).Conclusion:These findings support that meeting 24-HMB guidelines in a single or combined movement behaviors was significantly related to reduced risk of depression,enhanced cognitive function,and improved QoL among individuals with diabetes.展开更多
Significant differences exist between deep and medium-shallow coalbed methane(CBM)reservoirs.The unclear understanding of flowback and production behavior severely constrains the development of deep CBM resources.To a...Significant differences exist between deep and medium-shallow coalbed methane(CBM)reservoirs.The unclear understanding of flowback and production behavior severely constrains the development of deep CBM resources.To address this challenge,guided by the gas-liquid two-phase flow theory in ultra-low permeability reservoirs,and integrating theoretical analysis,numerical simulation,and insights from production practices,this study classifies the flowback and production stages of deep CBM well considering the Daning-Jixian Block,Eastern Ordos Basin as a representative case.We summarize the flowback characteristics for each stage and establish a standard flowback production type curve,aiming to guide field operations.The results indicate that:(a)The production process of deep CBM horizontal wells can be divided into five distinct stages:initial single-phase water dewatering stage,initial gas appearance to peak water production stage,gas breakthrough to peak gas production stage,stable production and decline stage,and low-rate production stage.(b)Based on reservoir energy,two standard type curves for horizontal well flowback production are established:the‘Sufficient Reservoir Energy’type and the‘Insufficient Reservoir Energy’type.The former achieves a higher initial gas rate(up to 12×10^(4)m^(3)/d)but exhibits poorer stability,while the latter achieves a lower stable rate(up to 8×10^(4)m^(3)/d)but demonstrates stronger stability.Numerical simulation confirms these behavioral patterns and reveals the underlying mechanisms related to the effectively drained area where pressure is significantly depleted.The findings from this study have guided the flowback production operations in 53 deep CBM wells with positive results,demonstrating high potential for broad application.展开更多
BACKGROUND Despite societal guidelines recommending targeted screening for Barrett’s esophagus(BE)and esophageal adenocarcinoma(EAC)in individuals with gastroesophageal reflux symptoms(GERS),screening adherence is su...BACKGROUND Despite societal guidelines recommending targeted screening for Barrett’s esophagus(BE)and esophageal adenocarcinoma(EAC)in individuals with gastroesophageal reflux symptoms(GERS),screening adherence is suboptimal.Current screening approaches fail to identify individuals not seeking medical consultation for GERS or whose GERS are managed with‘over-the-counter’(OTC)acid suppressant therapies.AIM To assess patients’self-management and help-seeking behavior for GERS.METHODS This cross-sectional study collected data from the Dutch general population aged 18-75 years between January and April 2023 using a web-based survey.The survey included questions regarding self-management(e.g.,use of acid suppressant therapy with or without prescription)and help-seeking behavior(e.g.,consulting a primary care provider)for GERS.Simple random sampling was performed to select individuals within the target age group.In total,18156 randomly selected individuals were invited to participate.The study protocol was registered in ClinicalTrials.gov(identifier:NCT05689918).RESULTS Of the 18156 invited individuals,3214 participants(17.7%)completed the survey,of which 1572 participants(48.9%)reported GERS.Of these,904 participants(57.5%)had never consulted a primary care provider for these symptoms,of which 331 participants(36.6%)reported taking OTC acid suppressant therapy in the past six months and 100 participants(11.1%)fulfilled the screening criteria for BE and EAC according to the European Society of Gastrointestinal Endoscopy Guideline.CONCLUSION The population fulfilling the screening criteria for BE and EAC is incompletely identified,suggesting potential underutilization of medical consultation.Raising public awareness of GERS as a risk factor for EAC is needed.展开更多
To investigate the aging mechanisms and elucidate the correlations between unstable microstructure and performance in biodegradable Zn alloys,the accelerated aging experiment was conducted on a high-performance wrough...To investigate the aging mechanisms and elucidate the correlations between unstable microstructure and performance in biodegradable Zn alloys,the accelerated aging experiment was conducted on a high-performance wrought Zn−0.1Mg alloy by annealing at 200℃ for varying durations.The findings reveal that the tensile strength of the alloy rapidly and significantly declines with prolonged annealing time,decreasing from 383 MPa for the as-received alloy to 102 MPa for the alloy subjected to 1440 min of annealing.The primary factors contributing to this considerable reduction in strength are static recrystallization,grain coarsening,and dislocation annihilation.Initially,the ductility of the alloy shows fluctuations,ultimately experiencing a marked decrease after extended annealing.This decline is linked to the grain growth and heightened texture intensity,while the unusual increase in ductility observed between 30 and 120 min of annealing is likely due to the formation of twins.In addition,due to rapid grain growth and an increase in precipitates and twins,the corrosion resistance of the alloy in Hank’s solution has worsened,with the corrosion rate rising from 0.037 to 0.069 mm/a following 300 min of annealing.展开更多
BACKGROUND Due to the dry and cold climate,the obvious temperature difference between day and night,and the low oxygen content of the air in the plateau area,people are prone to upper respiratory tract diseases,and of...BACKGROUND Due to the dry and cold climate,the obvious temperature difference between day and night,and the low oxygen content of the air in the plateau area,people are prone to upper respiratory tract diseases,and often the condition is prolonged,and the patients are prone to anxiety and uneasiness,which may be related to the harshness of the plateau environment,somatic discomfort due to the lack of oxygen,anxiety about the disease,and other factors.AIM To investigate the effects of cognitive behavioral therapy(CBT)on anxiety,sleep disorders,and hypoxia tolerance in patients with high-altitude respiratory diseases.METHODS A total of 2337 patients with high-altitude-related respiratory diseases treated at our hospital between November 2023 and January 2024 were selected as the study subjects.The subjects’pre-high-altitude residential altitude was approximately 1700 meters.They were divided into two groups.Both groups were given symptomatic treatment,and the control group implemented conventional nursing intervention,while the research group simultaneously conducted CBT intervention;assessed the degree of health knowledge of the two groups,and applied the Hamilton Anxiety Scale and the Pittsburgh Sleep Quality Index to assess the anxiety and sleep quality of the patients before and after the intervention,respectively.It also observed the length and efficiency of sleep,and detected the level of serum hypoxia inducible factor-1α,erythropoietin(EPO)and clinical intervention before and after intervention.EPO levels,and investigated satisfaction with the clinical intervention.RESULTS The rate of excellent health knowledge in the intervention group was 93.64%,which was higher than that in the control group(74.23%;P<0.05).Before the intervention,there was no significant difference in Hamilton Anxiety Scale and Pittsburgh Sleep Quality Index scores between the two groups(P>0.05),and after the intervention,the scores of the study group were significantly lower than those of the control group(P<0.05).There was no significant difference in sleep duration and sleep efficiency between the groups before the intervention(P>0.05),and after the intervention,the scores of the study group were significantly larger than those of the control group(P<0.05).There was no significant difference in serum hypoxia inducible factor-1αand EPO between the two groups before intervention(P>0.05),and both research groups were significantly lower than the control group after intervention(P<0.05).According to the questionnaire survey,the intervention satisfaction of the study group was 95.53%,which was higher than that of the control group(80.14%;P<0.05).CONCLUSION The CBT intervention in the treatment of patients with high-altitude-related respiratory diseases helps improve patients'health knowledge,relieve anxiety,improve sleep quality and hypoxia tolerance,and improve nursing satisfaction.展开更多
BACKGROUND Approximately 30%of patients with head and neck cancer experience adverse effects caused by anxiety and depression.Considering the high prevalence,implementing customized interventions to ease adverse emoti...BACKGROUND Approximately 30%of patients with head and neck cancer experience adverse effects caused by anxiety and depression.Considering the high prevalence,implementing customized interventions to ease adverse emotional states is imperative.AIM To evaluate the efficacy of cognitive behavioral therapy(CBT)-based psychological interventions in improving the psychological well-being and quality of life(QoL)of patients with laryngeal carcinoma.METHODS This study enrolled 120 patients admitted from February 2022 to February 2024.The control group,comprising 50 participants,received standard supportive psychological care,while the research group,consisting 70 participants,underwent CBT-based interventions.Several clinical outcomes were systematically assessed that included postoperative recovery metrics(duration of tracheostomy and nasogastric tube dependence and length of hospitalization),psychological status(Self-Rating Anxiety Scale and Self-Rating Depression Scale),nutritional markers(serum albumin and hemoglobin levels),sleep quality(Self-Rating Scale of Sleep and Athens Insomnia Scale),and QoL(Functional Assessment of Cancer Therapy-Head and Neck).RESULTS The results demonstrated that the research group experienced superior outcomes,with significantly reduced durations of tracheostomy and nasogastric tube dependence,as well as shorter hospital stays,compared with the control group.Additionally,the research group exhibited markedly lower post-intervention Self-Rating Anxiety Scale,Self-Rating Depression Scale,Self-Rating Scale of Sleep,and Athens Insomnia Scale scores,along with minimal but higher change in serum albumin and hemoglobin levels compared with the control group.All five domains of Functional Assessment of Cancer Therapy-Head and Neck showed notable improvements in the research group,exceeding those observed in the control group.CONCLUSION CBT-based psychological support positively affects the mental well-being and QoL of patients with laryngeal carcinoma,highlighting its potential for broader clinical application.展开更多
Accurate purchase prediction in e-commerce critically depends on the quality of behavioral features.This paper proposes a layered and interpretable feature engineering framework that organizes user signals into three ...Accurate purchase prediction in e-commerce critically depends on the quality of behavioral features.This paper proposes a layered and interpretable feature engineering framework that organizes user signals into three layers:Basic,Conversion&Stability(efficiency and volatility across actions),and Advanced Interactions&Activity(crossbehavior synergies and intensity).Using real Taobao(Alibaba’s primary e-commerce platform)logs(57,976 records for 10,203 users;25 November–03 December 2017),we conducted a hierarchical,layer-wise evaluation that holds data splits and hyperparameters fixed while varying only the feature set to quantify each layer’s marginal contribution.Across logistic regression(LR),decision tree,random forest,XGBoost,and CatBoost models with stratified 5-fold cross-validation,the performance improvedmonotonically fromBasic to Conversion&Stability to Advanced features.With LR,F1 increased from 0.613(Basic)to 0.962(Advanced);boosted models achieved high discrimination(0.995 AUC Score)and an F1 score up to 0.983.Calibration and precision–recall analyses indicated strong ranking quality and acknowledged potential dataset and period biases given the short(9-day)window.By making feature contributions measurable and reproducible,the framework complements model-centric advances and offers a transparent blueprint for production-grade behavioralmodeling.The code and processed artifacts are publicly available,and future work will extend the validation to longer,seasonal datasets and hybrid approaches that combine automated feature learning with domain-driven design.展开更多
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.
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.
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.
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.
基金support from the Joint Funds of the National Natural Science Foundation of China(Grant No.U23A2060)the National Natural Science Foundation of China(Grant Nos.42177143 and 52474150).
文摘Drilling and blasting tunneling is a cyclic process in which tunnel rock undergoes repeated blast loading,affecting its dynamic characteristics,energy evolution,and damage progression.To explore the dynamic mechanical properties and damage mechanisms of carbonaceous slate under cyclic impact loads of varying intensities,cyclic dynamic tests are conducted using a triaxial split Hopkinson pressure bar.This study analyzes the stress-strain relationship,energy damage evolution,and macro-to-micro failure characteristics.The results show that peak stress and strain are significantly influenced by impact intensity and the number of impacts.The initial dynamic stress is positively correlated with the impact intensity,but with more impact,the dynamic stress decreases while the peak strain increases.Energy evolution follows a pattern of"slow growthfluctuating growthrapid growth,"with the crack initiation stress and its proportion decreasing.CT and SEM analyses reveal that as the impact intensity increases,failure becomes more chaotic,the fracture volume increases,and the fracture mode shifts from interlayer and intergranular to through-layer and trans-granular fractures.These findings provide an experimental basis for soft rock tunnel stability analysis.
文摘Objectives:24-h movement behaviors(24-HMB),encompassing physical activity,sedentary behavior,and sleep duration,are increasingly regarded as interrelated and important factors for mental health.However,evidence on the comprehensive association of these behaviors with mental health in adults with diabetes in developing countries remains scarce.This study examined the association between 24-HMB guidelines and psychological health among adults with diabetes in developing countries.Methods:Data were retrieved from the World Health Organization’s study on Global Aging and Adult Health Survey dataset.Adults(N=1905)diagnosed with diabetes from five low-and middle-income countries were included.The exposure of interest was adherence to 24-HMB guidelines,depression,cognition,and quality of life(QoL).Multiple logistic and multiple linear regression analyses were used to examine the association between meeting 24-HMB guidelines and depression,cognition,and QoL,respectively.Results:This cross-sectional study revealed that 28.61%complied with all three 24-HMB guidelines.Diabetic patients who met more numbers of 24-HMB guidelines had lower depression risk(OR=0.74,95%CI:0.61 to 0.91,p=0.004),greater cognition(β=0.42,95%CI:0.25 to 0.60,p<0.001),and QoL(β=1.30,95%CI:1.04 to 1.55,p<0.001)with the non-compliant population.For specific combinations,meeting all three guidelines were significantly associated with lower odds of depression,improved cognitive function,and enhanced QoL(all p<0.001).Conclusion:These findings support that meeting 24-HMB guidelines in a single or combined movement behaviors was significantly related to reduced risk of depression,enhanced cognitive function,and improved QoL among individuals with diabetes.
基金supported by the National Science and Technology Major Project of China(No.2025ZD1405702)the Scientific Research and Technology Development Project of PetroChina Coalbed Methane Co.,Ltd.(Project No.25MQCTSG010)Applied Science and Technology Project of PetroChina Company Limited(2023ZZ18YJ04).
文摘Significant differences exist between deep and medium-shallow coalbed methane(CBM)reservoirs.The unclear understanding of flowback and production behavior severely constrains the development of deep CBM resources.To address this challenge,guided by the gas-liquid two-phase flow theory in ultra-low permeability reservoirs,and integrating theoretical analysis,numerical simulation,and insights from production practices,this study classifies the flowback and production stages of deep CBM well considering the Daning-Jixian Block,Eastern Ordos Basin as a representative case.We summarize the flowback characteristics for each stage and establish a standard flowback production type curve,aiming to guide field operations.The results indicate that:(a)The production process of deep CBM horizontal wells can be divided into five distinct stages:initial single-phase water dewatering stage,initial gas appearance to peak water production stage,gas breakthrough to peak gas production stage,stable production and decline stage,and low-rate production stage.(b)Based on reservoir energy,two standard type curves for horizontal well flowback production are established:the‘Sufficient Reservoir Energy’type and the‘Insufficient Reservoir Energy’type.The former achieves a higher initial gas rate(up to 12×10^(4)m^(3)/d)but exhibits poorer stability,while the latter achieves a lower stable rate(up to 8×10^(4)m^(3)/d)but demonstrates stronger stability.Numerical simulation confirms these behavioral patterns and reveals the underlying mechanisms related to the effectively drained area where pressure is significantly depleted.The findings from this study have guided the flowback production operations in 53 deep CBM wells with positive results,demonstrating high potential for broad application.
文摘BACKGROUND Despite societal guidelines recommending targeted screening for Barrett’s esophagus(BE)and esophageal adenocarcinoma(EAC)in individuals with gastroesophageal reflux symptoms(GERS),screening adherence is suboptimal.Current screening approaches fail to identify individuals not seeking medical consultation for GERS or whose GERS are managed with‘over-the-counter’(OTC)acid suppressant therapies.AIM To assess patients’self-management and help-seeking behavior for GERS.METHODS This cross-sectional study collected data from the Dutch general population aged 18-75 years between January and April 2023 using a web-based survey.The survey included questions regarding self-management(e.g.,use of acid suppressant therapy with or without prescription)and help-seeking behavior(e.g.,consulting a primary care provider)for GERS.Simple random sampling was performed to select individuals within the target age group.In total,18156 randomly selected individuals were invited to participate.The study protocol was registered in ClinicalTrials.gov(identifier:NCT05689918).RESULTS Of the 18156 invited individuals,3214 participants(17.7%)completed the survey,of which 1572 participants(48.9%)reported GERS.Of these,904 participants(57.5%)had never consulted a primary care provider for these symptoms,of which 331 participants(36.6%)reported taking OTC acid suppressant therapy in the past six months and 100 participants(11.1%)fulfilled the screening criteria for BE and EAC according to the European Society of Gastrointestinal Endoscopy Guideline.CONCLUSION The population fulfilling the screening criteria for BE and EAC is incompletely identified,suggesting potential underutilization of medical consultation.Raising public awareness of GERS as a risk factor for EAC is needed.
基金supported by the National Natural Science Foundation of China(No.52271101)Suzhou Science and Technology Project,China(Nos.SYG202312,SJC2023005,SZS2023023)+1 种基金Nanjing Major Science and Technology Project,China(No.202309015)the Opening Project of Jiangsu Key Laboratory of Advanced Structural Materials and Application Technology,China(No.ASMA202305)。
文摘To investigate the aging mechanisms and elucidate the correlations between unstable microstructure and performance in biodegradable Zn alloys,the accelerated aging experiment was conducted on a high-performance wrought Zn−0.1Mg alloy by annealing at 200℃ for varying durations.The findings reveal that the tensile strength of the alloy rapidly and significantly declines with prolonged annealing time,decreasing from 383 MPa for the as-received alloy to 102 MPa for the alloy subjected to 1440 min of annealing.The primary factors contributing to this considerable reduction in strength are static recrystallization,grain coarsening,and dislocation annihilation.Initially,the ductility of the alloy shows fluctuations,ultimately experiencing a marked decrease after extended annealing.This decline is linked to the grain growth and heightened texture intensity,while the unusual increase in ductility observed between 30 and 120 min of annealing is likely due to the formation of twins.In addition,due to rapid grain growth and an increase in precipitates and twins,the corrosion resistance of the alloy in Hank’s solution has worsened,with the corrosion rate rising from 0.037 to 0.069 mm/a following 300 min of annealing.
基金Supported by Army Logistics Department Health Bureau Project,No.QJGYXYJZX-012.
文摘BACKGROUND Due to the dry and cold climate,the obvious temperature difference between day and night,and the low oxygen content of the air in the plateau area,people are prone to upper respiratory tract diseases,and often the condition is prolonged,and the patients are prone to anxiety and uneasiness,which may be related to the harshness of the plateau environment,somatic discomfort due to the lack of oxygen,anxiety about the disease,and other factors.AIM To investigate the effects of cognitive behavioral therapy(CBT)on anxiety,sleep disorders,and hypoxia tolerance in patients with high-altitude respiratory diseases.METHODS A total of 2337 patients with high-altitude-related respiratory diseases treated at our hospital between November 2023 and January 2024 were selected as the study subjects.The subjects’pre-high-altitude residential altitude was approximately 1700 meters.They were divided into two groups.Both groups were given symptomatic treatment,and the control group implemented conventional nursing intervention,while the research group simultaneously conducted CBT intervention;assessed the degree of health knowledge of the two groups,and applied the Hamilton Anxiety Scale and the Pittsburgh Sleep Quality Index to assess the anxiety and sleep quality of the patients before and after the intervention,respectively.It also observed the length and efficiency of sleep,and detected the level of serum hypoxia inducible factor-1α,erythropoietin(EPO)and clinical intervention before and after intervention.EPO levels,and investigated satisfaction with the clinical intervention.RESULTS The rate of excellent health knowledge in the intervention group was 93.64%,which was higher than that in the control group(74.23%;P<0.05).Before the intervention,there was no significant difference in Hamilton Anxiety Scale and Pittsburgh Sleep Quality Index scores between the two groups(P>0.05),and after the intervention,the scores of the study group were significantly lower than those of the control group(P<0.05).There was no significant difference in sleep duration and sleep efficiency between the groups before the intervention(P>0.05),and after the intervention,the scores of the study group were significantly larger than those of the control group(P<0.05).There was no significant difference in serum hypoxia inducible factor-1αand EPO between the two groups before intervention(P>0.05),and both research groups were significantly lower than the control group after intervention(P<0.05).According to the questionnaire survey,the intervention satisfaction of the study group was 95.53%,which was higher than that of the control group(80.14%;P<0.05).CONCLUSION The CBT intervention in the treatment of patients with high-altitude-related respiratory diseases helps improve patients'health knowledge,relieve anxiety,improve sleep quality and hypoxia tolerance,and improve nursing satisfaction.
文摘BACKGROUND Approximately 30%of patients with head and neck cancer experience adverse effects caused by anxiety and depression.Considering the high prevalence,implementing customized interventions to ease adverse emotional states is imperative.AIM To evaluate the efficacy of cognitive behavioral therapy(CBT)-based psychological interventions in improving the psychological well-being and quality of life(QoL)of patients with laryngeal carcinoma.METHODS This study enrolled 120 patients admitted from February 2022 to February 2024.The control group,comprising 50 participants,received standard supportive psychological care,while the research group,consisting 70 participants,underwent CBT-based interventions.Several clinical outcomes were systematically assessed that included postoperative recovery metrics(duration of tracheostomy and nasogastric tube dependence and length of hospitalization),psychological status(Self-Rating Anxiety Scale and Self-Rating Depression Scale),nutritional markers(serum albumin and hemoglobin levels),sleep quality(Self-Rating Scale of Sleep and Athens Insomnia Scale),and QoL(Functional Assessment of Cancer Therapy-Head and Neck).RESULTS The results demonstrated that the research group experienced superior outcomes,with significantly reduced durations of tracheostomy and nasogastric tube dependence,as well as shorter hospital stays,compared with the control group.Additionally,the research group exhibited markedly lower post-intervention Self-Rating Anxiety Scale,Self-Rating Depression Scale,Self-Rating Scale of Sleep,and Athens Insomnia Scale scores,along with minimal but higher change in serum albumin and hemoglobin levels compared with the control group.All five domains of Functional Assessment of Cancer Therapy-Head and Neck showed notable improvements in the research group,exceeding those observed in the control group.CONCLUSION CBT-based psychological support positively affects the mental well-being and QoL of patients with laryngeal carcinoma,highlighting its potential for broader clinical application.
基金supported by the research fund of Hanyang University(HY-202500000001616).
文摘Accurate purchase prediction in e-commerce critically depends on the quality of behavioral features.This paper proposes a layered and interpretable feature engineering framework that organizes user signals into three layers:Basic,Conversion&Stability(efficiency and volatility across actions),and Advanced Interactions&Activity(crossbehavior synergies and intensity).Using real Taobao(Alibaba’s primary e-commerce platform)logs(57,976 records for 10,203 users;25 November–03 December 2017),we conducted a hierarchical,layer-wise evaluation that holds data splits and hyperparameters fixed while varying only the feature set to quantify each layer’s marginal contribution.Across logistic regression(LR),decision tree,random forest,XGBoost,and CatBoost models with stratified 5-fold cross-validation,the performance improvedmonotonically fromBasic to Conversion&Stability to Advanced features.With LR,F1 increased from 0.613(Basic)to 0.962(Advanced);boosted models achieved high discrimination(0.995 AUC Score)and an F1 score up to 0.983.Calibration and precision–recall analyses indicated strong ranking quality and acknowledged potential dataset and period biases given the short(9-day)window.By making feature contributions measurable and reproducible,the framework complements model-centric advances and offers a transparent blueprint for production-grade behavioralmodeling.The code and processed artifacts are publicly available,and future work will extend the validation to longer,seasonal datasets and hybrid approaches that combine automated feature learning with domain-driven design.
