Tuojiang River Basin is a first-class tributary of the upper reaches of the Yangtze River—which is the longest river in China.As phytoplankton are sensitive indicators of trophic changes inwater bodies,characterizing...Tuojiang River Basin is a first-class tributary of the upper reaches of the Yangtze River—which is the longest river in China.As phytoplankton are sensitive indicators of trophic changes inwater bodies,characterizing phytoplankton communities and their growth influencing factors in polluted urban rivers can provide new ideas for pollution control.Here,we used direct microscopic count and environmental DNA(eDNA)metabarcoding methods to investigate phytoplankton community structure in Tuojiang River Basin(Chengdu,Sichuan Province,China).The association between phytoplankton community structure and water environmental factors was evaluated by Mantel analysis.Additional environmental monitoring data were used to pinpoint major factors that influenced phytoplankton growth based on structural equation modeling.At the phylum level,the dominant phytoplankton taxa identified by the conventional microscopic method mainly belonged to Bacillariophyta,Chlorophyta,and Cyanophyta,in contrast with Chlorophyta,Dinophyceae,and Bacillariophyta identified by eDNA metabarcoding.Inα-diversity analysis,eDNA metabarcoding detected greater species diversity and achieved higher precision than the microscopic method.Phytoplankton growth was largely limited by phosphorus based on the nitrogen-to-phosphorus ratios>16:1 in all water samples.Redundancy analysis and structural equation modeling also confirmed that the nitrogen-to-phosphorus ratio was the principal factor influencing phytoplankton growth.The results could be useful for implementing comprehensive management of the river basin environment.It is recommended to control the discharge of point-and surface-source pollutants and the concentration of dissolved oxygen in areas with excessive nutrients(e.g.,Jianyang-Ziyang).Algae monitoring techniques and removal strategies should be improved in 201 Hospital,Hongrihe Bridge and Colmar Town areas.展开更多
The acetylpolyamine oxidase(APAO),spermine oxidase(SMO),and spermidine/spermine N1-acetyltransferase(SSAT)are pivotal enzymes in polyamine metabolism,exerting direct influence on polyamine homeostasis regulation.Dysfu...The acetylpolyamine oxidase(APAO),spermine oxidase(SMO),and spermidine/spermine N1-acetyltransferase(SSAT)are pivotal enzymes in polyamine metabolism,exerting direct influence on polyamine homeostasis regulation.Dysfunctions in these enzymes are intricately linked to inflammatory diseases and cancers.Establishing their three-dimensional structures is essential for exploring enzymatic catalytic mechanisms and designing inhibitors at the atomic level.This article primarily assesses the precision of AlphaFold2 and molecular dynamics simulations in determining the three-dimensional structures of these enzymes,utilizing protein conformation rationality assessment,residue correlation matrix,and other techniques.This provides robust models for subsequent polyamine catabolic metabolism calculations and offers valuable insights for modeling proteins that have yet to acquire crystal structures.展开更多
Background:As is widely known,an increasing number of forest areas were managed to preserve and enhance the health of forest ecosystems.However,previous research on forest management has often overlooked the importanc...Background:As is widely known,an increasing number of forest areas were managed to preserve and enhance the health of forest ecosystems.However,previous research on forest management has often overlooked the importance of structure-based.Aims:Our objectives were to define the direction of structure-based forest management.Subsequently,we investigated the relationships between forest structure and the regeneration,growth,and mortality of trees under different thinning treatments.Ultimately,the drivers of forest structural change were explored.Methods:On the basis of 92 sites selected from northeastern China,with different recovery time (from 1 to 15years) and different thinning intensities (0–59.9%) since the last thinning.Principal component analysis (PCA)identified relationships among factors determining forest spatial structure.The structural equation model (SEM)was used to analyze the driving factors behind the changes in forest spatial structure after thinning.Results:Light thinning (0–20%trees removed) promoted forest regeneration,and heavy thinning (over 35% of trees removed) facilitated forest growth.However,only moderate thinning (20%–35%trees removed) created a reasonable spatial structure.While dead trees were clustered,and they were hardly affected by thinning intensity.Additionally,thinning intensity,recovery time,and altitude indirectly improve the spatial structure of the forest by influencing diameter at breast height (DBH) and canopy area.Conclusion:Creating larger DBH and canopy area through thinning will promote the formation of complex forest structures,which cultivates healthy and stable forests.展开更多
Intensive management is known to markedly alter soil carbon(C)storage and turnover in Moso bamboo forests compared with extensive management.However,the effects of intensive management on soil respiration(RS)component...Intensive management is known to markedly alter soil carbon(C)storage and turnover in Moso bamboo forests compared with extensive management.However,the effects of intensive management on soil respiration(RS)components remain unclear.This study aimed to evaluate the changes in different RScomponents(root,mycorrhizal,and free-living microorganism respiration)in Moso bamboo forests under extensive and intensive management practices.A1-year in-situ microcosm experiment was conducted to quantify the RScomponents in Moso bamboo forests under the two management practices using mesh screens of varying sizes.The results showed that the total RSand its components exhibited similar seasonal variability between the two management practices.Compared with extensive management,intensive management significantly increased cumulative respiration from mycorrhizal fungi by 36.73%,while decreased cumulative respiration from free-living soil microorganisms by 8.97%.Moreover,the abundance of arbuscular mycorrhizal fungi(AMF)increased by 43.38%,but bacterial and fungal abundances decreased by 21.65%and 33.30%,respectively,under intensive management.Both management practices significantly changed the bacterial community composition,which could be mainly explained by soil pH and available potassium.Mycorrhizal fungi and intensive management affected the interrelationships between bacterial members.Structural equation modeling indicated that intensive management changed the cumulative RSby elevating AMF abundance and lowering bacterial abundance.We concluded that intensive management reduced the microbial respiration-derived C loss,but increased mycorrhizal respiration-derived C loss.展开更多
Elemental analysis,nuclear magnetic resonance carbon spectroscopy(^(13)C-NMR),X-ray photoelectron spectroscopy(XPS)and Fourier transform infrared spectroscopy(FTIR)experiments were carried out to determine the existen...Elemental analysis,nuclear magnetic resonance carbon spectroscopy(^(13)C-NMR),X-ray photoelectron spectroscopy(XPS)and Fourier transform infrared spectroscopy(FTIR)experiments were carried out to determine the existence of aromatic structure,heteroatom structure and fat structure in coal.MS(materials studio)software was used to optimize and construct a 3D molecular structure model of coal.A method for establishing a coal molecular structure model was formed,which was“determination of key structures in coal,construction of planar molecular structure model,and optimization of three-dimensional molecular structure model”.The structural differences were compared and analyzed.The results show that with the increase of coal rank,the dehydrogenation of cycloalkanes in coal is continuously enhanced,and the content of heteroatoms in the aromatic ring decreases.The heteroatoms and branch chains in the coal are reduced,and the structure is more orderly and tight.The stability of the structure is determined by theπ-πinteraction between the aromatic rings in the nonbonding energy EN.Key Stretching Energy The size of EB determines how tight the structure is.The research results provide a method and reference for the study of the molecular structure of medium and high coal ranks.展开更多
To design the control system for some homing missile so that the autopilot can transfer guidance command correctly and be robust to disturbances, such as the measurement noises and parameter variation caused by areody...To design the control system for some homing missile so that the autopilot can transfer guidance command correctly and be robust to disturbances, such as the measurement noises and parameter variation caused by areodynamic floating. The model reference adaptive control was combined with the variable structure control to design a model reference variable structure (MRVS) control system whose control structure is simple and can be realized easily. The simulation results indicate that MRVS can complete the task of transferring guidance command and suppress the distrubances effectively.展开更多
The large-scale exploitation of vanadium(Ⅴ) bearing minerals has led to a massive accumulation of Ⅴ tailings, of which Ⅴ pollution poses severe ecological risks. Although the mechanisms of Ⅴ stress to the microbia...The large-scale exploitation of vanadium(Ⅴ) bearing minerals has led to a massive accumulation of Ⅴ tailings, of which Ⅴ pollution poses severe ecological risks. Although the mechanisms of Ⅴ stress to the microbial community have been reported, the influential pathways in a multi-medium-containing system, for example, the soil-tailings-groundwater system,are unknown. The dynamic redox conditions and substance exchange within the system exhibited complex Ⅴ stress on the local microbial communities. In this study, the influence pathways of Ⅴ stress to the microbial community in the soil-tailings-groundwater system were first investigated. High Ⅴ contents were observed in groundwater(139.2 ± 0.15 μg/L) and soil(98.0–323.8 ± 0.02 mg/kg), respectively. Distinct microbial composition was observed for soil and groundwater, where soil showed the highest level of diversity and richness. Firmicutes, Proteobacteria, Actinobacteria, and Acidobacteria were dominant in soil and groundwater with a sum relative abundance of around 80 %. Based on redundancy analysis and structural equation models, Ⅴ was one of the vital driving factors affecting microbial communities. Groundwater microbial communities were influenced by Ⅴ via Cr, dissolved oxygen, and total nitrogen, while Fe, Mn, and total phosphorus were the key mediators for Ⅴ to affect soil microbial communities. Ⅴ affected the microbial community via metabolic pathways related to carbonaceous matter, which was involved in the establishment of survival strategies for metal stress. This study provides novel insights into the influence pathways of Ⅴ on the microorganisms in tailings reservoir for pollution bioremediation.展开更多
Objectives:Teachers are facing unprecedented new challenges leading them to face an increasing number of tasks that are not part of their job,as well as having to cope with the additional skills acquisition that comes...Objectives:Teachers are facing unprecedented new challenges leading them to face an increasing number of tasks that are not part of their job,as well as having to cope with the additional skills acquisition that comes with non-traditional forms of teaching and learning,and increased work pressure leading to an increase in the rate of teachers leaving the profession.Therefore,this study aims to explore the mechanism of the career calling on job burnout through career adaptability and work engagement.Methods:This study conducted a cross-sectional survey of 465 primary and secondary school teachers(PSST)in China's Mainland from the perspective of work adjustment and used structural equation modeling(SEM)to examine the mediating roles of career adaptability and work engagement in the relationship between teachers’career calling and job burnout.Results:The results show that PSSTs are above average in career calling,career adaptability,and work engagement,while job burnout is below average.A significant positive or negative correlation exists between career calling,career adaptability,work engagement,and job burnout.The result of path analysis indicates that career adaptability and work engagement exert an indirect influence on the job burnout of PSST through three paths:namely,the independent intermediary role of career adaptability(EV=−0.144),the independent intermediary role of work engagement(EV=0.172)and the chain intermediary role of the two(EV=0.176).Conclusion:This study emphasizes the importance of career adaptability and work engagement in teacher development in regulating career calling and job burnout.Therefore,on the one hand,we think that if managers want to reduce teachers’job burnout,they need to pay more attention to teachers’career adaptability and work engagement,rather than relying solely on teachers’career calling.On the other hand,it is to remind teachers not to rely on their adjustment to adapt to the work,but also to need outside help as much as possible.展开更多
High-Entropy Alloys(HEAs)exhibit significant potential across multiple domains due to their unique properties.However,conventional research methodologies face limitations in composition design,property prediction,and ...High-Entropy Alloys(HEAs)exhibit significant potential across multiple domains due to their unique properties.However,conventional research methodologies face limitations in composition design,property prediction,and process optimization,characterized by low efficiency and high costs.The integration of Artificial Intelligence(AI)technologies has provided innovative solutions for HEAs research.This review presented a detailed overview of recent advancements in AI applications for structural modeling and mechanical property prediction of HEAs.Furthermore,it discussed the advantages of big data analytics in facilitating alloy composition design and screening,quality control,and defect prediction,as well as the construction and sharing of specialized material databases.The paper also addressed the existing challenges in current AI-driven HEAs research,including issues related to data quality,model interpretability,and cross-domain knowledge integration.Additionally,it proposed prospects for the synergistic development of AI-enhanced computational materials science and experimental validation systems.展开更多
The study area is rich in shale gas resources and has reached the stage of comprehensive development. Shale gas extraction poses risks such as induced seismicity and well closure, compounded by the limited availabilit...The study area is rich in shale gas resources and has reached the stage of comprehensive development. Shale gas extraction poses risks such as induced seismicity and well closure, compounded by the limited availability of fi xed seismic monitoring stations nearby. To address these challenges, a dense observation array was developed within the study area to monitor and analyze microseismic activity during hydraulic fracturing. Microseismic events generated by hydraulic fracturing typically exhibit low amplitude and signal-to-noise ratio, rendering traditional manual analysis methods impractical. To overcome these limitations, an innovative artifi cial intelligence method combining picking-association-location (PAL) and match-expand- shift-stack (MESS) techniques (PALM) has been utilized for automated seismic detection. Numerous factors influence the accuracy of microseismic detection and localization. To evaluate these factors, the effects of various velocity structure models, instrument types, and station distributions on seismic location were analyzed and compared. The results indicate that the PALM method significantly mitigates the influence of velocity structure models on seismic location accuracy. Additionally, the use of broadband seismic instruments and a uniform station distribution enhances the precision of seismic location results. Furthermore, by integrating data from diff erent types of observation instruments, a comprehensive seismic catalog for the study area was established. These fi ndings not only enhance seismic location accuracy but also provide valuable guidance for optimizing regional seismic monitoring network design and improving seismic risk assessment.展开更多
Background:Understanding the factors that influence adolescent psychological resilience is critical for promoting mental health.This study explores the impact and mechanism of labor values on adolescent psychological ...Background:Understanding the factors that influence adolescent psychological resilience is critical for promoting mental health.This study explores the impact and mechanism of labor values on adolescent psychological resilience from the perspective of emotion regulation theory.Methods:This study conducted an in-depth analysis using the Labor Value Scale on 2691 elementary school upper-grade students,middle school students,and high school students.Results:The results show that:(1)labor values can positively predict adolescents’mental resilience;(2)cognitive reappraisal and expression inhibition play a partial mediating role in the relationship between labor values and adolescents’psychological resilience.Among them,labor values can positively predict adolescents’mental resilience through positive cognitive reappraisal,and labor values can also predict adolescents’mental resilience through expression inhibition.Conclusion:Based on the theory of emotion regulation,this study explores the direct effect of labor values on mental resilience and the mediating effect of different strategies of emotion regulation.The results of this study provide a theoretical basis for improving the mental resilience of adolescents.展开更多
BACKGROUND Depression,anxiety,and insomnia were found out that were significant relevance to the mental health impact of the coronavirus disease 2019(COVID-19)lock-down.AIM To examine the interrelationships among perc...BACKGROUND Depression,anxiety,and insomnia were found out that were significant relevance to the mental health impact of the coronavirus disease 2019(COVID-19)lock-down.AIM To examine the interrelationships among perceived severity,anxiety,depression,insomnia,and sense of security in Chinese community residents during the COVID-19 lockdown period.METHODS Participants were selected using simple random sampling from four large gated communities in Chengdu,China.All participants were invited to complete a survey that included the Perceived Severity Questionnaire,Security Question-naire,Patient Health Questionnaire-9,Generalized Anxiety Disorder 7-item,and Insomnia Severity Index-7.In total,568 valid questionnaires were gathered.Co-rrelation analysis and structural equation models were used to explore the rela-RESULTS The observed prevalence rates of anxiety,depression,and insomnia among residents during lockdown were 27.5%,17.6%,and 16.0%,respectively.Correlation analysis showed that both perceived severity and sense of security were positively correlated with anxiety,depression,and insomnia[Pearson’s r was perceived severity and anxiety r=0.44(P<0.01);with depression r=0.48(P<0.01);with insomnia r=0.43(P<0.01);security with anxiety r=-0.65(P<0.01);with depression r=-0.65(P<0.01);with insomnia r=-0.53(P<0.01)].Structural equation modeling and bootstrap tests revealed that sense of security acted as a significant mediator in the relationship between perceived severity and emotional and sleep disorders(anxiety,depression,and insomnia).CONCLUSION This study demonstrates that sense of security is a significant predictor of emotional and sleep disorders(namely,depression,anxiety,and insomnia)among residents during the COVID-19 lockdown,with sense of security acting as a mediating factor.These findings suggest that mental health interventions for Chinese community residents during lockdowns may benefit from developing community-based educational programs to reduce perceived severity and ensuring the stable supply of essential resources and promoting social support networks to enhance the sense of security.展开更多
Controversy is ongoing regarding the relationship between ore formation and the structural evolution of the Hadamengou gold deposit.To address this issue,we conducted a comprehensive investigation of mineralization-re...Controversy is ongoing regarding the relationship between ore formation and the structural evolution of the Hadamengou gold deposit.To address this issue,we conducted a comprehensive investigation of mineralization-related structures,geochronology and Fe isotopes.From the perspective of spatial evolution,hydrothermal fluids originating from the Shadegai and Xishadegai plutons have extracted accumulated ore-forming elements from the Wulashan Group(Ar2WL)and then evolved,initiating at Exploration Line 11 and migrating eastwards and westwards along the EW-trending thrust fault system to form orebodies.From the temporal evolution standpoint,the Wulashan Group(Ar_(2)WL)experienced diagenesis(2591.00 Ma to 2204.00 Ma)and metamorphism(2074.00 Ma to 1625.00 Ma)from late Neoarchean to early Paleoproterozoic,when ore-forming materials were initially accumulated;in the early Paleozoic(440.71 Ma to 425.00 Ma),the collision led to the formation of early-stage EW-trending imbricated thrust faults,which established a fundamental structural framework for the orefield and further accumulated ore-forming materials;from the late Paleozoic to the Mesozoic,multiple subsequent episodes of regional tectonic-magmatic-hydrothermal events have superimposed,modified and reactivated the thrust fault system.Notably,the Triassic period,particularly between 245.00 Ma and 217.90 Ma,is considered to be a primary ore-forming stage.In summary,the intricate relationship between ore-formation and structural evolution has been fundamentally elucidated.展开更多
As the impact of climate change intensifies,climate migration(climate change-induced migration)has become a pressing global issue that requires effective adaptation strategies to lessen its effects.Therefore,this stud...As the impact of climate change intensifies,climate migration(climate change-induced migration)has become a pressing global issue that requires effective adaptation strategies to lessen its effects.Therefore,this study delved into the complex relationship between climate change adaptation strategies and climate migration with food insecurity serving as a mediating factor.We collected sample data through face-to-face interviews in Khorramabad City,Iran from February to May in 2023.Using the Structural Equation Modeling(SEM),we explored how food insecurity influences the relationship between climate change adaptation strategies and climate migration.The findings showed that while climate change adaptation strategies can boost community resilience,their success is closely tied to levels of food insecurity.About 78.72%of the surveyed households experienced certain levels of food insecurity,increasing the risk of displacement due to climate-related disasters.Climate change adaptation strategies including economic strategies,irrigation management strategies,organic-oriented strategies,sustainable development-oriented strategies,and crop variety management strategies played a significant role in reducing climate migration.Moreover,we found that climate change adaptation strategies not only impact food security,but also shape migration decisions.This research underscores the importance of an integrated approach that links climate change adaptation strategies,climate migration,and food insecurity.This study emphasizes the importance of food security for formulating sustainable adaptation strategies.展开更多
The Master Intelligent interview is based on the Stimulus-Organism-Response(SOR)theory,this study integrates key constructs from the Technology Acceptance Model(TAM)and the Theory of Planned Behavior(TPB),namely attit...The Master Intelligent interview is based on the Stimulus-Organism-Response(SOR)theory,this study integrates key constructs from the Technology Acceptance Model(TAM)and the Theory of Planned Behavior(TPB),namely attitude and behavioral intention,to develop a dual-path model of how AI empowerment influences college graduates’acceptance of intelligent interview technology.Taking AI empowerment as the independent variable,perceived risk and attitude as mediating variables,and behavioral intention as the outcome variable,the study employs questionnaire surveys and structural equation modeling(SEM)for empirical analysis.The results show that AI empowerment exerts a significant positive impact on attitude,perceived risk,and behavioral intention.Both perceived risk and attitude play significant mediating roles between AI empowerment and behavioral intention.Interestingly,perceived risk does not suppress behavioral intention;instead,it positively promotes it through a“rational trade-off”mechanism.Moreover,perceived risk and attitude form a significant chain-mediated pathway,revealing a continuous psychological transmission mechanism of“rational cognition-emotional adjustment-behavioral decision-making”.This study enriches the theoretical framework of AI technology acceptance,extends the application of the SOR model to the context of intelligent recruitment,and provides valuable implications for optimizing university career guidance and enterprise recruitment systems.展开更多
Social networks are vital for building the livelihood resilience of rural households.However,the impact of social networks on rural household livelihood resilience remains em-pirically underexplored,and most existing ...Social networks are vital for building the livelihood resilience of rural households.However,the impact of social networks on rural household livelihood resilience remains em-pirically underexplored,and most existing studies do not disaggregate social networks into different dimensions,which limits the understanding of specific mechanisms.Based on 895 household samples collected in China's Dabie Mountains and structural equation modeling,this paper explored the pathway to enhance livelihood resilience through social networks by dis-aggregating it into five dimensions:network size,interaction intensity,social cohesion,social support,and social learning.The results indicate that:(1)Livelihood assets,adaptive capacity and safety nets significantly contribute to livelihood resilience,whereas sensitivity negatively affects it.Accessibility to basic services has no significant relationship with livelihood resilience in the study area.(2)Social networks and their five dimensions positively impact livelihood re-silience,with network support having the greatest impact.Therefore,both the government and rural households should recognize and enhance the role of social networks in improving liveli-hood resilience under frequent disturbances.These findings have valuable implications for mitigating the risks of poverty recurrence and contributing to rural revitalization.展开更多
The expansion of the scale of the elderly care industry,the acquisition of market share,and the seizure of high profits depend on the consistency between the ecological niche of the elderly care industry and the actua...The expansion of the scale of the elderly care industry,the acquisition of market share,and the seizure of high profits depend on the consistency between the ecological niche of the elderly care industry and the actual resource and environmental conditions.Based on the situation theory of ecological niche,this paper expands the factor of“energy”and represents the three dimensions of“state,”“potential,”and“energy”from three aspects:market niche,technology niche,and resource niche.Taking 220 listed companies as samples,this paper improves the traditional catastrophe progression evaluation model and uses structural equation modeling to test the validity of the indicator system,thereby conducting evaluation research on the ecological niche of the elderly care industry.From the results of niche potential energy measurement,the three dimensions of market niche,resource niche,and technology niche are unevenly developed,reflecting the lack of competitiveness of the elderly care industry.展开更多
Background:Resilience is crucial for medical college students to thrive in the highly stressful environment of medical education.However,the prevalence of problematic internet use(PIU)in this population may negatively...Background:Resilience is crucial for medical college students to thrive in the highly stressful environment of medical education.However,the prevalence of problematic internet use(PIU)in this population may negatively impact their resilience.This study investigated the influence of problematic online gaming(PG)and problematic social media use(PSMU)on the resilience of medical college students in China.Methods:A sample of 5075 first-year medical college students from four Chinese universities was studied.PG served as the independent variable,resilience as the dependent variable,fatigue as the mediator,and PSMU as the moderator.Structural equation modeling was conducted using LISREL 8.80.Additionally,a moderated mediation model was evaluated using the jAMM module in jamovi 2.6.13.Results:The study’s findings revealed significant negative correlations between resilience and the variables of PG,PSMU,and fatigue.Fatigue mediated the relationship between PG and resilience(B=−0.04,95%CI=[−0.05,−0.03]).PSMU moderated the direct relationship between PG and resilience with the interaction term PG×PSMU significant(B=−0.004,t=−6.501,p<0.001)and the first stage(PG→fatigue)of the mediation with PG×PSMU significant(B=0.055,t=8.351,p<0.001).The detrimental effects of PG on resilience were more pronounced among individuals with lower levels of PSMU.Conclusion:This study concluded that addressing PIU,particularly PG,is essential for fostering resilience in medical college students.While PSMU itself is maladaptive,the underlying social media engagement may serve a protective role through social support in mitigating the adverse effects of PG on resilience.展开更多
Branch angles are an important plant morphological trait affecting light interception within forest canopies.However,studies on branch angles have been limited due to the time-consuming nature of manual measurements u...Branch angles are an important plant morphological trait affecting light interception within forest canopies.However,studies on branch angles have been limited due to the time-consuming nature of manual measurements using a protractor.Terrestrial laser scanning(TLS),however,provides new opportunities to measure branch angles more efficiently.Despite this potential,studies validating branch angle measurements from TLS have been limited.Here,our aim is to evaluate both manual and automatic branch angle measurements of European beech from TLS data using traditional field-measurements with a protractor as a reference.We evaluated the accuracy of branch angle measurements based on four automated algorithms(aRchiQSM,TreeQSM,Laplacian,SemanticLaplacian)from TLS data.Additionally,we assessed different ways of manual branch angle measurements in the field.Our study was based on a dataset comprising 124 branch angles measured from six European beech in a European deciduous forest.Our results show that manual branch angle measurements from TLS data are in high agreement with the reference(root-mean-squared error,RMSE:[3.57°-4.18°],concordance correlation coefficient,CCC:[0.950.97])across different branch length positions.Automated algorithms also are in high agreement with the reference although RMSE is approximately twice as large compared to manual branch angle measurements from TLS(RMSE:[9.29°-10.55°],CCC:[0.830.86])with manual leaf points removal.When applying the automatic wood-leaf separation algorithm,the performance of the four methods declined significantly,with only approximately 20 branch angles successfully identified.Moreover,it is important to note that there is no influence of the measurement position(branch surface versus center)for branch angle measurements.However,for curved branches,the selection of branch measurement length significantly impacts the branch angle measurement.This study provides a comprehensive understanding of branch angle measurements in forests.We show that automated measurement methods based on TLS data of branch angles are a valuable tool to quantify branch angles at larger scales.展开更多
Porosity is an important attribute for evaluating the petrophysical properties of reservoirs, and has guiding significance for the exploration and development of oil and gas. The seismic inversion is a key method for ...Porosity is an important attribute for evaluating the petrophysical properties of reservoirs, and has guiding significance for the exploration and development of oil and gas. The seismic inversion is a key method for comprehensively obtaining the porosity. Deep learning methods provide an intelligent approach to suppress the ambiguity of the conventional inversion method. However, under the trace-bytrace inversion strategy, there is a lack of constraints from geological structural information, resulting in poor lateral continuity of prediction results. In addition, the heterogeneity and the sedimentary variability of subsurface media also lead to uncertainty in intelligent prediction. To achieve fine prediction of porosity, we consider the lateral continuity and variability and propose an improved structural modeling deep learning porosity prediction method. First, we combine well data, waveform attributes, and structural information as constraints to model geophysical parameters, constructing a high-quality training dataset with sedimentary facies-controlled significance. Subsequently, we introduce a gated axial attention mechanism to enhance the features of dataset and design a bidirectional closed-loop network system constrained by inversion and forward processes. The constraint coefficient is adaptively adjusted by the petrophysical information contained between the porosity and impedance in the study area. We demonstrate the effectiveness of the adaptive coefficient through numerical experiments.Finally, we compare the performance differences between the proposed method and conventional deep learning methods using data from two study areas. The proposed method achieves better consistency with the logging porosity, demonstrating the superiority of the proposed method.展开更多
基金supported by the National Natural Science Foundation of China (No.72091511)the Science Fund for Distinguished Young Scholars of Hebei Province (No.E2022402064).
文摘Tuojiang River Basin is a first-class tributary of the upper reaches of the Yangtze River—which is the longest river in China.As phytoplankton are sensitive indicators of trophic changes inwater bodies,characterizing phytoplankton communities and their growth influencing factors in polluted urban rivers can provide new ideas for pollution control.Here,we used direct microscopic count and environmental DNA(eDNA)metabarcoding methods to investigate phytoplankton community structure in Tuojiang River Basin(Chengdu,Sichuan Province,China).The association between phytoplankton community structure and water environmental factors was evaluated by Mantel analysis.Additional environmental monitoring data were used to pinpoint major factors that influenced phytoplankton growth based on structural equation modeling.At the phylum level,the dominant phytoplankton taxa identified by the conventional microscopic method mainly belonged to Bacillariophyta,Chlorophyta,and Cyanophyta,in contrast with Chlorophyta,Dinophyceae,and Bacillariophyta identified by eDNA metabarcoding.Inα-diversity analysis,eDNA metabarcoding detected greater species diversity and achieved higher precision than the microscopic method.Phytoplankton growth was largely limited by phosphorus based on the nitrogen-to-phosphorus ratios>16:1 in all water samples.Redundancy analysis and structural equation modeling also confirmed that the nitrogen-to-phosphorus ratio was the principal factor influencing phytoplankton growth.The results could be useful for implementing comprehensive management of the river basin environment.It is recommended to control the discharge of point-and surface-source pollutants and the concentration of dissolved oxygen in areas with excessive nutrients(e.g.,Jianyang-Ziyang).Algae monitoring techniques and removal strategies should be improved in 201 Hospital,Hongrihe Bridge and Colmar Town areas.
基金National Natural Science Foundation of China(22073023)Natural Science Foundation of Henan Province(242300421134)+1 种基金the Young Backbone Teacher in Colleges and Universities of Henan Province(2021GGJS020)Foundation of State Key Laboratory of Antiviral Drugs。
文摘The acetylpolyamine oxidase(APAO),spermine oxidase(SMO),and spermidine/spermine N1-acetyltransferase(SSAT)are pivotal enzymes in polyamine metabolism,exerting direct influence on polyamine homeostasis regulation.Dysfunctions in these enzymes are intricately linked to inflammatory diseases and cancers.Establishing their three-dimensional structures is essential for exploring enzymatic catalytic mechanisms and designing inhibitors at the atomic level.This article primarily assesses the precision of AlphaFold2 and molecular dynamics simulations in determining the three-dimensional structures of these enzymes,utilizing protein conformation rationality assessment,residue correlation matrix,and other techniques.This provides robust models for subsequent polyamine catabolic metabolism calculations and offers valuable insights for modeling proteins that have yet to acquire crystal structures.
基金financially supported by the Innovation Foundation for Doctoral Program of Forestry Engineering of Northeast Forestry University,grant number:LYGC202117the China Scholarship Council(CSC),grant number:202306600046+1 种基金the Research and Development Plan of Applied Technology in Heilongjiang Province of China,grant number:GA19C006Research and Demonstration on Functional Improvement Technology of Forest Ecological Security Barrier in Heilongjiang Province,grant number:GA21C030。
文摘Background:As is widely known,an increasing number of forest areas were managed to preserve and enhance the health of forest ecosystems.However,previous research on forest management has often overlooked the importance of structure-based.Aims:Our objectives were to define the direction of structure-based forest management.Subsequently,we investigated the relationships between forest structure and the regeneration,growth,and mortality of trees under different thinning treatments.Ultimately,the drivers of forest structural change were explored.Methods:On the basis of 92 sites selected from northeastern China,with different recovery time (from 1 to 15years) and different thinning intensities (0–59.9%) since the last thinning.Principal component analysis (PCA)identified relationships among factors determining forest spatial structure.The structural equation model (SEM)was used to analyze the driving factors behind the changes in forest spatial structure after thinning.Results:Light thinning (0–20%trees removed) promoted forest regeneration,and heavy thinning (over 35% of trees removed) facilitated forest growth.However,only moderate thinning (20%–35%trees removed) created a reasonable spatial structure.While dead trees were clustered,and they were hardly affected by thinning intensity.Additionally,thinning intensity,recovery time,and altitude indirectly improve the spatial structure of the forest by influencing diameter at breast height (DBH) and canopy area.Conclusion:Creating larger DBH and canopy area through thinning will promote the formation of complex forest structures,which cultivates healthy and stable forests.
基金financially supported by the National Natural Science Foundation of China(Nos.31971631,41977083,and 41671252)。
文摘Intensive management is known to markedly alter soil carbon(C)storage and turnover in Moso bamboo forests compared with extensive management.However,the effects of intensive management on soil respiration(RS)components remain unclear.This study aimed to evaluate the changes in different RScomponents(root,mycorrhizal,and free-living microorganism respiration)in Moso bamboo forests under extensive and intensive management practices.A1-year in-situ microcosm experiment was conducted to quantify the RScomponents in Moso bamboo forests under the two management practices using mesh screens of varying sizes.The results showed that the total RSand its components exhibited similar seasonal variability between the two management practices.Compared with extensive management,intensive management significantly increased cumulative respiration from mycorrhizal fungi by 36.73%,while decreased cumulative respiration from free-living soil microorganisms by 8.97%.Moreover,the abundance of arbuscular mycorrhizal fungi(AMF)increased by 43.38%,but bacterial and fungal abundances decreased by 21.65%and 33.30%,respectively,under intensive management.Both management practices significantly changed the bacterial community composition,which could be mainly explained by soil pH and available potassium.Mycorrhizal fungi and intensive management affected the interrelationships between bacterial members.Structural equation modeling indicated that intensive management changed the cumulative RSby elevating AMF abundance and lowering bacterial abundance.We concluded that intensive management reduced the microbial respiration-derived C loss,but increased mycorrhizal respiration-derived C loss.
基金supported by the National Natural Science Foundation of China(41872174 and 42072189)the Program for Innovative Research Team(in Science and Technology)in the Universities of Henan Province,China(21IRTSTHN007)the Program for Innovative Research Team(in Science and Technology)of Henan Polytechnic University(T2020-4)。
文摘Elemental analysis,nuclear magnetic resonance carbon spectroscopy(^(13)C-NMR),X-ray photoelectron spectroscopy(XPS)and Fourier transform infrared spectroscopy(FTIR)experiments were carried out to determine the existence of aromatic structure,heteroatom structure and fat structure in coal.MS(materials studio)software was used to optimize and construct a 3D molecular structure model of coal.A method for establishing a coal molecular structure model was formed,which was“determination of key structures in coal,construction of planar molecular structure model,and optimization of three-dimensional molecular structure model”.The structural differences were compared and analyzed.The results show that with the increase of coal rank,the dehydrogenation of cycloalkanes in coal is continuously enhanced,and the content of heteroatoms in the aromatic ring decreases.The heteroatoms and branch chains in the coal are reduced,and the structure is more orderly and tight.The stability of the structure is determined by theπ-πinteraction between the aromatic rings in the nonbonding energy EN.Key Stretching Energy The size of EB determines how tight the structure is.The research results provide a method and reference for the study of the molecular structure of medium and high coal ranks.
文摘To design the control system for some homing missile so that the autopilot can transfer guidance command correctly and be robust to disturbances, such as the measurement noises and parameter variation caused by areodynamic floating. The model reference adaptive control was combined with the variable structure control to design a model reference variable structure (MRVS) control system whose control structure is simple and can be realized easily. The simulation results indicate that MRVS can complete the task of transferring guidance command and suppress the distrubances effectively.
基金supported by the National Natural Science Foundation of China(No.42377415)the Natural Science Foundation of Sichuan Province(No.2023NSFSC0811),Sichuan Science and Technology Program(Nos.2021JDTD0013 and 2021YFQ0066)+1 种基金the Science and Technology Major Project of Xizhang Autonomous Region of China(No.XZ202201ZD0004G06)the Everest Scientific Research Program(No.80000-2023ZF11405).
文摘The large-scale exploitation of vanadium(Ⅴ) bearing minerals has led to a massive accumulation of Ⅴ tailings, of which Ⅴ pollution poses severe ecological risks. Although the mechanisms of Ⅴ stress to the microbial community have been reported, the influential pathways in a multi-medium-containing system, for example, the soil-tailings-groundwater system,are unknown. The dynamic redox conditions and substance exchange within the system exhibited complex Ⅴ stress on the local microbial communities. In this study, the influence pathways of Ⅴ stress to the microbial community in the soil-tailings-groundwater system were first investigated. High Ⅴ contents were observed in groundwater(139.2 ± 0.15 μg/L) and soil(98.0–323.8 ± 0.02 mg/kg), respectively. Distinct microbial composition was observed for soil and groundwater, where soil showed the highest level of diversity and richness. Firmicutes, Proteobacteria, Actinobacteria, and Acidobacteria were dominant in soil and groundwater with a sum relative abundance of around 80 %. Based on redundancy analysis and structural equation models, Ⅴ was one of the vital driving factors affecting microbial communities. Groundwater microbial communities were influenced by Ⅴ via Cr, dissolved oxygen, and total nitrogen, while Fe, Mn, and total phosphorus were the key mediators for Ⅴ to affect soil microbial communities. Ⅴ affected the microbial community via metabolic pathways related to carbonaceous matter, which was involved in the establishment of survival strategies for metal stress. This study provides novel insights into the influence pathways of Ⅴ on the microorganisms in tailings reservoir for pollution bioremediation.
基金funded by Humanities and Social Sciences Foundation and Natural Science Foundation of Nanjing University of Posts and Telecommunications(NYY222055,NY224176)General Subject of Educational Science Planning in Jiangsu Province(C/2024/01/76)National Natural Science Foundation of China(62307025).
文摘Objectives:Teachers are facing unprecedented new challenges leading them to face an increasing number of tasks that are not part of their job,as well as having to cope with the additional skills acquisition that comes with non-traditional forms of teaching and learning,and increased work pressure leading to an increase in the rate of teachers leaving the profession.Therefore,this study aims to explore the mechanism of the career calling on job burnout through career adaptability and work engagement.Methods:This study conducted a cross-sectional survey of 465 primary and secondary school teachers(PSST)in China's Mainland from the perspective of work adjustment and used structural equation modeling(SEM)to examine the mediating roles of career adaptability and work engagement in the relationship between teachers’career calling and job burnout.Results:The results show that PSSTs are above average in career calling,career adaptability,and work engagement,while job burnout is below average.A significant positive or negative correlation exists between career calling,career adaptability,work engagement,and job burnout.The result of path analysis indicates that career adaptability and work engagement exert an indirect influence on the job burnout of PSST through three paths:namely,the independent intermediary role of career adaptability(EV=−0.144),the independent intermediary role of work engagement(EV=0.172)and the chain intermediary role of the two(EV=0.176).Conclusion:This study emphasizes the importance of career adaptability and work engagement in teacher development in regulating career calling and job burnout.Therefore,on the one hand,we think that if managers want to reduce teachers’job burnout,they need to pay more attention to teachers’career adaptability and work engagement,rather than relying solely on teachers’career calling.On the other hand,it is to remind teachers not to rely on their adjustment to adapt to the work,but also to need outside help as much as possible.
文摘High-Entropy Alloys(HEAs)exhibit significant potential across multiple domains due to their unique properties.However,conventional research methodologies face limitations in composition design,property prediction,and process optimization,characterized by low efficiency and high costs.The integration of Artificial Intelligence(AI)technologies has provided innovative solutions for HEAs research.This review presented a detailed overview of recent advancements in AI applications for structural modeling and mechanical property prediction of HEAs.Furthermore,it discussed the advantages of big data analytics in facilitating alloy composition design and screening,quality control,and defect prediction,as well as the construction and sharing of specialized material databases.The paper also addressed the existing challenges in current AI-driven HEAs research,including issues related to data quality,model interpretability,and cross-domain knowledge integration.Additionally,it proposed prospects for the synergistic development of AI-enhanced computational materials science and experimental validation systems.
基金the support of the China Three Gorges Corporation Science and Technology Fund, with the numbers 0799275the support of the National Natural Science Foundation of China, with the numbers 42174177 and 62106239。
文摘The study area is rich in shale gas resources and has reached the stage of comprehensive development. Shale gas extraction poses risks such as induced seismicity and well closure, compounded by the limited availability of fi xed seismic monitoring stations nearby. To address these challenges, a dense observation array was developed within the study area to monitor and analyze microseismic activity during hydraulic fracturing. Microseismic events generated by hydraulic fracturing typically exhibit low amplitude and signal-to-noise ratio, rendering traditional manual analysis methods impractical. To overcome these limitations, an innovative artifi cial intelligence method combining picking-association-location (PAL) and match-expand- shift-stack (MESS) techniques (PALM) has been utilized for automated seismic detection. Numerous factors influence the accuracy of microseismic detection and localization. To evaluate these factors, the effects of various velocity structure models, instrument types, and station distributions on seismic location were analyzed and compared. The results indicate that the PALM method significantly mitigates the influence of velocity structure models on seismic location accuracy. Additionally, the use of broadband seismic instruments and a uniform station distribution enhances the precision of seismic location results. Furthermore, by integrating data from diff erent types of observation instruments, a comprehensive seismic catalog for the study area was established. These fi ndings not only enhance seismic location accuracy but also provide valuable guidance for optimizing regional seismic monitoring network design and improving seismic risk assessment.
基金supported by Scientific Research Fund of Hunan Provincial EducationDepartment(23B1133):How Labor Affects Moral Development:Based on the perspective of mixed research methods.
文摘Background:Understanding the factors that influence adolescent psychological resilience is critical for promoting mental health.This study explores the impact and mechanism of labor values on adolescent psychological resilience from the perspective of emotion regulation theory.Methods:This study conducted an in-depth analysis using the Labor Value Scale on 2691 elementary school upper-grade students,middle school students,and high school students.Results:The results show that:(1)labor values can positively predict adolescents’mental resilience;(2)cognitive reappraisal and expression inhibition play a partial mediating role in the relationship between labor values and adolescents’psychological resilience.Among them,labor values can positively predict adolescents’mental resilience through positive cognitive reappraisal,and labor values can also predict adolescents’mental resilience through expression inhibition.Conclusion:Based on the theory of emotion regulation,this study explores the direct effect of labor values on mental resilience and the mediating effect of different strategies of emotion regulation.The results of this study provide a theoretical basis for improving the mental resilience of adolescents.
基金Supported by Young Talent Project of Air Force Medical Center,No.2022YXQN008and Rapid Response Project of Air Force Medical University,No.2023KXKT041.
文摘BACKGROUND Depression,anxiety,and insomnia were found out that were significant relevance to the mental health impact of the coronavirus disease 2019(COVID-19)lock-down.AIM To examine the interrelationships among perceived severity,anxiety,depression,insomnia,and sense of security in Chinese community residents during the COVID-19 lockdown period.METHODS Participants were selected using simple random sampling from four large gated communities in Chengdu,China.All participants were invited to complete a survey that included the Perceived Severity Questionnaire,Security Question-naire,Patient Health Questionnaire-9,Generalized Anxiety Disorder 7-item,and Insomnia Severity Index-7.In total,568 valid questionnaires were gathered.Co-rrelation analysis and structural equation models were used to explore the rela-RESULTS The observed prevalence rates of anxiety,depression,and insomnia among residents during lockdown were 27.5%,17.6%,and 16.0%,respectively.Correlation analysis showed that both perceived severity and sense of security were positively correlated with anxiety,depression,and insomnia[Pearson’s r was perceived severity and anxiety r=0.44(P<0.01);with depression r=0.48(P<0.01);with insomnia r=0.43(P<0.01);security with anxiety r=-0.65(P<0.01);with depression r=-0.65(P<0.01);with insomnia r=-0.53(P<0.01)].Structural equation modeling and bootstrap tests revealed that sense of security acted as a significant mediator in the relationship between perceived severity and emotional and sleep disorders(anxiety,depression,and insomnia).CONCLUSION This study demonstrates that sense of security is a significant predictor of emotional and sleep disorders(namely,depression,anxiety,and insomnia)among residents during the COVID-19 lockdown,with sense of security acting as a mediating factor.These findings suggest that mental health interventions for Chinese community residents during lockdowns may benefit from developing community-based educational programs to reduce perceived severity and ensuring the stable supply of essential resources and promoting social support networks to enhance the sense of security.
基金the financial support by the Major Research Plan of National Natural Science Foundation of China(92062219)the Young Elite Scientists Sponsorship Program by BAST(No.BYESS2023411)+2 种基金the Open Research Project from the State Key Laboratory of Geological Processes and Mineral Resources,China University of Geosciences(GPMR202407)the Geological Survey Project of the China Geological Survey„General survey of Hadamengou Rock Gold Deposit in Inner Mongolia'(DD20191017)the Geological Survey Project(H90063).
文摘Controversy is ongoing regarding the relationship between ore formation and the structural evolution of the Hadamengou gold deposit.To address this issue,we conducted a comprehensive investigation of mineralization-related structures,geochronology and Fe isotopes.From the perspective of spatial evolution,hydrothermal fluids originating from the Shadegai and Xishadegai plutons have extracted accumulated ore-forming elements from the Wulashan Group(Ar2WL)and then evolved,initiating at Exploration Line 11 and migrating eastwards and westwards along the EW-trending thrust fault system to form orebodies.From the temporal evolution standpoint,the Wulashan Group(Ar_(2)WL)experienced diagenesis(2591.00 Ma to 2204.00 Ma)and metamorphism(2074.00 Ma to 1625.00 Ma)from late Neoarchean to early Paleoproterozoic,when ore-forming materials were initially accumulated;in the early Paleozoic(440.71 Ma to 425.00 Ma),the collision led to the formation of early-stage EW-trending imbricated thrust faults,which established a fundamental structural framework for the orefield and further accumulated ore-forming materials;from the late Paleozoic to the Mesozoic,multiple subsequent episodes of regional tectonic-magmatic-hydrothermal events have superimposed,modified and reactivated the thrust fault system.Notably,the Triassic period,particularly between 245.00 Ma and 217.90 Ma,is considered to be a primary ore-forming stage.In summary,the intricate relationship between ore-formation and structural evolution has been fundamentally elucidated.
基金support provided by the Department of Agricultural Economics and Rural Development,Faculty of Agriculture,Lorestan University,Iran.
文摘As the impact of climate change intensifies,climate migration(climate change-induced migration)has become a pressing global issue that requires effective adaptation strategies to lessen its effects.Therefore,this study delved into the complex relationship between climate change adaptation strategies and climate migration with food insecurity serving as a mediating factor.We collected sample data through face-to-face interviews in Khorramabad City,Iran from February to May in 2023.Using the Structural Equation Modeling(SEM),we explored how food insecurity influences the relationship between climate change adaptation strategies and climate migration.The findings showed that while climate change adaptation strategies can boost community resilience,their success is closely tied to levels of food insecurity.About 78.72%of the surveyed households experienced certain levels of food insecurity,increasing the risk of displacement due to climate-related disasters.Climate change adaptation strategies including economic strategies,irrigation management strategies,organic-oriented strategies,sustainable development-oriented strategies,and crop variety management strategies played a significant role in reducing climate migration.Moreover,we found that climate change adaptation strategies not only impact food security,but also shape migration decisions.This research underscores the importance of an integrated approach that links climate change adaptation strategies,climate migration,and food insecurity.This study emphasizes the importance of food security for formulating sustainable adaptation strategies.
基金The 2025 Guizhou University of Finance and Economics University-level Project“Research on the‘Action-Learning’Strategy of Artificial Intelligence in Complex Tasks”(Project No.:2025BAZYSY287)。
文摘The Master Intelligent interview is based on the Stimulus-Organism-Response(SOR)theory,this study integrates key constructs from the Technology Acceptance Model(TAM)and the Theory of Planned Behavior(TPB),namely attitude and behavioral intention,to develop a dual-path model of how AI empowerment influences college graduates’acceptance of intelligent interview technology.Taking AI empowerment as the independent variable,perceived risk and attitude as mediating variables,and behavioral intention as the outcome variable,the study employs questionnaire surveys and structural equation modeling(SEM)for empirical analysis.The results show that AI empowerment exerts a significant positive impact on attitude,perceived risk,and behavioral intention.Both perceived risk and attitude play significant mediating roles between AI empowerment and behavioral intention.Interestingly,perceived risk does not suppress behavioral intention;instead,it positively promotes it through a“rational trade-off”mechanism.Moreover,perceived risk and attitude form a significant chain-mediated pathway,revealing a continuous psychological transmission mechanism of“rational cognition-emotional adjustment-behavioral decision-making”.This study enriches the theoretical framework of AI technology acceptance,extends the application of the SOR model to the context of intelligent recruitment,and provides valuable implications for optimizing university career guidance and enterprise recruitment systems.
基金National Natural Science Foundation of China,No.42371315,No.41901213。
文摘Social networks are vital for building the livelihood resilience of rural households.However,the impact of social networks on rural household livelihood resilience remains em-pirically underexplored,and most existing studies do not disaggregate social networks into different dimensions,which limits the understanding of specific mechanisms.Based on 895 household samples collected in China's Dabie Mountains and structural equation modeling,this paper explored the pathway to enhance livelihood resilience through social networks by dis-aggregating it into five dimensions:network size,interaction intensity,social cohesion,social support,and social learning.The results indicate that:(1)Livelihood assets,adaptive capacity and safety nets significantly contribute to livelihood resilience,whereas sensitivity negatively affects it.Accessibility to basic services has no significant relationship with livelihood resilience in the study area.(2)Social networks and their five dimensions positively impact livelihood re-silience,with network support having the greatest impact.Therefore,both the government and rural households should recognize and enhance the role of social networks in improving liveli-hood resilience under frequent disturbances.These findings have valuable implications for mitigating the risks of poverty recurrence and contributing to rural revitalization.
基金Natural Science Foundation Project of Hebei Provincial Science and Technology Department(G2023415001)Humanities and Social Sciences Research Project of Colleges and Universities in Hebei Province(SD2021084)The 2025 Hebei Province Social Science Development Research Project titled“Practical Research on Hebei Province’s Undertaking of the Elderly Care Service Industry from Beijing and Tianjin under the Collaborative Development of the Beijing-Tianjin-Hebei Region”。
文摘The expansion of the scale of the elderly care industry,the acquisition of market share,and the seizure of high profits depend on the consistency between the ecological niche of the elderly care industry and the actual resource and environmental conditions.Based on the situation theory of ecological niche,this paper expands the factor of“energy”and represents the three dimensions of“state,”“potential,”and“energy”from three aspects:market niche,technology niche,and resource niche.Taking 220 listed companies as samples,this paper improves the traditional catastrophe progression evaluation model and uses structural equation modeling to test the validity of the indicator system,thereby conducting evaluation research on the ecological niche of the elderly care industry.From the results of niche potential energy measurement,the three dimensions of market niche,resource niche,and technology niche are unevenly developed,reflecting the lack of competitiveness of the elderly care industry.
基金supported by General Education Project of the National Social Science Foundation in 2020:“Multi-Dimensional Reconstruction of Peer Review Mechanisms in the Evaluation of Scientific and Technological Talents in Universities(BIA200167).”。
文摘Background:Resilience is crucial for medical college students to thrive in the highly stressful environment of medical education.However,the prevalence of problematic internet use(PIU)in this population may negatively impact their resilience.This study investigated the influence of problematic online gaming(PG)and problematic social media use(PSMU)on the resilience of medical college students in China.Methods:A sample of 5075 first-year medical college students from four Chinese universities was studied.PG served as the independent variable,resilience as the dependent variable,fatigue as the mediator,and PSMU as the moderator.Structural equation modeling was conducted using LISREL 8.80.Additionally,a moderated mediation model was evaluated using the jAMM module in jamovi 2.6.13.Results:The study’s findings revealed significant negative correlations between resilience and the variables of PG,PSMU,and fatigue.Fatigue mediated the relationship between PG and resilience(B=−0.04,95%CI=[−0.05,−0.03]).PSMU moderated the direct relationship between PG and resilience with the interaction term PG×PSMU significant(B=−0.004,t=−6.501,p<0.001)and the first stage(PG→fatigue)of the mediation with PG×PSMU significant(B=0.055,t=8.351,p<0.001).The detrimental effects of PG on resilience were more pronounced among individuals with lower levels of PSMU.Conclusion:This study concluded that addressing PIU,particularly PG,is essential for fostering resilience in medical college students.While PSMU itself is maladaptive,the underlying social media engagement may serve a protective role through social support in mitigating the adverse effects of PG on resilience.
基金supported by the Chinese Scholarship Council under Grant 202106910006.
文摘Branch angles are an important plant morphological trait affecting light interception within forest canopies.However,studies on branch angles have been limited due to the time-consuming nature of manual measurements using a protractor.Terrestrial laser scanning(TLS),however,provides new opportunities to measure branch angles more efficiently.Despite this potential,studies validating branch angle measurements from TLS have been limited.Here,our aim is to evaluate both manual and automatic branch angle measurements of European beech from TLS data using traditional field-measurements with a protractor as a reference.We evaluated the accuracy of branch angle measurements based on four automated algorithms(aRchiQSM,TreeQSM,Laplacian,SemanticLaplacian)from TLS data.Additionally,we assessed different ways of manual branch angle measurements in the field.Our study was based on a dataset comprising 124 branch angles measured from six European beech in a European deciduous forest.Our results show that manual branch angle measurements from TLS data are in high agreement with the reference(root-mean-squared error,RMSE:[3.57°-4.18°],concordance correlation coefficient,CCC:[0.950.97])across different branch length positions.Automated algorithms also are in high agreement with the reference although RMSE is approximately twice as large compared to manual branch angle measurements from TLS(RMSE:[9.29°-10.55°],CCC:[0.830.86])with manual leaf points removal.When applying the automatic wood-leaf separation algorithm,the performance of the four methods declined significantly,with only approximately 20 branch angles successfully identified.Moreover,it is important to note that there is no influence of the measurement position(branch surface versus center)for branch angle measurements.However,for curved branches,the selection of branch measurement length significantly impacts the branch angle measurement.This study provides a comprehensive understanding of branch angle measurements in forests.We show that automated measurement methods based on TLS data of branch angles are a valuable tool to quantify branch angles at larger scales.
基金the support of Research Program of Fine Exploration and Surrounding Rock Classification Technology for Deep Buried Long Tunnels Driven by Horizontal Directional Drilling and Magnetotelluric Methods Based on Deep Learning under Grant E202408010the Sichuan Science and Technology Program under Grant 2024NSFSC1984 and Grant 2024NSFSC1990。
文摘Porosity is an important attribute for evaluating the petrophysical properties of reservoirs, and has guiding significance for the exploration and development of oil and gas. The seismic inversion is a key method for comprehensively obtaining the porosity. Deep learning methods provide an intelligent approach to suppress the ambiguity of the conventional inversion method. However, under the trace-bytrace inversion strategy, there is a lack of constraints from geological structural information, resulting in poor lateral continuity of prediction results. In addition, the heterogeneity and the sedimentary variability of subsurface media also lead to uncertainty in intelligent prediction. To achieve fine prediction of porosity, we consider the lateral continuity and variability and propose an improved structural modeling deep learning porosity prediction method. First, we combine well data, waveform attributes, and structural information as constraints to model geophysical parameters, constructing a high-quality training dataset with sedimentary facies-controlled significance. Subsequently, we introduce a gated axial attention mechanism to enhance the features of dataset and design a bidirectional closed-loop network system constrained by inversion and forward processes. The constraint coefficient is adaptively adjusted by the petrophysical information contained between the porosity and impedance in the study area. We demonstrate the effectiveness of the adaptive coefficient through numerical experiments.Finally, we compare the performance differences between the proposed method and conventional deep learning methods using data from two study areas. The proposed method achieves better consistency with the logging porosity, demonstrating the superiority of the proposed method.
