In cold regions,slope rocks are inevitably impacted by freeze-thaw,dry-wet cycles and their alternating actions,leading to strength weakening and pore degradation.In this study,the mechanical and microstructural prope...In cold regions,slope rocks are inevitably impacted by freeze-thaw,dry-wet cycles and their alternating actions,leading to strength weakening and pore degradation.In this study,the mechanical and microstructural properties of schist subjected to four conditions were investigated:freeze-thaw cycles in air(FTA),freeze-thaw cycles in water(FTW),dry-wet cycles(DW),and dry-wet-freeze-thaw cycles(DWFT).Uniaxial compressive strength(UCS),water absorption,ultrasonication,low-field nuclear magnetic resonance,and scanning electron microscopy analyses were conducted.The integrity attenuation characteristics of the longitudinal wave velocity,UCS,and elastic modulus were analyzed.The results showed that liquid water emerged as a critical factor in reducing the brittleness of schist.The attenuation function model accurately described the peak stress and static elastic modulus of schist in various media(R2>0.97).Different media affected the schist deterioration and half-life,with the FTW-immersed samples having a half-life of 28 cycles.Furthermore,the longitudinal wave velocity decreased as the number of cycles increased,with the FTW showing the most significant reduction and having the shortest half-life of 208 cycles.Moreover,the damage variables of compressive strength and elastic modulus increased with the number of cycles.After 40 cycles,the schist exposed to FTW exhibited the highest damage variables and saturated water content.展开更多
Since April 2002,the Gravity Recovery and Climate Experiment Satellite(GRACE)has provided monthly total water storage anomalies(TWSAs)on a global scale.However,these TWSAs are discontinuous because some GRACE observat...Since April 2002,the Gravity Recovery and Climate Experiment Satellite(GRACE)has provided monthly total water storage anomalies(TWSAs)on a global scale.However,these TWSAs are discontinuous because some GRACE observation data are missing.This study presents a combined machine learning-based modeling algorithm without hydrological model data.The TWSA time-series data for 11 large regions worldwide were divided into training and test sets.Autoregressive integrated moving average(ARIMA),long short-term memory(LSTM),and an ARIMA-LSTM combined model were used.The model predictions were compared with GRACE observations,and the model accuracy was evaluated using fi ve metrics:the Nash-Sutcliff e effi ciency coeffi cient(NSE),Pearson correlation coeffi cient(CC),root mean square error(RMSE),normalized RMSE(NRMSE),and mean absolute percentage error.The results show that at the basin scale,the mean CC,NSE,and NRMSE for the ARIMA-LSTM model were 0.93,0.83,and 0.12,respectively.At the grid scale,this study compared the spatial distribution and cumulative distribution function curves of the metrics in the Amazon and Volga River basins.The ARIMA-LSTM model had mean CC and NSE values of 0.89 and 0.61 and 0.92 and 0.61 in the Amazon and Volga River basins,respectively,which are superior to those of the ARIMA model(0.86 and 0.48 and 0.88 and 0.46,respectively)and the LSTM model(0.80 and 0.41 and 0.89 and 0.31,respectively).In the ARIMA-LSTM model,the proportions of grid cells with NSE>0.50 for the two basins were 63.3%and 80.8%,while they were 54.3%and 51.3%in the ARIMA model and 53.7%and 43.2%in the LSTM model.The ARIMA-LSTM model significantly improved the NSE values of the predictions while guaranteeing high CC values in the GRACE data reconstruction at both scales,which can aid in fi lling in discontinuous data in temporal gravity fi eld models..展开更多
Spherical harmonic analysis(SHA)and synthesis(SHS)are widely used by researchers in various fields.Both numerical integration and least-squares methods can be employed for analysis and synthesis.However,these approach...Spherical harmonic analysis(SHA)and synthesis(SHS)are widely used by researchers in various fields.Both numerical integration and least-squares methods can be employed for analysis and synthesis.However,these approaches,when calculated via summation,are computationally intensive.Although the Fast Fourier Transform(FFT)algorithm is efficient,it is traditionally limited to processing global grid points starting from zero longitude.In this paper,we derive an improved FFT algorithm for spherical harmonic analysis and synthesis.The proposed algorithm eliminates the need for grid points to start at zero longitude,thereby expanding the applicability of FFT-based methods.Numerical experiments demonstrate that the new algorithm retains the computational efficiency of conventional FFT while achieving accuracy comparable to the summation method.Consequently,it enables direct harmonic coefficient calculation from global grid data without requiring interpolation to align with zero longitude.Additionally,the algrithm can generate grid points with equi-angular spacing using the improved FFT algorithm,starting from non-zero longitudes.To address the loss of orthogonality in latitude due to discrete spherical grids,a quadrature weight factor-dependent on grid type(e.g.,regular or Gauss grid)-is incorporated,as summarized in this study.展开更多
Understanding the characteristics and driving factors behind changes in vegetation ecosystem resilience is crucial for mitigating both current and future impacts of climate change. Despite recent advances in resilienc...Understanding the characteristics and driving factors behind changes in vegetation ecosystem resilience is crucial for mitigating both current and future impacts of climate change. Despite recent advances in resilience research, significant knowledge gaps remain regarding the drivers of resilience changes. In this study, we investigated the dynamics of ecosystem resilience across China and identified potential driving factors using the kernel normalized difference vegetation index(kNDVI) from 2000 to 2020. Our results indicate that vegetation resilience in China has exhibited an increasing trend over the past two decades, with a notable breakpoint occurring around 2012. We found that precipitation was the dominant driver of changes in ecosystem resilience, accounting for 35.82% of the variation across China, followed by monthly average maximum temperature(Tmax) and vapor pressure deficit(VPD), which explained 28.95% and 28.31% of the variation, respectively. Furthermore, we revealed that daytime and nighttime warming has asymmetric impacts on vegetation resilience, with temperature factors such as Tmin and Tmax becoming more influential, while the importance of precipitation slightly decreases after the resilience change point. Overall, our study highlights the key roles of water availability and temperature in shaping vegetation resilience and underscores the asymmetric effects of daytime and nighttime warming on ecosystem resilience.展开更多
Geological storage and utilization of CO_(2)involve complex interactions among Thermo-hydromechanical-chemical(THMC)coupling processes,which significantly affect storage integrity and efficiency.To address the challen...Geological storage and utilization of CO_(2)involve complex interactions among Thermo-hydromechanical-chemical(THMC)coupling processes,which significantly affect storage integrity and efficiency.To address the challenges in accurately simulating these coupled phenomena,this paper systematically reviews recent advances in the mathematical modeling and numerical solution of THMC coupling in CO_(2)geological storage.The study focuses on the derivation and structure of governing and constitutive equations,the classification and comparative performance of fully coupled,iteratively coupled,and explicitly coupled solution methods,and the modeling of dynamic changes in porosity,permeability,and fracture evolution induced by multi-field interactions.Furthermore,the paper evaluates the capabilities,application scenarios,and limitations of major simulation platforms,including TOUGH,CMG-GEM,and COMSOL.By establishing a comparative framework integrating model formulations and solver strategies,this work clarifies the strengths and gaps of current approaches and contributes to the development of robust,scalable,and mechanism-oriented numerical models for long-term prediction of CO_(2)behavior in geological formations.展开更多
An analytical seismic fragility assessment framework is presented for the existing low strength reinforced concrete structures more common in the building stock of the developing countries.For realistic modelling of s...An analytical seismic fragility assessment framework is presented for the existing low strength reinforced concrete structures more common in the building stock of the developing countries.For realistic modelling of such substandard structures,low strength concrete stress-strain and bond-slip capacity models are included in calibrating material models.Key capacity parameters are generated stochastically to produce building population and cyclic pushover analysis is carried out to capture inelastic behaviour.Secant period values are evaluated corresponding to each displacement step on the capacity curves and used as seismic demand.A modified capacity demand diagram method is adopted for the degrading structures,which is further used to evaluate peak ground acceleration from back analysis considering each point on the capacity curve as performance point.For developing fragility curves,the mean values of peak ground acceleration are evaluated corresponding to each performance point on the series of capacity curves.A suitable probability distribution function is adopted for the secant period scatter at different mean peak ground acceleration values and probability of exceedance of limit states is evaluated.A suitable regression function is used for developing fragility curves and regression coefficients are proposed for different confidence levels.Fragility curves are presented for a low rise pre-seismic code reinforced concrete structure typical of developing countries.展开更多
Protecting the ecological security of the Qinghai-Tibet Plateau(QTP)is of great importance for global ecology and climate.Over the past few decades,climate extremes have posed a significant challenge to the ecological...Protecting the ecological security of the Qinghai-Tibet Plateau(QTP)is of great importance for global ecology and climate.Over the past few decades,climate extremes have posed a significant challenge to the ecological environment of the QTP.However,there are few studies that explored the effects of climate extremes on ecological environment quality of the QTP,and few researchers have made quantitative analysis.Hereby,this paper proposed the Ecological Environmental Quality Index(EEQI)for analyzing the spatial and temporal variation of ecological environment quality on the QTP from 2000 to 2020,and explored the effects of climate extremes on EEQI based on Geographically and Temporally Weighted Regression(GTWR)model.The results showed that the ecological environment quality in QTP was poor in the west,but good in the east.Between 2000 and 2020,the area of EEQI variation was large(34.61%of the total area),but the intensity of EEQI variation was relatively low and occurred mainly by a slightly increasing level(EEQI change range of 0.05-0.1).The overall ecological environment quality of the QTP exhibited spatial and temporal fluctuations,which may be attributed to climate extremes.Significant spatial heterogeneity was observed in the effects of the climate extremes on ecological environment quality.Specifically,the effects of daily temperature range(DTR),number of frost days(FD0),maximum 5-day precipitation(RX5day),and moderate precipitation days(R10)on ecological environment quality were positive in most regions.Furthermore,there were significant temporal differences in the effects of consecutive dry days(CDD),consecutive wet days(CWD),R10,and FD0 on ecological environment quality.These differences may be attributed to variances in ecological environment quality,climate extremes,and vegetation types across different regions.In conclusion,the impact of climate extremes on ecological environment quality exhibits complex patterns.These findings will assist managers in identifying changes in the ecological environment quality of the QTP and addressing the effects of climate extremes.展开更多
The ecological environment of the Yellow River Basin has become more fragile under the combined action of natural and manmade activities.However,the change mechanisms of ecological vulnerability in different sub-regio...The ecological environment of the Yellow River Basin has become more fragile under the combined action of natural and manmade activities.However,the change mechanisms of ecological vulnerability in different sub-regions and periods vary,and the reasons for this variability are yet to be explained.Thus,in this study,we proposed a new remote sensing ecological vulnerability index by considering moisture,heat,greenness,dryness,land degradation,and social economy indicators and then analyzed and disclosed the spatial and temporal change patterns of ecological vulnerability of the Yellow River Basin,China from 2000 to 2022 and its driving mechanisms.The results showed that the newly proposed remote sensing ecological vulnerability index had a high accuracy,at 86.36%,which indicated a higher applicability in the Yellow River Basin.From 2000 to 2022,the average remote sensing ecological vulnerability index of the Yellow River Basin was 1.03,denoting moderate vulnerability level.The intensive vulnerability area was the most widely distributed,which was mostly located in the northern part of Shaanxi Province and the eastern part of Shanxi Province.From 2000 to 2022,the ecological vulnerability in the Yellow showed an overall stable trend,while that of the central and eastern regions showed an obvious trend of improvement.The gravity center of ecological vulnerability migrated southwest,indicating that the aggravation of ecological vulnerability in the southwestern regions was more severe than in the northeastern regions of the basin.The dominant single factor of changes in ecological vulnerability shifted from normalized difference vegetation index(NDVI)to temperature from 2000 to 2022,and the interaction factors shifted from temperature∩NDVI to temperature∩precipitation,which indicated that the global climate change exerted a more significant impact on regional ecosystems.The above results could provide decision support for the ecological protection and restoration of the Yellow River Basin.展开更多
The occurrence of the Wenchuan earthquake caused the degradation of regional ecosystems,including vegetation destruction.However,the post-seismic vegetation recovery and its driving forces on the spatial-temporal scal...The occurrence of the Wenchuan earthquake caused the degradation of regional ecosystems,including vegetation destruction.However,the post-seismic vegetation recovery and its driving forces on the spatial-temporal scale are still vague,especially in the severely damaged areas(including Wenchuan,Beichuan,Mianzhu,Shifang,Qingchuan,Maoxian,Anzhou,Dujiangyan,Pingwu and Pengzhou).Here,we detected vegetation recovery in the severely damaged areas by using Ensemble Empirical Mode Decomposition(EEMD)to analyze the time series characteristics of the Enhanced Vegetation Index(EVI),and explored the driving effects of climate,land use types,nighttime light,water system,slope,and clay content on vegetation recovery based on Geographically and Temporally Weighted Regression(GTWR)model.The results indicated that the post-seismic vegetation recovery rate increased rapidly(acceleration>0)but slowed down after 2013.And the areas of best vegetation recovery(EVI increments>0.1)were distributed in the north of the study area,the Minjiang River Basin,and front fault and central fault of the Longmenshan Fault Zone.While the areas with the worst vegetation recovery(EVI increments<-0.1)were concentrated in the southern high-altitude areas and the Chengdu Plain.Additionally,a process attribution of the driving forces of vegetation recovery indicated that accumulated precipitation and maximum temperature promoted vegetation recovery(regression coefficients>0),but the impacts weakened after the earthquake,possibly due to the increase of secondary disasters induced by precipitation and the rise in maximum temperature.The impact of cultivated land on vegetation recovery was mostly positive(regression coefficients>0),which may be related to the implementation of the Grain for Green Project.The nighttime light inhibited vegetation recovery(regression coefficients<0),which could be closely associated with urbanization.The results indicated that more attention should be paid to the nonlinear variations of post-earthquake vegetation recovery trends,and the effects of climatic and anthropogenic factors on vegetation recovery also should not be underestimated.展开更多
Based on the analysis of the whole process of LNG spill on land,the research methods of LNG pool expansion and heavy gas diffusion are summarized and analyzed.This paper reviews the experimental and analytical work pe...Based on the analysis of the whole process of LNG spill on land,the research methods of LNG pool expansion and heavy gas diffusion are summarized and analyzed.This paper reviews the experimental and analytical work performed to data on spill of LNG.Specifically,experiments on the spill of LNG onshore,as well as experiments and numerical study on heavy gas dispersion.Pool boiling and turbulence model are described and discussed,as well as models used to predict dispersion.Although there have been significant progress in understanding the behavior of LNG spills,technical knowledge gaps to improve hazard prediction are still identified.Some of the gaps can be addressed with current modeling and testing capabilities.Finally,a discussion of the state of knowledge,and recommendations to further improvement the understanding of the behavior of LNG spills onshore.展开更多
Liquefaction is one of the most destructive phenomena caused by earthquakes,which has been studied in the issues of potential,triggering and hazard analysis.The strain energy approach is a common method to investigate...Liquefaction is one of the most destructive phenomena caused by earthquakes,which has been studied in the issues of potential,triggering and hazard analysis.The strain energy approach is a common method to investigate liquefaction potential.In this study,two Artificial Neural Network(ANN)models were developed to estimate the liquefaction resistance of sandy soil based on the capacity strain energy concept(W)by using laboratory test data.A large database was collected from the literature.One group of the dataset was utilized for validating the process in order to prevent overtraining the presented model.To investigate the complex influence of fine content(FC)on liquefaction resistance,according to previous studies,the second database was arranged by samples with FC of less than 28%and was used to train the second ANN model.Then,two presented ANN models in this study,in addition to four extra available models,were applied to an additional 20 new samples for comparing their results to show the capability and accuracy of the presented models herein.Furthermore,a parametric sensitivity analysis was performed through Monte Carlo Simulation(MCS)to evaluate the effects of parameters and their uncertainties on the liquefaction resistance of soils.According to the results,the developed models provide a higher accuracy prediction performance than the previously publishedmodels.The sensitivity analysis illustrated that the uncertainties of grading parameters significantly affect the liquefaction resistance of soils.展开更多
In order to obtain more accurate precipitation data and better simulate the precipitation on the Tibetan Plateau,the simulation capability of 14 Coupled Model Intercomparison Project Phase 6(CMIP6)models of historical...In order to obtain more accurate precipitation data and better simulate the precipitation on the Tibetan Plateau,the simulation capability of 14 Coupled Model Intercomparison Project Phase 6(CMIP6)models of historical precipitation(1982-2014)on the Qinghai-Tibetan Plateau was evaluated in this study.Results indicate that all models exhibit an overestimation of precipitation through the analysis of the Taylor index,temporal and spatial statistical parameters.To correct the overestimation,a fusion correction method combining the Backpropagation Neural Network Correction(BP)and Quantum Mapping(QM)correction,named BQ method,was proposed.With this method,the historical precipitation of each model was corrected in space and time,respectively.The correction results were then analyzed in time,space,and analysis of variance(ANOVA)with those corrected by the BP and QM methods,respectively.Finally,the fusion correction method results for each model were compared with the Climatic Research Unit(CRU)data for significance analysis to obtain the trends of precipitation increase and decrease for each model.The results show that the IPSL-CM6A-LR model is relatively good in simulating historical precipitation on the Qinghai-Tibetan Plateau(R=0.7,RSME=0.15)among the uncorrected data.In terms of time,the total precipitation corrected by the fusion method has the same interannual trend and the closest precipitation values to the CRU data;In terms of space,the annual average precipitation corrected by the fusion method has the smallest difference with the CRU data,and the total historical annual average precipitation is not significantly different from the CRU data,which is better than BP and QM.Therefore,the correction effect of the fusion method on the historical precipitation of each model is better than that of the QM and BP methods.The precipitation in the central and northeastern parts of the plateau shows a significant increasing trend.The correlation coefficients between monthly precipitation and site-detected precipitation for all models after BQ correction exceed 0.8.展开更多
This study numerically and experimentally investigates the effects of wave loads on a monopile-type offshore wind turbine placed on a 1:25 slope at different water depths as well as the effect of choosing different tu...This study numerically and experimentally investigates the effects of wave loads on a monopile-type offshore wind turbine placed on a 1:25 slope at different water depths as well as the effect of choosing different turbulence models on the efficiency of the numerical model.The numerical model adopts a two-phase flow by solving Unsteady Reynolds-Averaged Navier−Stokes(URANS)equations using the Volume Of Fluid(VOF)method and three differentk-ωturbulence models.Typical environmental conditions from the East China Sea are studied.The wave run-up and the wave loads applied on the monopile are investigated and compared with relevant experimental data as well as with mathematical predictions based on relevant theories.The numerical model is well validated against the experimental data at model scale.The use of different turbulence models results in different predictions on the wave height but less differences on the wave period.The baseline k-ωturbulence model and Shear-Stress Transport(SST)k-ωturbulence model exhibit better performance on the prediction of hydrodynamic load,at a model-scale water depth of 0.42 m,while the laminar model provides better results for large water depths.The SST turbulence model performs better in predicting wave run-up for water depth 0.42 m,while the laminar model and standard k-ωmodel perform better at water depth 0.52 m and 0.62 m,respectively.展开更多
As different power has its own receivers,this paper analyzes and designs a multiple-receiver wireless power transfer(WPT)system systematically.The equivalent circuit model of the system is established to analyze the k...As different power has its own receivers,this paper analyzes and designs a multiple-receiver wireless power transfer(WPT)system systematically.The equivalent circuit model of the system is established to analyze the key parameters including transmitter power,receiver power,transmission efficiency,and each receiver power allocation.A control circuit is proposed to achieve the maximum transmission efficiency and transmitter power control and arbitrary receiver power allocation ratios for different receivers.Through the proposed control circuit,receivers with different loads can allocate appropriate power according to its power demand,the transmitter power and system efficiency do not vary with the change of the number of receivers.Finally,this control circuit is validated using a 130-kHz WPT system with three receivers whose power received is 3:10:12,and the overall system efficiency can reach as high as 55.5%.展开更多
Fracture geometry is important when stimulating low-permeability reservoirs for natural gas or oil production. The geological layer(GL) properties and contrasts in in-situ stress are the two most important parameters ...Fracture geometry is important when stimulating low-permeability reservoirs for natural gas or oil production. The geological layer(GL) properties and contrasts in in-situ stress are the two most important parameters for determination of the vertical fracture growth extent and containment in layered rocks. However, the method for assessing the cumulative impact on growth in height remains ambiguous. In this research, a 3D model based on the cohesive zone method is used to simulate the evolution of hydraulic fracture(HF) height in layered reservoirs. The model incorporates fluid flow and elastic deformation, considering the friction between the contacting fracture surfaces and the interaction between fracture components. First, an analytical solution that was readily available was used to validate the model. Afterwards, a quantitative analysis was performed on the combined impacts of the layer interface strength, coefficient of interlayer stress difference, and coefficient of vertical stress difference.The results indicate that the observed fracture height geometries can be categorized into three distinct regions within the parametric space: blunted fracture, crossed fracture, and T-shaped fracture.Furthermore, the results explained the formation mechanism of the low fracture height in the deep shale reservoir of the Sichuan Basin, China, as well as the distinction between fracture network patterns in mid-depth and deep shale reservoirs.展开更多
Due to an increasing life expectancy and decreasing fertility rate,China officially entered a stage of increased ageing in 2011[1].According to China’s seventh national census,2019,the country’s overall population w...Due to an increasing life expectancy and decreasing fertility rate,China officially entered a stage of increased ageing in 2011[1].According to China’s seventh national census,2019,the country’s overall population was 1.44 billion,and this included eighteen per cent of people over 60(13.5%of people exceeding 65 years old).展开更多
More than 5000 landslides or potential landslides have been triggered in the Three Gorges Reservoir(TGR)area since the impoundment in 2003.This study aims at investigating the reservoirinduced landslides spatiotempora...More than 5000 landslides or potential landslides have been triggered in the Three Gorges Reservoir(TGR)area since the impoundment in 2003.This study aims at investigating the reservoirinduced landslides spatiotemporal and size distribution and its influence factors in the TGR by taking 790 landslides as statistical samples.The landslides exhibit significant regional and sub-regional spatial differences,and numerous landslides occurred at the initial three impoundment stages and the corresponding 2-3 cycles of reservoir operations followed,but the landslide frequency decreased dramatically after 2010 from temporal perspective.The relationship between landslide development and topographical,geological as well as hydrological factors were analyzed qualitatively.The reservoir-induced landslides in TGR area exhibit self-organized criticality and the rollover is nearly 2.5×10^(4) m^(2),which could not be attributed to the missing data but the coupled influences imposed by affecting factors.Both the double Pareto and inverse gamma functions are more suitable than the power-law function to present the landslide size characteristics.In term of the fitting precious,the adaptability of the inverse gamma function is better if the landslide inventories are limited.The research results provide foundation for the landslide susceptibility maps and hazard risk assessment.展开更多
China is experiencing rapid population aging.The one contributing factor affecting senior citizens’lives is the disconnect between the built environment in urban and rural areas and the behavioral preferences of olde...China is experiencing rapid population aging.The one contributing factor affecting senior citizens’lives is the disconnect between the built environment in urban and rural areas and the behavioral preferences of older adults.However,research on the relation between the built environment and the behavior of older individuals has been limited.Thus,this paper uses the most recent health tracking data on factors influencing aging in China released in 2020(China Senior Health Survey Tracking Survey).Applying traditional regression,least absolute shrinkage and selection operator regression,and two decision tree optimization models from machine learning,a comprehensive comparative study is carried out to investigate the correlation between the built environment and the physical activity,dietary habits,and social interactions of older age groups.The findings reveal that built environment variables most significantly impact physical activity,accounting for 52.525%,followed by social interaction behaviors at 50.202%and dietary intake at 47.991%.Furthermore,the authors identify population density and greenness rate as the built environment factors having considerable effects on the behavior of older adults.Thus,this study establishes a theoretical foundation for developing age-friendly community environments for older adults.展开更多
Traditional visual interpretation is often inefficient due to its excessively workload professional knowledge and strong subjectivity.Therefore,building an automatic interpretation model on high spatial resolution rem...Traditional visual interpretation is often inefficient due to its excessively workload professional knowledge and strong subjectivity.Therefore,building an automatic interpretation model on high spatial resolution remote sensing images is the key to the quick and efficient interpretation of earthquake-triggered landslides.Aiming at addressing this problem,a landslide interpretation model of high-resolution images based on bag of visual word(BoVW)feature was proposed.The high-resolution images were pre-processed,and then BoVW feature and support vector machine(SVM)was adopted to establish an automatic landslide interpretation model.This model was further compared with the currently widely used Histogram of Oriented Gradient(HoG)feature extraction model.In order to test the effectiveness of the method,typical landslide images were selected to construct a landslide sample library,which was subsequently utilized as the foundation for conducting an experimental study.The results show that the accuracy of landslide extraction using this method reaches as high as 89%,indicating that the method can be used for the automatic interpretation of landslides in disaster-prone areas,and has high practical value for regional disaster prevention and damage reduction.展开更多
Clarifying the system structure of various influencing factors is a crucial prerequisite for identifying the key action point to address the“Energy Trilemma”in China’s natural gas industry.Based on the three-dimens...Clarifying the system structure of various influencing factors is a crucial prerequisite for identifying the key action point to address the“Energy Trilemma”in China’s natural gas industry.Based on the three-dimensional system of“safety and stability-economic feasibility-low-carbon and environmental protection,”an influencing factor system for the“Energy Trilemma”in the natural gas industry is constructed.展开更多
基金supported by the National Natural Science Foundation of China(Nos.42171108 and 42101136)Sichuan Science and Technology Program(Nos.2024NSFSC2007 and2025YFHZ0273)Natural Science Starting Project of SWPU(No.2024QHZ029)。
文摘In cold regions,slope rocks are inevitably impacted by freeze-thaw,dry-wet cycles and their alternating actions,leading to strength weakening and pore degradation.In this study,the mechanical and microstructural properties of schist subjected to four conditions were investigated:freeze-thaw cycles in air(FTA),freeze-thaw cycles in water(FTW),dry-wet cycles(DW),and dry-wet-freeze-thaw cycles(DWFT).Uniaxial compressive strength(UCS),water absorption,ultrasonication,low-field nuclear magnetic resonance,and scanning electron microscopy analyses were conducted.The integrity attenuation characteristics of the longitudinal wave velocity,UCS,and elastic modulus were analyzed.The results showed that liquid water emerged as a critical factor in reducing the brittleness of schist.The attenuation function model accurately described the peak stress and static elastic modulus of schist in various media(R2>0.97).Different media affected the schist deterioration and half-life,with the FTW-immersed samples having a half-life of 28 cycles.Furthermore,the longitudinal wave velocity decreased as the number of cycles increased,with the FTW showing the most significant reduction and having the shortest half-life of 208 cycles.Moreover,the damage variables of compressive strength and elastic modulus increased with the number of cycles.After 40 cycles,the schist exposed to FTW exhibited the highest damage variables and saturated water content.
基金financially supported by The National Natural Science Foundation of China (42374004)the Open Fund of Hubei Luojia Laboratory (220100045)the Natural Science Foundation of Sichuan Province (2022NSFSC1047)。
文摘Since April 2002,the Gravity Recovery and Climate Experiment Satellite(GRACE)has provided monthly total water storage anomalies(TWSAs)on a global scale.However,these TWSAs are discontinuous because some GRACE observation data are missing.This study presents a combined machine learning-based modeling algorithm without hydrological model data.The TWSA time-series data for 11 large regions worldwide were divided into training and test sets.Autoregressive integrated moving average(ARIMA),long short-term memory(LSTM),and an ARIMA-LSTM combined model were used.The model predictions were compared with GRACE observations,and the model accuracy was evaluated using fi ve metrics:the Nash-Sutcliff e effi ciency coeffi cient(NSE),Pearson correlation coeffi cient(CC),root mean square error(RMSE),normalized RMSE(NRMSE),and mean absolute percentage error.The results show that at the basin scale,the mean CC,NSE,and NRMSE for the ARIMA-LSTM model were 0.93,0.83,and 0.12,respectively.At the grid scale,this study compared the spatial distribution and cumulative distribution function curves of the metrics in the Amazon and Volga River basins.The ARIMA-LSTM model had mean CC and NSE values of 0.89 and 0.61 and 0.92 and 0.61 in the Amazon and Volga River basins,respectively,which are superior to those of the ARIMA model(0.86 and 0.48 and 0.88 and 0.46,respectively)and the LSTM model(0.80 and 0.41 and 0.89 and 0.31,respectively).In the ARIMA-LSTM model,the proportions of grid cells with NSE>0.50 for the two basins were 63.3%and 80.8%,while they were 54.3%and 51.3%in the ARIMA model and 53.7%and 43.2%in the LSTM model.The ARIMA-LSTM model significantly improved the NSE values of the predictions while guaranteeing high CC values in the GRACE data reconstruction at both scales,which can aid in fi lling in discontinuous data in temporal gravity fi eld models..
基金supported by The National Natural Science Foundation of China(42374004).
文摘Spherical harmonic analysis(SHA)and synthesis(SHS)are widely used by researchers in various fields.Both numerical integration and least-squares methods can be employed for analysis and synthesis.However,these approaches,when calculated via summation,are computationally intensive.Although the Fast Fourier Transform(FFT)algorithm is efficient,it is traditionally limited to processing global grid points starting from zero longitude.In this paper,we derive an improved FFT algorithm for spherical harmonic analysis and synthesis.The proposed algorithm eliminates the need for grid points to start at zero longitude,thereby expanding the applicability of FFT-based methods.Numerical experiments demonstrate that the new algorithm retains the computational efficiency of conventional FFT while achieving accuracy comparable to the summation method.Consequently,it enables direct harmonic coefficient calculation from global grid data without requiring interpolation to align with zero longitude.Additionally,the algrithm can generate grid points with equi-angular spacing using the improved FFT algorithm,starting from non-zero longitudes.To address the loss of orthogonality in latitude due to discrete spherical grids,a quadrature weight factor-dependent on grid type(e.g.,regular or Gauss grid)-is incorporated,as summarized in this study.
基金National Key Research and Development Program,No.2021xjkk0303。
文摘Understanding the characteristics and driving factors behind changes in vegetation ecosystem resilience is crucial for mitigating both current and future impacts of climate change. Despite recent advances in resilience research, significant knowledge gaps remain regarding the drivers of resilience changes. In this study, we investigated the dynamics of ecosystem resilience across China and identified potential driving factors using the kernel normalized difference vegetation index(kNDVI) from 2000 to 2020. Our results indicate that vegetation resilience in China has exhibited an increasing trend over the past two decades, with a notable breakpoint occurring around 2012. We found that precipitation was the dominant driver of changes in ecosystem resilience, accounting for 35.82% of the variation across China, followed by monthly average maximum temperature(Tmax) and vapor pressure deficit(VPD), which explained 28.95% and 28.31% of the variation, respectively. Furthermore, we revealed that daytime and nighttime warming has asymmetric impacts on vegetation resilience, with temperature factors such as Tmin and Tmax becoming more influential, while the importance of precipitation slightly decreases after the resilience change point. Overall, our study highlights the key roles of water availability and temperature in shaping vegetation resilience and underscores the asymmetric effects of daytime and nighttime warming on ecosystem resilience.
基金supported by the China Postdoctoral Science Foundation(No.2024M752803)the National Natural Science Foundation of China(No.52179112)the Open Fund of National Key Laboratory of Oil and Gas Reservoir Geology and Exploitation(Southwest Petroleum University)(No.PLN2023-02)。
文摘Geological storage and utilization of CO_(2)involve complex interactions among Thermo-hydromechanical-chemical(THMC)coupling processes,which significantly affect storage integrity and efficiency.To address the challenges in accurately simulating these coupled phenomena,this paper systematically reviews recent advances in the mathematical modeling and numerical solution of THMC coupling in CO_(2)geological storage.The study focuses on the derivation and structure of governing and constitutive equations,the classification and comparative performance of fully coupled,iteratively coupled,and explicitly coupled solution methods,and the modeling of dynamic changes in porosity,permeability,and fracture evolution induced by multi-field interactions.Furthermore,the paper evaluates the capabilities,application scenarios,and limitations of major simulation platforms,including TOUGH,CMG-GEM,and COMSOL.By establishing a comparative framework integrating model formulations and solver strategies,this work clarifies the strengths and gaps of current approaches and contributes to the development of robust,scalable,and mechanism-oriented numerical models for long-term prediction of CO_(2)behavior in geological formations.
基金financial support provided by the Overseas Research Student (ORS) award scheme of the Vice-Chancellors committee of the United Kingdom's universities as well as the A.G. Leventis Foundation
文摘An analytical seismic fragility assessment framework is presented for the existing low strength reinforced concrete structures more common in the building stock of the developing countries.For realistic modelling of such substandard structures,low strength concrete stress-strain and bond-slip capacity models are included in calibrating material models.Key capacity parameters are generated stochastically to produce building population and cyclic pushover analysis is carried out to capture inelastic behaviour.Secant period values are evaluated corresponding to each displacement step on the capacity curves and used as seismic demand.A modified capacity demand diagram method is adopted for the degrading structures,which is further used to evaluate peak ground acceleration from back analysis considering each point on the capacity curve as performance point.For developing fragility curves,the mean values of peak ground acceleration are evaluated corresponding to each performance point on the series of capacity curves.A suitable probability distribution function is adopted for the secant period scatter at different mean peak ground acceleration values and probability of exceedance of limit states is evaluated.A suitable regression function is used for developing fragility curves and regression coefficients are proposed for different confidence levels.Fragility curves are presented for a low rise pre-seismic code reinforced concrete structure typical of developing countries.
基金funded by the key R&D project of the Sichuan Provincial Department of Science and Technology,“Research and Application of Key Technologies for Agricultural Drought Monitoring in Tibet Based on Multi-source Remote Sensing Data”(2021YFQ0042)Tibet Autonomous Region Science and Technology Support Plan Project“Construction and Demonstration Application of Ecological Environment Monitoring Technology System in Tibet Based on Three-Dimensional Remote Sensing Observation Network”(XZ201901-GA-07)。
文摘Protecting the ecological security of the Qinghai-Tibet Plateau(QTP)is of great importance for global ecology and climate.Over the past few decades,climate extremes have posed a significant challenge to the ecological environment of the QTP.However,there are few studies that explored the effects of climate extremes on ecological environment quality of the QTP,and few researchers have made quantitative analysis.Hereby,this paper proposed the Ecological Environmental Quality Index(EEQI)for analyzing the spatial and temporal variation of ecological environment quality on the QTP from 2000 to 2020,and explored the effects of climate extremes on EEQI based on Geographically and Temporally Weighted Regression(GTWR)model.The results showed that the ecological environment quality in QTP was poor in the west,but good in the east.Between 2000 and 2020,the area of EEQI variation was large(34.61%of the total area),but the intensity of EEQI variation was relatively low and occurred mainly by a slightly increasing level(EEQI change range of 0.05-0.1).The overall ecological environment quality of the QTP exhibited spatial and temporal fluctuations,which may be attributed to climate extremes.Significant spatial heterogeneity was observed in the effects of the climate extremes on ecological environment quality.Specifically,the effects of daily temperature range(DTR),number of frost days(FD0),maximum 5-day precipitation(RX5day),and moderate precipitation days(R10)on ecological environment quality were positive in most regions.Furthermore,there were significant temporal differences in the effects of consecutive dry days(CDD),consecutive wet days(CWD),R10,and FD0 on ecological environment quality.These differences may be attributed to variances in ecological environment quality,climate extremes,and vegetation types across different regions.In conclusion,the impact of climate extremes on ecological environment quality exhibits complex patterns.These findings will assist managers in identifying changes in the ecological environment quality of the QTP and addressing the effects of climate extremes.
基金funded by the National Natural Science Foundation of China(42471329,42101306,42301102)the Natural Science Foundation of Shandong Province(ZR2021MD047)+1 种基金the Scientific Innovation Project for Young Scientists in Shandong Provincial Universities(2022KJ224)the Gansu Youth Science and Technology Fund Program(24JRRA100).
文摘The ecological environment of the Yellow River Basin has become more fragile under the combined action of natural and manmade activities.However,the change mechanisms of ecological vulnerability in different sub-regions and periods vary,and the reasons for this variability are yet to be explained.Thus,in this study,we proposed a new remote sensing ecological vulnerability index by considering moisture,heat,greenness,dryness,land degradation,and social economy indicators and then analyzed and disclosed the spatial and temporal change patterns of ecological vulnerability of the Yellow River Basin,China from 2000 to 2022 and its driving mechanisms.The results showed that the newly proposed remote sensing ecological vulnerability index had a high accuracy,at 86.36%,which indicated a higher applicability in the Yellow River Basin.From 2000 to 2022,the average remote sensing ecological vulnerability index of the Yellow River Basin was 1.03,denoting moderate vulnerability level.The intensive vulnerability area was the most widely distributed,which was mostly located in the northern part of Shaanxi Province and the eastern part of Shanxi Province.From 2000 to 2022,the ecological vulnerability in the Yellow showed an overall stable trend,while that of the central and eastern regions showed an obvious trend of improvement.The gravity center of ecological vulnerability migrated southwest,indicating that the aggravation of ecological vulnerability in the southwestern regions was more severe than in the northeastern regions of the basin.The dominant single factor of changes in ecological vulnerability shifted from normalized difference vegetation index(NDVI)to temperature from 2000 to 2022,and the interaction factors shifted from temperature∩NDVI to temperature∩precipitation,which indicated that the global climate change exerted a more significant impact on regional ecosystems.The above results could provide decision support for the ecological protection and restoration of the Yellow River Basin.
基金funded by the key R&D project of Sichuan Provincial Department of Science and Technology,"Research and Application of Key Technologies for Agricultural Drought Monitoring in Tibet Based on Multi-source Remote Sensing Data"(2021YFQ0042)Tibet Autonomous Region Science and Technology Support Plan Project"Construction and Demonstration Application of Ecological Environment Monitoring Technology System in Tibet Based on Three-dimensional Remote Sensing Observation Network”(XZ201901-GA-07)。
文摘The occurrence of the Wenchuan earthquake caused the degradation of regional ecosystems,including vegetation destruction.However,the post-seismic vegetation recovery and its driving forces on the spatial-temporal scale are still vague,especially in the severely damaged areas(including Wenchuan,Beichuan,Mianzhu,Shifang,Qingchuan,Maoxian,Anzhou,Dujiangyan,Pingwu and Pengzhou).Here,we detected vegetation recovery in the severely damaged areas by using Ensemble Empirical Mode Decomposition(EEMD)to analyze the time series characteristics of the Enhanced Vegetation Index(EVI),and explored the driving effects of climate,land use types,nighttime light,water system,slope,and clay content on vegetation recovery based on Geographically and Temporally Weighted Regression(GTWR)model.The results indicated that the post-seismic vegetation recovery rate increased rapidly(acceleration>0)but slowed down after 2013.And the areas of best vegetation recovery(EVI increments>0.1)were distributed in the north of the study area,the Minjiang River Basin,and front fault and central fault of the Longmenshan Fault Zone.While the areas with the worst vegetation recovery(EVI increments<-0.1)were concentrated in the southern high-altitude areas and the Chengdu Plain.Additionally,a process attribution of the driving forces of vegetation recovery indicated that accumulated precipitation and maximum temperature promoted vegetation recovery(regression coefficients>0),but the impacts weakened after the earthquake,possibly due to the increase of secondary disasters induced by precipitation and the rise in maximum temperature.The impact of cultivated land on vegetation recovery was mostly positive(regression coefficients>0),which may be related to the implementation of the Grain for Green Project.The nighttime light inhibited vegetation recovery(regression coefficients<0),which could be closely associated with urbanization.The results indicated that more attention should be paid to the nonlinear variations of post-earthquake vegetation recovery trends,and the effects of climatic and anthropogenic factors on vegetation recovery also should not be underestimated.
基金This work is supported by Nanchong Science and Technology Bureau Project under Grant No.18SXHZ0021.
文摘Based on the analysis of the whole process of LNG spill on land,the research methods of LNG pool expansion and heavy gas diffusion are summarized and analyzed.This paper reviews the experimental and analytical work performed to data on spill of LNG.Specifically,experiments on the spill of LNG onshore,as well as experiments and numerical study on heavy gas dispersion.Pool boiling and turbulence model are described and discussed,as well as models used to predict dispersion.Although there have been significant progress in understanding the behavior of LNG spills,technical knowledge gaps to improve hazard prediction are still identified.Some of the gaps can be addressed with current modeling and testing capabilities.Finally,a discussion of the state of knowledge,and recommendations to further improvement the understanding of the behavior of LNG spills onshore.
基金supported by the Scientific Innovation Group for Youths of Sichuan Province under Grant No.2019JDTD0017。
文摘Liquefaction is one of the most destructive phenomena caused by earthquakes,which has been studied in the issues of potential,triggering and hazard analysis.The strain energy approach is a common method to investigate liquefaction potential.In this study,two Artificial Neural Network(ANN)models were developed to estimate the liquefaction resistance of sandy soil based on the capacity strain energy concept(W)by using laboratory test data.A large database was collected from the literature.One group of the dataset was utilized for validating the process in order to prevent overtraining the presented model.To investigate the complex influence of fine content(FC)on liquefaction resistance,according to previous studies,the second database was arranged by samples with FC of less than 28%and was used to train the second ANN model.Then,two presented ANN models in this study,in addition to four extra available models,were applied to an additional 20 new samples for comparing their results to show the capability and accuracy of the presented models herein.Furthermore,a parametric sensitivity analysis was performed through Monte Carlo Simulation(MCS)to evaluate the effects of parameters and their uncertainties on the liquefaction resistance of soils.According to the results,the developed models provide a higher accuracy prediction performance than the previously publishedmodels.The sensitivity analysis illustrated that the uncertainties of grading parameters significantly affect the liquefaction resistance of soils.
文摘In order to obtain more accurate precipitation data and better simulate the precipitation on the Tibetan Plateau,the simulation capability of 14 Coupled Model Intercomparison Project Phase 6(CMIP6)models of historical precipitation(1982-2014)on the Qinghai-Tibetan Plateau was evaluated in this study.Results indicate that all models exhibit an overestimation of precipitation through the analysis of the Taylor index,temporal and spatial statistical parameters.To correct the overestimation,a fusion correction method combining the Backpropagation Neural Network Correction(BP)and Quantum Mapping(QM)correction,named BQ method,was proposed.With this method,the historical precipitation of each model was corrected in space and time,respectively.The correction results were then analyzed in time,space,and analysis of variance(ANOVA)with those corrected by the BP and QM methods,respectively.Finally,the fusion correction method results for each model were compared with the Climatic Research Unit(CRU)data for significance analysis to obtain the trends of precipitation increase and decrease for each model.The results show that the IPSL-CM6A-LR model is relatively good in simulating historical precipitation on the Qinghai-Tibetan Plateau(R=0.7,RSME=0.15)among the uncorrected data.In terms of time,the total precipitation corrected by the fusion method has the same interannual trend and the closest precipitation values to the CRU data;In terms of space,the annual average precipitation corrected by the fusion method has the smallest difference with the CRU data,and the total historical annual average precipitation is not significantly different from the CRU data,which is better than BP and QM.Therefore,the correction effect of the fusion method on the historical precipitation of each model is better than that of the QM and BP methods.The precipitation in the central and northeastern parts of the plateau shows a significant increasing trend.The correlation coefficients between monthly precipitation and site-detected precipitation for all models after BQ correction exceed 0.8.
基金the National Natural Science Foundation of China(Grant Nos.52071058 and 51939002)Liaoning Revitalization Talents Program(Grant No,XLYC1807208)the Special Funds for Promoting High Quality Development from Department of Natural Resources of Guangdong Province(Grant No.GDNRC[2020]015).
文摘This study numerically and experimentally investigates the effects of wave loads on a monopile-type offshore wind turbine placed on a 1:25 slope at different water depths as well as the effect of choosing different turbulence models on the efficiency of the numerical model.The numerical model adopts a two-phase flow by solving Unsteady Reynolds-Averaged Navier−Stokes(URANS)equations using the Volume Of Fluid(VOF)method and three differentk-ωturbulence models.Typical environmental conditions from the East China Sea are studied.The wave run-up and the wave loads applied on the monopile are investigated and compared with relevant experimental data as well as with mathematical predictions based on relevant theories.The numerical model is well validated against the experimental data at model scale.The use of different turbulence models results in different predictions on the wave height but less differences on the wave period.The baseline k-ωturbulence model and Shear-Stress Transport(SST)k-ωturbulence model exhibit better performance on the prediction of hydrodynamic load,at a model-scale water depth of 0.42 m,while the laminar model provides better results for large water depths.The SST turbulence model performs better in predicting wave run-up for water depth 0.42 m,while the laminar model and standard k-ωmodel perform better at water depth 0.52 m and 0.62 m,respectively.
基金supported by the National Natural Science Foundation of China under Grant No.51574198Nanchong City 2018 Special Fund for City-School Cooperation under Grant No.18SXHZ0021
文摘As different power has its own receivers,this paper analyzes and designs a multiple-receiver wireless power transfer(WPT)system systematically.The equivalent circuit model of the system is established to analyze the key parameters including transmitter power,receiver power,transmission efficiency,and each receiver power allocation.A control circuit is proposed to achieve the maximum transmission efficiency and transmitter power control and arbitrary receiver power allocation ratios for different receivers.Through the proposed control circuit,receivers with different loads can allocate appropriate power according to its power demand,the transmitter power and system efficiency do not vary with the change of the number of receivers.Finally,this control circuit is validated using a 130-kHz WPT system with three receivers whose power received is 3:10:12,and the overall system efficiency can reach as high as 55.5%.
基金the funding provided by the National Natural Science Foundation of China (No. 52334001, No. 42372337)National Key Research and Development Program of China (No. SQ2023YFE0100562)+1 种基金CPET Industrialization Fund Project (No. CPETCY202417)Natural Science Starting Project of SWPU (No. 2022QHZ009)。
文摘Fracture geometry is important when stimulating low-permeability reservoirs for natural gas or oil production. The geological layer(GL) properties and contrasts in in-situ stress are the two most important parameters for determination of the vertical fracture growth extent and containment in layered rocks. However, the method for assessing the cumulative impact on growth in height remains ambiguous. In this research, a 3D model based on the cohesive zone method is used to simulate the evolution of hydraulic fracture(HF) height in layered reservoirs. The model incorporates fluid flow and elastic deformation, considering the friction between the contacting fracture surfaces and the interaction between fracture components. First, an analytical solution that was readily available was used to validate the model. Afterwards, a quantitative analysis was performed on the combined impacts of the layer interface strength, coefficient of interlayer stress difference, and coefficient of vertical stress difference.The results indicate that the observed fracture height geometries can be categorized into three distinct regions within the parametric space: blunted fracture, crossed fracture, and T-shaped fracture.Furthermore, the results explained the formation mechanism of the low fracture height in the deep shale reservoir of the Sichuan Basin, China, as well as the distinction between fracture network patterns in mid-depth and deep shale reservoirs.
基金support by Chengdu Green and Low-carbon Development Research Base[No.LD23YB05]
文摘Due to an increasing life expectancy and decreasing fertility rate,China officially entered a stage of increased ageing in 2011[1].According to China’s seventh national census,2019,the country’s overall population was 1.44 billion,and this included eighteen per cent of people over 60(13.5%of people exceeding 65 years old).
基金supported by the National Natural Science Foundation of China(Nos.42277187,42407279)the United Key Program of the National Natural Sciences Foundation of China(No.U23A202579)+4 种基金Hebei Provincial Natural Science Foundation(No.D2021202002)Hunan Provincial Natural Science Foundation(No.2022JJ40521)Changsha Municipal Natural Science Foundation(No.kq2202065)the Open Research Fund Program of Hunan Provincial Key Laboratory for Big Data Smart Application of Natural Disaster Risks Survey of Highway Engineering(No.BNH2024KFB04)the Conselleria de Innovación,Universidades,Ciencia y Sociedad Digital(No.CIAICO/2021/335)to Roberto Tomás。
文摘More than 5000 landslides or potential landslides have been triggered in the Three Gorges Reservoir(TGR)area since the impoundment in 2003.This study aims at investigating the reservoirinduced landslides spatiotemporal and size distribution and its influence factors in the TGR by taking 790 landslides as statistical samples.The landslides exhibit significant regional and sub-regional spatial differences,and numerous landslides occurred at the initial three impoundment stages and the corresponding 2-3 cycles of reservoir operations followed,but the landslide frequency decreased dramatically after 2010 from temporal perspective.The relationship between landslide development and topographical,geological as well as hydrological factors were analyzed qualitatively.The reservoir-induced landslides in TGR area exhibit self-organized criticality and the rollover is nearly 2.5×10^(4) m^(2),which could not be attributed to the missing data but the coupled influences imposed by affecting factors.Both the double Pareto and inverse gamma functions are more suitable than the power-law function to present the landslide size characteristics.In term of the fitting precious,the adaptability of the inverse gamma function is better if the landslide inventories are limited.The research results provide foundation for the landslide susceptibility maps and hazard risk assessment.
基金supported by the Special Funds for Cultivation of Guangdong College Students’Scientific and Technological Innovation(“Climbing Program”Special Funds)[Grant No.pdjh2024a053]National Innovation and Entrepreneurship Training Program for Undergraduate[Grant No.S202310559083].
文摘China is experiencing rapid population aging.The one contributing factor affecting senior citizens’lives is the disconnect between the built environment in urban and rural areas and the behavioral preferences of older adults.However,research on the relation between the built environment and the behavior of older individuals has been limited.Thus,this paper uses the most recent health tracking data on factors influencing aging in China released in 2020(China Senior Health Survey Tracking Survey).Applying traditional regression,least absolute shrinkage and selection operator regression,and two decision tree optimization models from machine learning,a comprehensive comparative study is carried out to investigate the correlation between the built environment and the physical activity,dietary habits,and social interactions of older age groups.The findings reveal that built environment variables most significantly impact physical activity,accounting for 52.525%,followed by social interaction behaviors at 50.202%and dietary intake at 47.991%.Furthermore,the authors identify population density and greenness rate as the built environment factors having considerable effects on the behavior of older adults.Thus,this study establishes a theoretical foundation for developing age-friendly community environments for older adults.
基金the National Key R&D Program of China(2019YFC1510700)the Sichuan Science and Technology Program(2022YFS0539)the Geomatics Technology and Application Key Laboratory of Qinghai Province,China(QHDX-2018-07).
文摘Traditional visual interpretation is often inefficient due to its excessively workload professional knowledge and strong subjectivity.Therefore,building an automatic interpretation model on high spatial resolution remote sensing images is the key to the quick and efficient interpretation of earthquake-triggered landslides.Aiming at addressing this problem,a landslide interpretation model of high-resolution images based on bag of visual word(BoVW)feature was proposed.The high-resolution images were pre-processed,and then BoVW feature and support vector machine(SVM)was adopted to establish an automatic landslide interpretation model.This model was further compared with the currently widely used Histogram of Oriented Gradient(HoG)feature extraction model.In order to test the effectiveness of the method,typical landslide images were selected to construct a landslide sample library,which was subsequently utilized as the foundation for conducting an experimental study.The results show that the accuracy of landslide extraction using this method reaches as high as 89%,indicating that the method can be used for the automatic interpretation of landslides in disaster-prone areas,and has high practical value for regional disaster prevention and damage reduction.
基金Western Project of the National Social Science Fund of China (22XGL019)Major Project of the National Social Science Fund of China (22&ZD105)+1 种基金Special Academic Research Grant at the Key Research Base of Philosophy and Social Sciences in Sichuan Province (SC24E091)Chengdu Philosophy and Social Science Planning Project 2024 (2024BS072)。
文摘Clarifying the system structure of various influencing factors is a crucial prerequisite for identifying the key action point to address the“Energy Trilemma”in China’s natural gas industry.Based on the three-dimensional system of“safety and stability-economic feasibility-low-carbon and environmental protection,”an influencing factor system for the“Energy Trilemma”in the natural gas industry is constructed.
