The remaining useful life prediction of rolling bearing is vital in safety and reliability guarantee.In engineering scenarios,only a small amount of bearing performance degradation data can be obtained through acceler...The remaining useful life prediction of rolling bearing is vital in safety and reliability guarantee.In engineering scenarios,only a small amount of bearing performance degradation data can be obtained through accelerated life testing.In the absence of lifetime data,the hidden long-term correlation between performance degradation data is challenging to mine effectively,which is the main factor that restricts the prediction precision and engineering application of the residual life prediction method.To address this problem,a novel method based on the multi-layer perception neural network and bidirectional long short-term memory network is proposed.Firstly,a nonlinear health indicator(HI)calculation method based on kernel principal component analysis(KPCA)and exponential weighted moving average(EWMA)is designed.Then,using the raw vibration data and HI,a multi-layer perceptron(MLP)neural network is trained to further calculate the HI of the online bearing in real time.Furthermore,The bidirectional long short-term memory model(BiLSTM)optimized by particle swarm optimization(PSO)is used to mine the time series features of HI and predict the remaining service life.Performance verification experiments and comparative experiments are carried out on the XJTU-SY bearing open dataset.The research results indicate that this method has an excellent ability to predict future HI and remaining life.展开更多
Accurate prediction of remaining useful life serves as a reliable basis for maintenance strategies,effectively reducing both the frequency of failures and associated costs.As a core component of PHM,RUL prediction pla...Accurate prediction of remaining useful life serves as a reliable basis for maintenance strategies,effectively reducing both the frequency of failures and associated costs.As a core component of PHM,RUL prediction plays a crucial role in preventing equipment failures and optimizing maintenance decision-making.However,deep learning models often falter when processing raw,noisy temporal signals,fail to quantify prediction uncertainty,and face challenges in effectively capturing the nonlinear dynamics of equipment degradation.To address these issues,this study proposes a novel deep learning framework.First,a newbidirectional long short-termmemory network integrated with an attention mechanism is designed to enhance temporal feature extraction with improved noise robustness.Second,a probabilistic prediction framework based on kernel density estimation is constructed,incorporating residual connections and stochastic regularization to achieve precise RUL estimation.Finally,extensive experiments on the C-MAPSS dataset demonstrate that our method achieves competitive performance in terms of RMSE and Score metrics compared to state-of-the-artmodels.More importantly,the probabilistic output provides a quantifiablemeasure of prediction confidence,which is crucial for risk-informed maintenance planning,enabling managers to optimize maintenance strategies based on a quantifiable understanding of failure risk.展开更多
The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,th...The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,this study proposes an intelligent decision-making framework based on a deep long short-term memory Q-network.This framework transforms the real-time sequencing for bolter recovery problem into a partially observable Markov decision process.It employs a stacked long shortterm memory network to accurately capture the long-range temporal dependencies of bolter event chains and fuel consumption.Furthermore,it integrates a prioritized experience replay training mechanism to construct a safe and adaptive scheduling system capable of millisecond-level real-time decision-making.Experimental demonstrates that,within large-scale mass recovery scenarios,the framework achieves zero safety violations in static environments and maintains a fuel safety violation rate below 10%in dynamic scenarios,with single-step decision times at the millisecond level.The model exhibits strong generalization capability,effectively responding to unforeseen emergent situations—such as multiple bolters and fuel emergencies—without requiring retraining.This provides robust support for efficient carrier-based aircraft recovery operations.展开更多
In China,farmers have increasingly adopted direct-seeded rice(DSR).While various impacts of DSR have been studied,limited evidence exists regarding the effect of DSR adoption on pesticide use.This study examines the i...In China,farmers have increasingly adopted direct-seeded rice(DSR).While various impacts of DSR have been studied,limited evidence exists regarding the effect of DSR adoption on pesticide use.This study examines the impact of DSR adoption on pesticide use utilizing data from a 2018 survey of 982 rice farmers in China's Yangtze River Basin.The endogenous treatment-regression and switching regression models are employed to address self-selection bias.The results indicate that,after accounting for self-selection,DSR adopters spend 401.72 CNY ha^(-1) more on pesticides compared to non-adopters.Although DSR adoption significantly increases the use of insecticides,fungicides and herbicides,its impact is most pronounced for insecticide expenditure and least pronounced for herbicide expenditure.The findings remain robust when altering the dependent variable,truncating the research sample,and modifying the estimation method.Heterogeneous analysis reveals that DSR adoption has a stronger positive impact on pesticide expenditure among farmers below 60 years of age,with at least 6 years of education,and managing rice sown areas less than 2 ha.Based on these findings,this study recommends enhancing complementary techniques for DSR,improving the dissemination of DSR cultivation technologies,and strengthening socialized services.This research provides a comprehensive assessment of DSR's advantages and disadvantages,particularly regarding pesticide use,offering important policy implications for pesticide reduction.展开更多
Background:Music has proven to be vital in enhancing resilience and promotingwell-being.Previously,the impact of music in sports environments was solely investigated,while this paper applies it to study environments,s...Background:Music has proven to be vital in enhancing resilience and promotingwell-being.Previously,the impact of music in sports environments was solely investigated,while this paper applies it to study environments,standing out as pioneering research.The study consists of a systematic development of a conceptual framework based on theories of Uses and Gratification Expectancy(UGE)and perceived motivation based on music elements.Their components are observed variables influencing students’psychological well-being(as the dependent variable).Resilience is examined as a mediator,influencing the relationships of both observed and dependent variables.The main purpose of this study is to highlight the positive effects of online music consumption on the psychological well-being of students.Methods:Semi-structured qualitative interviews were conducted with eighteen final year creative multimedia undergraduate students belonging to five central region Malaysian universities,especially on their UGE needs,and a similar concept survey instrument with two hundred participants.The interview data were analysed through thematic analysis,while the survey data through descriptive and Partial Least Squares Structural Equation Modeling(PLS-SEM).Results:The results highlight that students gain motivation from online music,which positively affects their psychological well-being(β=0.190,p=0.003,f^(2)=0.037),while resilience significantly affects this relationship(β=0.562,p<0.001,f^(2)=0.461).However,the results also predict a partial relationship between constructs based on UGE with psychological well-being,mediated by resilience,i.e.,AT-UGE(β=0.021,p=0.783,f^(2)=0.000),SIPI-UGE(β=0.228,p=0.004,f^(2)=0.044).Conclusion:The outcome of the study reflected practical,meaningful,and statistically significant results.The majority of the predictors,with the exception of one,i.e.,AT-UGE,displayed a clear positive relation of online music consumption on the Psychological Well-being of students.Future research will explore varying contextual factors impacting online music-related gratifications,motivations,and resilience,along with additional potential mediators and moderators.展开更多
Under complex working conditions,accurate prediction of the remaining useful life(RUL)of lithium-ion batteries is of great significance to ensure the stable operation of energy storage systems,the safe driving of elec...Under complex working conditions,accurate prediction of the remaining useful life(RUL)of lithium-ion batteries is of great significance to ensure the stable operation of energy storage systems,the safe driving of electric vehicles,and the continuous power supply of electronic devices.This paper systematically describes the RUL prediction methods of lithium-ion batteries and comprehensively summarizes the development status and future trends in this field.First,the battery degradation mechanisms and lightweight data acquisition are analyzed.Secondly,a systematic classification model is constructed for the more widely used lithium battery RUL prediction methods,and the application characteristics and implementation limitations of different methods are analyzed in detail.An innovative classification framework for hybrid methods is proposed based on the depth of physical-data interaction.Then,collaborative modelling of calendar ageing and cyclic ageing is discussed,revealing their coupled effects and corresponding RUL prediction methods.Finally,the technical bottlenecks faced by the current RUL prediction of lithium batteries are identified,potential solutions are proposed,and the future development trends are outlined.展开更多
As a tropical island confronting the dual imperatives of tourism-driven economic growth and ecological vulnerability,Hainan's land-use sustainability critically impacts both regional development and coastal ecosys...As a tropical island confronting the dual imperatives of tourism-driven economic growth and ecological vulnerability,Hainan's land-use sustainability critically impacts both regional development and coastal ecosystem security.This study employs a coupled PLUS-InVEST modeling framework to analyze land-use changes and habitat quality dynamics from 2000 to 2020,projecting ecological outcomes under three development scenarios for 2030.Key findings reveal:(1)A persistent bimodal habitat distribution pattern,with high-quality areas concentrated in the central forest zone and degraded areas in coastal peripheries,exhibiting a continuous decline over the 20-year period.(2)Accelerated urbanization between 2010 and 2020 resulted in the conversion of ecological land to construction use,correlating strongly with habitat fragmentation intensity.(3)Baseline projections for 2030 indicate that construction land will dominate new conversions.(4)Ecological protection scenarios demonstrate recoverable habitat potentials,particularly within coastal buffer zones.These findings provide empirical validation of scenario-driven land-use planning as a viable tool for island ecosystems,highlighting the critical need to balance tourism infrastructure development with coastal conservation imperatives in tropical island sustainability management.This methodology advances spatial decision-making for balancing island economic growth with biodiversity preservation,offering replicable strategies for global island ecosystems facing similar sustainability challenges.展开更多
Soil organic carbon(SOC)dynamics significantly influence ecosystem carbon source-sink balance,particularly in agroecosystems.However,uncertainty remains regarding optimal land use types for maximizing farmland carbon ...Soil organic carbon(SOC)dynamics significantly influence ecosystem carbon source-sink balance,particularly in agroecosystems.However,uncertainty remains regarding optimal land use types for maximizing farmland carbon storage across different soil types,and identifying effective land management practices for enhanced carbon accumulation is essential for reducing agricultural emissions and strengthening carbon sinks.This study examined SOC variations in eastern Yunnan’s subtropical highlands(2,132 sites),analyzing topsoil(0–20 cm)across five land uses(dryland,irrigated land,forestland,grassland and plantation)of five soil types(red,yellow,yellowbrown,brown,purple).The investigation explored relationships between SOC and edaphic factors(26 elements)to determine SOC influencing factors.The study area demonstrated a mean SOC content of 27.78 g kg^(–1),with distinct spatial heterogeneity characterized by lower values in the southwestern sector and higher concentrations in the northeastern region.Brown soils displayed the highest SOC content(P<0.05),followed by yellow-brown then red,yellow,and purple soils.Irrigation significantly enhanced SOC storage,particularly in brown soils where irrigated land contained 2.2-,2.4-,and 1.6-times higher SOC than forestland,grassland,and dryland,respectively.Similar irrigation benefits occurred in purple,yellow,and yellow-brown soils,indicating moisture limitation as the primary SOC constraint.Notably,SOC exhibited strong positive correlations with nitrogen,sulfur,and selenium.Nitrogen fertilization demonstrated dual benefits:enhancing SOC sequestration and promoting Se enrichment in crops,potentially supporting specialty agriculture.Although land use impacts on SOC varied across soil types(P>0.05),irrigation consistently emerged as the optimal management for carbon sink enhancement.These findings suggest that targeted water management could effectively reduce farmland carbon emissions in moisture-limited subtropical highlands.Strategic nitrogen application offers co-benefits for soil fertility and selenium biofortification,providing practical pathways for climate-smart agriculture in similar ecoregions.展开更多
Insight into the carbon turnover in soil aggregates and density fractions is essential for reducing the uncertainty in estimating carbon pools on the Tibetan Plateau,and how they vary with land use type is unclear.In ...Insight into the carbon turnover in soil aggregates and density fractions is essential for reducing the uncertainty in estimating carbon pools on the Tibetan Plateau,and how they vary with land use type is unclear.In this study,the effect of land use type on carbon storage and fractionation was quantified based on organic carbon and its ^(13)C abundance at the microscale of soil aggregates and density fractions in Tibetan alpine ecosystems.The sequence of soil aggregate destruction in the land use types of plantation(13.1%)<shrubland(32.7%)<grassland(47.9%)<farmland(61.8%)shows that plantations strengthen the soil structure.Plantation land had a greater contribution of light fraction organic carbon(28.3%)but a lower contribution of mineral-associated organic carbon(40.6%)to the carbon stock compared to farmland(13.5 and 70.3%).Interestingly,plantation land enhanced the aggregational differentiation of organic carbon and ^(13)C in each density fraction,whereas no such phenomenon existed in the soil organic carbon.Carbon isotope analyses revealed that carbon transfer in the plantation land occurred from the light fraction in macroaggregates(–24.9‰)to the mineral-associated fraction in microaggregates(–19.9‰).When compared to the other three land use types,the low transferability of carbon in aggregates and density fractions in plantation land provides a stable carbon pool for the Tibetan Plateau.This study shows that plantations can mitigate global climate change by slowing carbon transfer and increasing carbon storage at the microscale of aggregates and density fractions in alpine regions.展开更多
Land use in arid and semi-arid regions has a substantial effect on climate,environment,and biodiversity,thereby projecting the spatiotemporal changes in land use and the subsequent effects.This study employed the loca...Land use in arid and semi-arid regions has a substantial effect on climate,environment,and biodiversity,thereby projecting the spatiotemporal changes in land use and the subsequent effects.This study employed the locally calibrated Future Land Use Simulation(FLUS)model,which coupled system dynamics with cellular automata and integrated an artificial neural network algorithm and a roulette wheel selection mechanism.We projected future land use(2020–2100)dynamics of Lanzhou,a typical river valley city in Northwest China,under three different Shared Socioeconomic Pathway(SSP)scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5).The simulation results were validated and subsequently reclassified using the International Geosphere Biosphere Programme(IGBP)system to produce a dataset suitable for driving climatic and environmental models.Under the SSP1-2.6 scenario,urban and built-up land expanded consistently,whereas irrigated cropland and pasture as well as grassland contracted continuously.Conversely,the SSP5-8.5 scenario was characterized by a contraction of urban and built-up land,and relative stability of irrigated cropland and pasture as well as grassland.The SSP2-4.5 scenario presented a more complex trade-off,where urban and built-up land and grassland increased first and then decreased,whereas irrigated cropland and pasture followed an opposite trajectory.A significant inverse relationship between urban and built-up land and irrigated cropland and pasture was observed under all scenarios,underscoring the fundamental spatial competition that prevailed in this land-constrained valley city.Furthermore,the negative correlation of grassland with urban and built-up land,coupled with the positive correlation of grassland with irrigated cropland and pasture under both the SSP1-2.6 and SSP5-8.5 scenarios,indicated an evolution from broad confrontation to intricate internal trade-offs within the urban–agricultural–ecological system.This study underscored the critical influence of regional topographic and hydrological constraints on land-use evolution in arid regions,providing guidance for water resource management and ecosystem protection in Lanzhou,with applications for sustainable land-use planning in other arid and semi-arid river valley cities.展开更多
As the global leader in rice production,China's paddy fields contribute substantially to greenhouse gas emissions through methane(CH_(4))and nitrous oxide(N_(2)O)releases.Aromatic rice cultivation practices have b...As the global leader in rice production,China's paddy fields contribute substantially to greenhouse gas emissions through methane(CH_(4))and nitrous oxide(N_(2)O)releases.Aromatic rice cultivation practices have been optimized to enhance the aroma,so the relationship between its cultivation and greenhouse gas emissions from paddy fields is unclear.To investigate how aroma-enhancing cultivation practices drive microbial community dynamics in aromatic rice paddies and their implications for greenhouse gas emissions,a two-year experiment in five ecological locations(Xingning,Nanxiong,Conghua,Luoding,and Zengcheng)compared two farming practices:partial organic substitution for inorganic fertilizers combined with water-saving irrigation(IOF+W)and traditional cultivation(CK).The CH_(4)and N_(2)O emissions,soil microbial composition and function,global warming potential(GWP),nitrogen use efficiency,yield,and the content of 2-acetyl-1-pyrroline(2-AP)were measured and analyzed.The main purpose was to investigate the impact of IOF+W on CH_(4)and N_(2)O emissions and their relationship with soil microorganisms.The results showed that IOF+W significantly reduced CH_(4)emission fluxes and totals(36.95%)and GWP(31.29%),while significantly increasing N_(2)O emission fluxes and totals(14.82%).The soil microbial community structure was reshaped by the IOF+W treatment,which suppressed methanogens but enhanced the abundances of nitrifying and denitrifying bacteria.Key enzymatic activities involved in CH_(4)production,such as methyl-coenzyme M reductase,formylmethanofuran dehydrogenase,and methyltransferase,decreased.In contrast,the activity of the key CH_(4)-oxidizing enzyme methanol dehydrogenase increased.This shift led to an overall attenuation of the CH_(4)production metabolism while enhancing the CH_(4)oxidation metabolism.In addition,the activities of pivotal enzymes involved in denitrification and nitrification were improved,thus enhancing nitrogen nitrification and denitrification metabolism.Moreover,the IOF+W treatment significantly increased nitrogen use efficiency(47.83%),yield(14.77%),and 2-AP content(13.78%).Therefore,the IOF+W treatment demonstrated good efficacy as a sustainable strategy for achieving productive,green,resource-efficient,and premium-quality aromatic rice cultivation in South China.展开更多
The Guangdong,Jiangxi and Fujian(GJF)provinces,located in the subtropical region of southeastern China,is one of the national key regions for soil erosion control and ecological restoration.This region is characterize...The Guangdong,Jiangxi and Fujian(GJF)provinces,located in the subtropical region of southeastern China,is one of the national key regions for soil erosion control and ecological restoration.This region is characterized by extensive red soil development and high rainfall erosivity,making it a representative landscape for exploring the interactions between land use change(LUC)and ecosystem services(ES).Despite the recognized importance of ES in hilly regions,comprehensive assessing the impacts of LUC on ES remain limited.This study investigates five key ES:water yield,soil conservation,carbon conservation,food supply,and habitat quality in GJF region from 2000 to 2020.By applying the InVEST model and the Geodetector method,we assessed the trade-offs,synergies,and transitions among ES,identified the natural and social drivers of ES dynamics,and quantified the contribution of LUC to ES changes using the ecosystem service contribution index.The results showed that cropland and woodland were the dominant land use types.Ecological restoration efforts positively influenced ES,with synergies intensifying and trade-offs diminishing over time.Land use conversions,particularly among woodland,grassland,and cropland,exerted significant impacts on ES.In particular,the conversion of woodland to other land uses had markedly negative effects on soil conservation,carbon conservation,and habitat quality.Forest cover was identified as a major driver of ES dynamics.These findings highlight the importance of maintaining and expanding forest and grassland cover,strengthening red soil conservation,and optimizing land use structure to achieve coordinated ecological protection and socioeconomic development in the subtropical hilly regions of southern China.展开更多
Against the background of rapid urbanization and the“Dual Carbon”goals,analyzing the impact mechanisms of land use change on carbon metabolism is crucial for regional sustainable development.Taking the Guangdong-Hon...Against the background of rapid urbanization and the“Dual Carbon”goals,analyzing the impact mechanisms of land use change on carbon metabolism is crucial for regional sustainable development.Taking the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)as the study area,we integrate energy consumption data and the Forest Carbon Sequestration(FCS)model to clarify the land use carbon metabolism status based on Ecological Network Analysis(ENA),and systematically analyze the spatiotemporal evolution patterns of urban land use carbon metabolism,interactions between land types,as well as its driving mechanisms in the GBA from 2000 to 2023.The results show that:(1)Over the past two decades,land use changes have exhibited a significant characteristic of“natural land retreat and construction land expansion”,with areas of cropland,forest,and waterbody shrank by 16%,4%,and 4% respectively,while urban land and industrial land increased by 50%and 438%respectively;76% of the reclaimed land was transferred to construction land.(2)The imbalance of carbon metabolism was jointly affected by land use patterns and land use change processes:carbon emissions from energy consumption surged by 116%,while land carbon sequestration capacity decreased by 12%;in most periods,the negative carbon flow from land use change exceeded positive flows,with both showing sharp fluctuations.(3)Construction land in various cities dominated the carbon flow network through control or exploitation relationships,and the mutual transfer between industrial land and cropland is the primary driver;ecological land protection policies(e.g.,the forest“in-out balance”scheme)effectively reduced the intensity of competition relationship.(4)The push-pull forces of land types demonstrate the dual effect of industrialization and urbanization,but their contribution has gradually weakened as the speed of urbanization declined in various cities;the proportion of the indirect carbon flow reached a maximum of 37%(2005-2010),indicating that the indirect impact of land use change cannot be ignored.This study deepens the understanding of the land-carbon interactions,reveals the implicit effects of the“policy implementation-land use change-carbon flow generation”transmission chain,and proposes a“construction land-cropland-ecological land”constraint system and a synergistic path of industrial land intensification and inefficient land ecological restoration.It provides methodological support for low-carbon governance at the urban agglomeration scale.展开更多
Residential energy-use behavior and energy-saving awareness play a crucial role in sustainable urban energy planning and building energy efficiency,particularly under the pressures of climate change.However,existing s...Residential energy-use behavior and energy-saving awareness play a crucial role in sustainable urban energy planning and building energy efficiency,particularly under the pressures of climate change.However,existing studies often lack comparative analysis of urban-rural differences and tend to focus excessively on behavior patterns while neglecting the dimension of energysaving awareness.With China’s urbanization rate reaching 66.16%,understanding such regional disparities has become increasingly important.To address these research gaps,this study conducts a large-scale survey on space cooling behaviors among residents in Beijing,a representative Chinese megacity.It should be noted that living standards in such megacities are generally higher than the national average,which may shape distinctive energy-use profiles.Analyzing 1573valid samples(1064 urban/442 rural)in 2024,this study employed K-Prototypes and K-Modes clustering to identify typical cooling behavior and energy-saving awareness pattems,followed by Kendall/Chi-square correlation tests and XGBoost importance analysis to determine key influencing factors,with subsequent urban-rural comparative analysis.Results indicate that urban residents are primarily heat-sensitive or heat-tolerant,with a secondary patten of mid-low temperature preference,and generally exhibit long cooling durations;rural behavior is dominated by heat-tolerant type,followed by heat-sensitive,mid-low temperature preference,and never-on types as secondary patterns;both urban and rural areas exhibit energy-savingawareness characterized by low consumption-lowwillingness,though urban areas show marginally higher motivation;energy-saving awareness correlates with cooling behavior in rural areas,but this relationship weakens significantly in urban contexts.展开更多
Systematically analyzing the impact mechanisms of policy on Land Use Conflict(LUC)is crucial for constructing effective conflict mitigation strategies.However,previous research on how policy influences LUC remains rel...Systematically analyzing the impact mechanisms of policy on Land Use Conflict(LUC)is crucial for constructing effective conflict mitigation strategies.However,previous research on how policy influences LUC remains relatively limited.Focusing on the indirect driving role of policy on LUC,this study proposed County Development Level(CDL)under Major Function Oriented Zone Planning(MFOZP)guidance as an intermediary variable,bridging the implicit influence of MFOZP and the explicit changes in LUC.Using the Beijing-Tianjin-Hebei(BTH)region in China as a case study,we analyzed the spatio-temporal evolution characteristics of LUC and CDL for the periods 2000-2010 and 2010-2020,before and after MFOZP implementation.Panel models and Geographically Weighted Regression(GWR)were employed to explore the mechanism by which CDL influences LUC under MFOZP guidance.The results show that:1)MFOZP implementation effectively alleviates land use pressure from regional development,with LUC continuously declining at a rate of 2.41%,while CDL exhibits slight growth(3.84%),during 2010-2020.2)Under MFOZP guidance,CDL reduces pressure on Land Use Structure Conflict(LUSC)and Land Use Process Conflict(LUPC),enhances its inhibitory effect on Land Use Function Conflict(LUFC),and significantly contributes to LUC coordination,with notable spatial heterogeneity.3)The coupling relationship between CDL and LUC has improved post-implementation.Based on this,tailored LUC coordination strategies are proposed for different functional zones.This study confirms the effectiveness of MFOZP in coordinating LUC and provides a scientific reference for LUC research under policy frameworks and the governance of LUC in the BTH region.展开更多
Turbofan engine is a critical aircraft component with complex structure and high-reliability requirements. Effectively predicting the remaining useful life(RUL) of turbofan engines has essential significance for devel...Turbofan engine is a critical aircraft component with complex structure and high-reliability requirements. Effectively predicting the remaining useful life(RUL) of turbofan engines has essential significance for developing maintenance strategies and reducing maintenance costs. Considering the characteristics of large sample size and high dimension of monitoring data, a hybrid health condition prediction model integrating the advantages of autoencoder and bidirectional long short-term memory(BLSTM) is proposed to improve the prediction accuracy of RUL. Autoencoder is used as a feature extractor to compress condition monitoring data. BLSTM is designed to capture the bidirectional long-range dependencies of features. A hybrid deep learning prediction model of RUL is constructed. This model has been tested on a benchmark dataset. The results demonstrate that this autoencoder-BLSTM hybrid model has a better prediction accuracy than the existing methods, such as multi-layer perceptron(MLP), support vector regression(SVR), convolutional neural network(CNN) and long short-term memory(LSTM). The proposed model can provide strong support for the health management and maintenance strategy development of turbofan engines.展开更多
Accurate load forecasting forms a crucial foundation for implementing household demand response plans andoptimizing load scheduling. When dealing with short-term load data characterized by substantial fluctuations,a s...Accurate load forecasting forms a crucial foundation for implementing household demand response plans andoptimizing load scheduling. When dealing with short-term load data characterized by substantial fluctuations,a single prediction model is hard to capture temporal features effectively, resulting in diminished predictionaccuracy. In this study, a hybrid deep learning framework that integrates attention mechanism, convolution neuralnetwork (CNN), improved chaotic particle swarm optimization (ICPSO), and long short-term memory (LSTM), isproposed for short-term household load forecasting. Firstly, the CNN model is employed to extract features fromthe original data, enhancing the quality of data features. Subsequently, the moving average method is used for datapreprocessing, followed by the application of the LSTM network to predict the processed data. Moreover, the ICPSOalgorithm is introduced to optimize the parameters of LSTM, aimed at boosting the model’s running speed andaccuracy. Finally, the attention mechanism is employed to optimize the output value of LSTM, effectively addressinginformation loss in LSTM induced by lengthy sequences and further elevating prediction accuracy. According tothe numerical analysis, the accuracy and effectiveness of the proposed hybrid model have been verified. It canexplore data features adeptly, achieving superior prediction accuracy compared to other forecasting methods forthe household load exhibiting significant fluctuations across different seasons.展开更多
In a previous study by the authors,positive results from both a case-control study and a cohort study were reported.In the present study a short-term test for the induction of mouse lung tumor by chloroprene was condu...In a previous study by the authors,positive results from both a case-control study and a cohort study were reported.In the present study a short-term test for the induction of mouse lung tumor by chloroprene was conducted to confirm whether chloroprene monomer itself can induce tumors.Kunming albino mice weaned at 2 weeks were subjected to inhaling 0,2.9±0.3, 19.2±1.9,and 189.0±13.3 mg/m^3 chloroprene(GC purity,99.8%)4 h daily(except Sunday) for 7 months.All survivors were killed at the end of the 8th month or when moribund.No lung tumors were found before the 6th month.Thus,survivors at the 6th month were counted as effective animals.Most lung tumors observed were papilloadenomas(50/57),and a few were adenomas(7/57).The tumor incidence in the 2.9 mg/m^3 group was 8.1% in comparison to 1.3% in the control group,with the significance level at P<0.05.The higher the concentration,the higher the incidence.Examination of the multiplicity of tumor induction also demonstrated a dose-response relationship,and the number of tumors per mouse in the 189 mg/m^3 group was significant at P<0.01.1989 Academic Press,Inc.展开更多
A generalized formulation for short-term scheduling of steam power system in iron and steel industry under the time-of-use（TOU）power price was presented,with minimization of total operational cost including fuel cos...A generalized formulation for short-term scheduling of steam power system in iron and steel industry under the time-of-use（TOU）power price was presented,with minimization of total operational cost including fuel cost,equipment maintenance cost and the charge of exchange power with main grid.The model took into account the varying nature of surplus byproduct gas flows,several practical technical constraints and the impact of TOU power price.All major types of utility equipments,involving boilers,steam turbines,combined heat and power（CHP）units,and waste heat and energy recovery generators（WHERG）,were separately modeled using thermodynamic balance equations and regression method.In order to solve this complex nonlinear optimization model,a new improved particle swarm optimization（IPSO）algorithm was proposed by incorporating time-variant parameters,a selfadaptive mutation scheme and efficient constraint handling strategies.Finally,a case study for a real industrial example was used for illustrating the model and validating the effectiveness of the proposed approach.展开更多
基金supported by the National Key Research and Development Project(Grant Number 2023YFB3709601)the National Natural Science Foundation of China(Grant Numbers 62373215,62373219,62073193)+2 种基金the Key Research and Development Plan of Shandong Province(Grant Numbers 2021CXGC010204,2022CXGC020902)the Fundamental Research Funds of Shandong University(Grant Number 2021JCG008)the Natural Science Foundation of Shandong Province(Grant Number ZR2023MF100).
文摘The remaining useful life prediction of rolling bearing is vital in safety and reliability guarantee.In engineering scenarios,only a small amount of bearing performance degradation data can be obtained through accelerated life testing.In the absence of lifetime data,the hidden long-term correlation between performance degradation data is challenging to mine effectively,which is the main factor that restricts the prediction precision and engineering application of the residual life prediction method.To address this problem,a novel method based on the multi-layer perception neural network and bidirectional long short-term memory network is proposed.Firstly,a nonlinear health indicator(HI)calculation method based on kernel principal component analysis(KPCA)and exponential weighted moving average(EWMA)is designed.Then,using the raw vibration data and HI,a multi-layer perceptron(MLP)neural network is trained to further calculate the HI of the online bearing in real time.Furthermore,The bidirectional long short-term memory model(BiLSTM)optimized by particle swarm optimization(PSO)is used to mine the time series features of HI and predict the remaining service life.Performance verification experiments and comparative experiments are carried out on the XJTU-SY bearing open dataset.The research results indicate that this method has an excellent ability to predict future HI and remaining life.
基金funded by scientific research projects under Grant JY2024B011.
文摘Accurate prediction of remaining useful life serves as a reliable basis for maintenance strategies,effectively reducing both the frequency of failures and associated costs.As a core component of PHM,RUL prediction plays a crucial role in preventing equipment failures and optimizing maintenance decision-making.However,deep learning models often falter when processing raw,noisy temporal signals,fail to quantify prediction uncertainty,and face challenges in effectively capturing the nonlinear dynamics of equipment degradation.To address these issues,this study proposes a novel deep learning framework.First,a newbidirectional long short-termmemory network integrated with an attention mechanism is designed to enhance temporal feature extraction with improved noise robustness.Second,a probabilistic prediction framework based on kernel density estimation is constructed,incorporating residual connections and stochastic regularization to achieve precise RUL estimation.Finally,extensive experiments on the C-MAPSS dataset demonstrate that our method achieves competitive performance in terms of RMSE and Score metrics compared to state-of-the-artmodels.More importantly,the probabilistic output provides a quantifiablemeasure of prediction confidence,which is crucial for risk-informed maintenance planning,enabling managers to optimize maintenance strategies based on a quantifiable understanding of failure risk.
基金supported by the National Natural Science Foundation of China(Grant No.62403486)。
文摘The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,this study proposes an intelligent decision-making framework based on a deep long short-term memory Q-network.This framework transforms the real-time sequencing for bolter recovery problem into a partially observable Markov decision process.It employs a stacked long shortterm memory network to accurately capture the long-range temporal dependencies of bolter event chains and fuel consumption.Furthermore,it integrates a prioritized experience replay training mechanism to construct a safe and adaptive scheduling system capable of millisecond-level real-time decision-making.Experimental demonstrates that,within large-scale mass recovery scenarios,the framework achieves zero safety violations in static environments and maintains a fuel safety violation rate below 10%in dynamic scenarios,with single-step decision times at the millisecond level.The model exhibits strong generalization capability,effectively responding to unforeseen emergent situations—such as multiple bolters and fuel emergencies—without requiring retraining.This provides robust support for efficient carrier-based aircraft recovery operations.
基金supported by the General Project of Humanities and Social Sciences Research of the Ministry of Education of China(24YJA790085)the Science and Technology Innovation Program of Beijing Institute of Technology,China(2024CX01020)。
文摘In China,farmers have increasingly adopted direct-seeded rice(DSR).While various impacts of DSR have been studied,limited evidence exists regarding the effect of DSR adoption on pesticide use.This study examines the impact of DSR adoption on pesticide use utilizing data from a 2018 survey of 982 rice farmers in China's Yangtze River Basin.The endogenous treatment-regression and switching regression models are employed to address self-selection bias.The results indicate that,after accounting for self-selection,DSR adopters spend 401.72 CNY ha^(-1) more on pesticides compared to non-adopters.Although DSR adoption significantly increases the use of insecticides,fungicides and herbicides,its impact is most pronounced for insecticide expenditure and least pronounced for herbicide expenditure.The findings remain robust when altering the dependent variable,truncating the research sample,and modifying the estimation method.Heterogeneous analysis reveals that DSR adoption has a stronger positive impact on pesticide expenditure among farmers below 60 years of age,with at least 6 years of education,and managing rice sown areas less than 2 ha.Based on these findings,this study recommends enhancing complementary techniques for DSR,improving the dissemination of DSR cultivation technologies,and strengthening socialized services.This research provides a comprehensive assessment of DSR's advantages and disadvantages,particularly regarding pesticide use,offering important policy implications for pesticide reduction.
基金funded by Malaysian Ministry of Higher Education(MOHE)under the Fundamental Research Grant Scheme(FRGS/1/2023/SSI07/MMU/02/3)which is awarded to the Multimedia University.The project is led by the second author.
文摘Background:Music has proven to be vital in enhancing resilience and promotingwell-being.Previously,the impact of music in sports environments was solely investigated,while this paper applies it to study environments,standing out as pioneering research.The study consists of a systematic development of a conceptual framework based on theories of Uses and Gratification Expectancy(UGE)and perceived motivation based on music elements.Their components are observed variables influencing students’psychological well-being(as the dependent variable).Resilience is examined as a mediator,influencing the relationships of both observed and dependent variables.The main purpose of this study is to highlight the positive effects of online music consumption on the psychological well-being of students.Methods:Semi-structured qualitative interviews were conducted with eighteen final year creative multimedia undergraduate students belonging to five central region Malaysian universities,especially on their UGE needs,and a similar concept survey instrument with two hundred participants.The interview data were analysed through thematic analysis,while the survey data through descriptive and Partial Least Squares Structural Equation Modeling(PLS-SEM).Results:The results highlight that students gain motivation from online music,which positively affects their psychological well-being(β=0.190,p=0.003,f^(2)=0.037),while resilience significantly affects this relationship(β=0.562,p<0.001,f^(2)=0.461).However,the results also predict a partial relationship between constructs based on UGE with psychological well-being,mediated by resilience,i.e.,AT-UGE(β=0.021,p=0.783,f^(2)=0.000),SIPI-UGE(β=0.228,p=0.004,f^(2)=0.044).Conclusion:The outcome of the study reflected practical,meaningful,and statistically significant results.The majority of the predictors,with the exception of one,i.e.,AT-UGE,displayed a clear positive relation of online music consumption on the Psychological Well-being of students.Future research will explore varying contextual factors impacting online music-related gratifications,motivations,and resilience,along with additional potential mediators and moderators.
基金supported by the National Natural Science Foundation of China(No.U23A20651)the Central Government Guides Local Science and Technology Development Foundation(No.2023ZYDF022)+1 种基金the Sichuan Science and Technology Program(2024ZDZX0031)the Open Fund Project of State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines(No.SKLMRDPC23KF19).
文摘Under complex working conditions,accurate prediction of the remaining useful life(RUL)of lithium-ion batteries is of great significance to ensure the stable operation of energy storage systems,the safe driving of electric vehicles,and the continuous power supply of electronic devices.This paper systematically describes the RUL prediction methods of lithium-ion batteries and comprehensively summarizes the development status and future trends in this field.First,the battery degradation mechanisms and lightweight data acquisition are analyzed.Secondly,a systematic classification model is constructed for the more widely used lithium battery RUL prediction methods,and the application characteristics and implementation limitations of different methods are analyzed in detail.An innovative classification framework for hybrid methods is proposed based on the depth of physical-data interaction.Then,collaborative modelling of calendar ageing and cyclic ageing is discussed,revealing their coupled effects and corresponding RUL prediction methods.Finally,the technical bottlenecks faced by the current RUL prediction of lithium batteries are identified,potential solutions are proposed,and the future development trends are outlined.
基金National Science and Technology Basic Resources Investigation Program(2022FY101901-2)。
文摘As a tropical island confronting the dual imperatives of tourism-driven economic growth and ecological vulnerability,Hainan's land-use sustainability critically impacts both regional development and coastal ecosystem security.This study employs a coupled PLUS-InVEST modeling framework to analyze land-use changes and habitat quality dynamics from 2000 to 2020,projecting ecological outcomes under three development scenarios for 2030.Key findings reveal:(1)A persistent bimodal habitat distribution pattern,with high-quality areas concentrated in the central forest zone and degraded areas in coastal peripheries,exhibiting a continuous decline over the 20-year period.(2)Accelerated urbanization between 2010 and 2020 resulted in the conversion of ecological land to construction use,correlating strongly with habitat fragmentation intensity.(3)Baseline projections for 2030 indicate that construction land will dominate new conversions.(4)Ecological protection scenarios demonstrate recoverable habitat potentials,particularly within coastal buffer zones.These findings provide empirical validation of scenario-driven land-use planning as a viable tool for island ecosystems,highlighting the critical need to balance tourism infrastructure development with coastal conservation imperatives in tropical island sustainability management.This methodology advances spatial decision-making for balancing island economic growth with biodiversity preservation,offering replicable strategies for global island ecosystems facing similar sustainability challenges.
基金funded by the Yunnan Provincial Key Programs for Basic Research Project,China(202301AS070087)the Yunnan Provincial R&D Program,China(202405AF140014 and 202302AO370015)the National Natural Science Foundation of China(42307058).
文摘Soil organic carbon(SOC)dynamics significantly influence ecosystem carbon source-sink balance,particularly in agroecosystems.However,uncertainty remains regarding optimal land use types for maximizing farmland carbon storage across different soil types,and identifying effective land management practices for enhanced carbon accumulation is essential for reducing agricultural emissions and strengthening carbon sinks.This study examined SOC variations in eastern Yunnan’s subtropical highlands(2,132 sites),analyzing topsoil(0–20 cm)across five land uses(dryland,irrigated land,forestland,grassland and plantation)of five soil types(red,yellow,yellowbrown,brown,purple).The investigation explored relationships between SOC and edaphic factors(26 elements)to determine SOC influencing factors.The study area demonstrated a mean SOC content of 27.78 g kg^(–1),with distinct spatial heterogeneity characterized by lower values in the southwestern sector and higher concentrations in the northeastern region.Brown soils displayed the highest SOC content(P<0.05),followed by yellow-brown then red,yellow,and purple soils.Irrigation significantly enhanced SOC storage,particularly in brown soils where irrigated land contained 2.2-,2.4-,and 1.6-times higher SOC than forestland,grassland,and dryland,respectively.Similar irrigation benefits occurred in purple,yellow,and yellow-brown soils,indicating moisture limitation as the primary SOC constraint.Notably,SOC exhibited strong positive correlations with nitrogen,sulfur,and selenium.Nitrogen fertilization demonstrated dual benefits:enhancing SOC sequestration and promoting Se enrichment in crops,potentially supporting specialty agriculture.Although land use impacts on SOC varied across soil types(P>0.05),irrigation consistently emerged as the optimal management for carbon sink enhancement.These findings suggest that targeted water management could effectively reduce farmland carbon emissions in moisture-limited subtropical highlands.Strategic nitrogen application offers co-benefits for soil fertility and selenium biofortification,providing practical pathways for climate-smart agriculture in similar ecoregions.
基金financially supported by the National Natural Science Foundation of China (42477044,32171648 and U23A2017)the Hubei Provincial Science and Technology Program,China (2025AFD451 and 2022CFB030)。
文摘Insight into the carbon turnover in soil aggregates and density fractions is essential for reducing the uncertainty in estimating carbon pools on the Tibetan Plateau,and how they vary with land use type is unclear.In this study,the effect of land use type on carbon storage and fractionation was quantified based on organic carbon and its ^(13)C abundance at the microscale of soil aggregates and density fractions in Tibetan alpine ecosystems.The sequence of soil aggregate destruction in the land use types of plantation(13.1%)<shrubland(32.7%)<grassland(47.9%)<farmland(61.8%)shows that plantations strengthen the soil structure.Plantation land had a greater contribution of light fraction organic carbon(28.3%)but a lower contribution of mineral-associated organic carbon(40.6%)to the carbon stock compared to farmland(13.5 and 70.3%).Interestingly,plantation land enhanced the aggregational differentiation of organic carbon and ^(13)C in each density fraction,whereas no such phenomenon existed in the soil organic carbon.Carbon isotope analyses revealed that carbon transfer in the plantation land occurred from the light fraction in macroaggregates(–24.9‰)to the mineral-associated fraction in microaggregates(–19.9‰).When compared to the other three land use types,the low transferability of carbon in aggregates and density fractions in plantation land provides a stable carbon pool for the Tibetan Plateau.This study shows that plantations can mitigate global climate change by slowing carbon transfer and increasing carbon storage at the microscale of aggregates and density fractions in alpine regions.
基金supported by the Soft Science Special Project of Gansu Basic Research Plan(25JRZA206)the Longyuan Youth Talent Project of Gansu Province(ZHU Rong)+1 种基金the Innovation Development Special Project of China Meteorological Administration(CXFZ2025J036)the Program of the State Key Laboratory of Cryospheric Science and Frozen Soil Engineering,Chinese Academy of Sciences(CSFSE-KF-2402).
文摘Land use in arid and semi-arid regions has a substantial effect on climate,environment,and biodiversity,thereby projecting the spatiotemporal changes in land use and the subsequent effects.This study employed the locally calibrated Future Land Use Simulation(FLUS)model,which coupled system dynamics with cellular automata and integrated an artificial neural network algorithm and a roulette wheel selection mechanism.We projected future land use(2020–2100)dynamics of Lanzhou,a typical river valley city in Northwest China,under three different Shared Socioeconomic Pathway(SSP)scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5).The simulation results were validated and subsequently reclassified using the International Geosphere Biosphere Programme(IGBP)system to produce a dataset suitable for driving climatic and environmental models.Under the SSP1-2.6 scenario,urban and built-up land expanded consistently,whereas irrigated cropland and pasture as well as grassland contracted continuously.Conversely,the SSP5-8.5 scenario was characterized by a contraction of urban and built-up land,and relative stability of irrigated cropland and pasture as well as grassland.The SSP2-4.5 scenario presented a more complex trade-off,where urban and built-up land and grassland increased first and then decreased,whereas irrigated cropland and pasture followed an opposite trajectory.A significant inverse relationship between urban and built-up land and irrigated cropland and pasture was observed under all scenarios,underscoring the fundamental spatial competition that prevailed in this land-constrained valley city.Furthermore,the negative correlation of grassland with urban and built-up land,coupled with the positive correlation of grassland with irrigated cropland and pasture under both the SSP1-2.6 and SSP5-8.5 scenarios,indicated an evolution from broad confrontation to intricate internal trade-offs within the urban–agricultural–ecological system.This study underscored the critical influence of regional topographic and hydrological constraints on land-use evolution in arid regions,providing guidance for water resource management and ecosystem protection in Lanzhou,with applications for sustainable land-use planning in other arid and semi-arid river valley cities.
基金provided by the Guangdong Province Low-Carbon Fragrant Rice Cultivation Demonstration Project,China(F23032)。
文摘As the global leader in rice production,China's paddy fields contribute substantially to greenhouse gas emissions through methane(CH_(4))and nitrous oxide(N_(2)O)releases.Aromatic rice cultivation practices have been optimized to enhance the aroma,so the relationship between its cultivation and greenhouse gas emissions from paddy fields is unclear.To investigate how aroma-enhancing cultivation practices drive microbial community dynamics in aromatic rice paddies and their implications for greenhouse gas emissions,a two-year experiment in five ecological locations(Xingning,Nanxiong,Conghua,Luoding,and Zengcheng)compared two farming practices:partial organic substitution for inorganic fertilizers combined with water-saving irrigation(IOF+W)and traditional cultivation(CK).The CH_(4)and N_(2)O emissions,soil microbial composition and function,global warming potential(GWP),nitrogen use efficiency,yield,and the content of 2-acetyl-1-pyrroline(2-AP)were measured and analyzed.The main purpose was to investigate the impact of IOF+W on CH_(4)and N_(2)O emissions and their relationship with soil microorganisms.The results showed that IOF+W significantly reduced CH_(4)emission fluxes and totals(36.95%)and GWP(31.29%),while significantly increasing N_(2)O emission fluxes and totals(14.82%).The soil microbial community structure was reshaped by the IOF+W treatment,which suppressed methanogens but enhanced the abundances of nitrifying and denitrifying bacteria.Key enzymatic activities involved in CH_(4)production,such as methyl-coenzyme M reductase,formylmethanofuran dehydrogenase,and methyltransferase,decreased.In contrast,the activity of the key CH_(4)-oxidizing enzyme methanol dehydrogenase increased.This shift led to an overall attenuation of the CH_(4)production metabolism while enhancing the CH_(4)oxidation metabolism.In addition,the activities of pivotal enzymes involved in denitrification and nitrification were improved,thus enhancing nitrogen nitrification and denitrification metabolism.Moreover,the IOF+W treatment significantly increased nitrogen use efficiency(47.83%),yield(14.77%),and 2-AP content(13.78%).Therefore,the IOF+W treatment demonstrated good efficacy as a sustainable strategy for achieving productive,green,resource-efficient,and premium-quality aromatic rice cultivation in South China.
基金funded by the National Natural Science Foundation of China(42377326 and 42201267)National Research-Development Support Plan Projects of China(Grant No.2017YFC05054)the Fujian Provincial Water Resources Department Science and Technology Project(MSK202308)。
文摘The Guangdong,Jiangxi and Fujian(GJF)provinces,located in the subtropical region of southeastern China,is one of the national key regions for soil erosion control and ecological restoration.This region is characterized by extensive red soil development and high rainfall erosivity,making it a representative landscape for exploring the interactions between land use change(LUC)and ecosystem services(ES).Despite the recognized importance of ES in hilly regions,comprehensive assessing the impacts of LUC on ES remain limited.This study investigates five key ES:water yield,soil conservation,carbon conservation,food supply,and habitat quality in GJF region from 2000 to 2020.By applying the InVEST model and the Geodetector method,we assessed the trade-offs,synergies,and transitions among ES,identified the natural and social drivers of ES dynamics,and quantified the contribution of LUC to ES changes using the ecosystem service contribution index.The results showed that cropland and woodland were the dominant land use types.Ecological restoration efforts positively influenced ES,with synergies intensifying and trade-offs diminishing over time.Land use conversions,particularly among woodland,grassland,and cropland,exerted significant impacts on ES.In particular,the conversion of woodland to other land uses had markedly negative effects on soil conservation,carbon conservation,and habitat quality.Forest cover was identified as a major driver of ES dynamics.These findings highlight the importance of maintaining and expanding forest and grassland cover,strengthening red soil conservation,and optimizing land use structure to achieve coordinated ecological protection and socioeconomic development in the subtropical hilly regions of southern China.
基金supported by the National Natural Science Foundation of China(Grant No.42371027).
文摘Against the background of rapid urbanization and the“Dual Carbon”goals,analyzing the impact mechanisms of land use change on carbon metabolism is crucial for regional sustainable development.Taking the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)as the study area,we integrate energy consumption data and the Forest Carbon Sequestration(FCS)model to clarify the land use carbon metabolism status based on Ecological Network Analysis(ENA),and systematically analyze the spatiotemporal evolution patterns of urban land use carbon metabolism,interactions between land types,as well as its driving mechanisms in the GBA from 2000 to 2023.The results show that:(1)Over the past two decades,land use changes have exhibited a significant characteristic of“natural land retreat and construction land expansion”,with areas of cropland,forest,and waterbody shrank by 16%,4%,and 4% respectively,while urban land and industrial land increased by 50%and 438%respectively;76% of the reclaimed land was transferred to construction land.(2)The imbalance of carbon metabolism was jointly affected by land use patterns and land use change processes:carbon emissions from energy consumption surged by 116%,while land carbon sequestration capacity decreased by 12%;in most periods,the negative carbon flow from land use change exceeded positive flows,with both showing sharp fluctuations.(3)Construction land in various cities dominated the carbon flow network through control or exploitation relationships,and the mutual transfer between industrial land and cropland is the primary driver;ecological land protection policies(e.g.,the forest“in-out balance”scheme)effectively reduced the intensity of competition relationship.(4)The push-pull forces of land types demonstrate the dual effect of industrialization and urbanization,but their contribution has gradually weakened as the speed of urbanization declined in various cities;the proportion of the indirect carbon flow reached a maximum of 37%(2005-2010),indicating that the indirect impact of land use change cannot be ignored.This study deepens the understanding of the land-carbon interactions,reveals the implicit effects of the“policy implementation-land use change-carbon flow generation”transmission chain,and proposes a“construction land-cropland-ecological land”constraint system and a synergistic path of industrial land intensification and inefficient land ecological restoration.It provides methodological support for low-carbon governance at the urban agglomeration scale.
文摘Residential energy-use behavior and energy-saving awareness play a crucial role in sustainable urban energy planning and building energy efficiency,particularly under the pressures of climate change.However,existing studies often lack comparative analysis of urban-rural differences and tend to focus excessively on behavior patterns while neglecting the dimension of energysaving awareness.With China’s urbanization rate reaching 66.16%,understanding such regional disparities has become increasingly important.To address these research gaps,this study conducts a large-scale survey on space cooling behaviors among residents in Beijing,a representative Chinese megacity.It should be noted that living standards in such megacities are generally higher than the national average,which may shape distinctive energy-use profiles.Analyzing 1573valid samples(1064 urban/442 rural)in 2024,this study employed K-Prototypes and K-Modes clustering to identify typical cooling behavior and energy-saving awareness pattems,followed by Kendall/Chi-square correlation tests and XGBoost importance analysis to determine key influencing factors,with subsequent urban-rural comparative analysis.Results indicate that urban residents are primarily heat-sensitive or heat-tolerant,with a secondary patten of mid-low temperature preference,and generally exhibit long cooling durations;rural behavior is dominated by heat-tolerant type,followed by heat-sensitive,mid-low temperature preference,and never-on types as secondary patterns;both urban and rural areas exhibit energy-savingawareness characterized by low consumption-lowwillingness,though urban areas show marginally higher motivation;energy-saving awareness correlates with cooling behavior in rural areas,but this relationship weakens significantly in urban contexts.
基金Under the auspices of the National Key Research and Development Program of China(No.2018YFD1100803)the Fundamental Research Fund for the Central Universities(Ph.D.Top Innovative Talents Fund of CUMTB)(No.BBJ2024029)。
文摘Systematically analyzing the impact mechanisms of policy on Land Use Conflict(LUC)is crucial for constructing effective conflict mitigation strategies.However,previous research on how policy influences LUC remains relatively limited.Focusing on the indirect driving role of policy on LUC,this study proposed County Development Level(CDL)under Major Function Oriented Zone Planning(MFOZP)guidance as an intermediary variable,bridging the implicit influence of MFOZP and the explicit changes in LUC.Using the Beijing-Tianjin-Hebei(BTH)region in China as a case study,we analyzed the spatio-temporal evolution characteristics of LUC and CDL for the periods 2000-2010 and 2010-2020,before and after MFOZP implementation.Panel models and Geographically Weighted Regression(GWR)were employed to explore the mechanism by which CDL influences LUC under MFOZP guidance.The results show that:1)MFOZP implementation effectively alleviates land use pressure from regional development,with LUC continuously declining at a rate of 2.41%,while CDL exhibits slight growth(3.84%),during 2010-2020.2)Under MFOZP guidance,CDL reduces pressure on Land Use Structure Conflict(LUSC)and Land Use Process Conflict(LUPC),enhances its inhibitory effect on Land Use Function Conflict(LUFC),and significantly contributes to LUC coordination,with notable spatial heterogeneity.3)The coupling relationship between CDL and LUC has improved post-implementation.Based on this,tailored LUC coordination strategies are proposed for different functional zones.This study confirms the effectiveness of MFOZP in coordinating LUC and provides a scientific reference for LUC research under policy frameworks and the governance of LUC in the BTH region.
基金the National Natural Science Foundation of China(Nos.51505288 and 51875359)the TBT Project of Shanghai(No.18TBT003)the Project of Shanghai Telecom(No.17C1ZA0069SH301)
文摘Turbofan engine is a critical aircraft component with complex structure and high-reliability requirements. Effectively predicting the remaining useful life(RUL) of turbofan engines has essential significance for developing maintenance strategies and reducing maintenance costs. Considering the characteristics of large sample size and high dimension of monitoring data, a hybrid health condition prediction model integrating the advantages of autoencoder and bidirectional long short-term memory(BLSTM) is proposed to improve the prediction accuracy of RUL. Autoencoder is used as a feature extractor to compress condition monitoring data. BLSTM is designed to capture the bidirectional long-range dependencies of features. A hybrid deep learning prediction model of RUL is constructed. This model has been tested on a benchmark dataset. The results demonstrate that this autoencoder-BLSTM hybrid model has a better prediction accuracy than the existing methods, such as multi-layer perceptron(MLP), support vector regression(SVR), convolutional neural network(CNN) and long short-term memory(LSTM). The proposed model can provide strong support for the health management and maintenance strategy development of turbofan engines.
基金the Shanghai Rising-Star Program(No.22QA1403900)the National Natural Science Foundation of China(No.71804106)the Noncarbon Energy Conversion and Utilization Institute under the Shanghai Class IV Peak Disciplinary Development Program.
文摘Accurate load forecasting forms a crucial foundation for implementing household demand response plans andoptimizing load scheduling. When dealing with short-term load data characterized by substantial fluctuations,a single prediction model is hard to capture temporal features effectively, resulting in diminished predictionaccuracy. In this study, a hybrid deep learning framework that integrates attention mechanism, convolution neuralnetwork (CNN), improved chaotic particle swarm optimization (ICPSO), and long short-term memory (LSTM), isproposed for short-term household load forecasting. Firstly, the CNN model is employed to extract features fromthe original data, enhancing the quality of data features. Subsequently, the moving average method is used for datapreprocessing, followed by the application of the LSTM network to predict the processed data. Moreover, the ICPSOalgorithm is introduced to optimize the parameters of LSTM, aimed at boosting the model’s running speed andaccuracy. Finally, the attention mechanism is employed to optimize the output value of LSTM, effectively addressinginformation loss in LSTM induced by lengthy sequences and further elevating prediction accuracy. According tothe numerical analysis, the accuracy and effectiveness of the proposed hybrid model have been verified. It canexplore data features adeptly, achieving superior prediction accuracy compared to other forecasting methods forthe household load exhibiting significant fluctuations across different seasons.
文摘In a previous study by the authors,positive results from both a case-control study and a cohort study were reported.In the present study a short-term test for the induction of mouse lung tumor by chloroprene was conducted to confirm whether chloroprene monomer itself can induce tumors.Kunming albino mice weaned at 2 weeks were subjected to inhaling 0,2.9±0.3, 19.2±1.9,and 189.0±13.3 mg/m^3 chloroprene(GC purity,99.8%)4 h daily(except Sunday) for 7 months.All survivors were killed at the end of the 8th month or when moribund.No lung tumors were found before the 6th month.Thus,survivors at the 6th month were counted as effective animals.Most lung tumors observed were papilloadenomas(50/57),and a few were adenomas(7/57).The tumor incidence in the 2.9 mg/m^3 group was 8.1% in comparison to 1.3% in the control group,with the significance level at P<0.05.The higher the concentration,the higher the incidence.Examination of the multiplicity of tumor induction also demonstrated a dose-response relationship,and the number of tumors per mouse in the 189 mg/m^3 group was significant at P<0.01.1989 Academic Press,Inc.
基金Sponsored by National Natural Science Foundation of China(51304053)International Science and Technology Cooperation Program of China(2013DFA10810)
文摘A generalized formulation for short-term scheduling of steam power system in iron and steel industry under the time-of-use（TOU）power price was presented,with minimization of total operational cost including fuel cost,equipment maintenance cost and the charge of exchange power with main grid.The model took into account the varying nature of surplus byproduct gas flows,several practical technical constraints and the impact of TOU power price.All major types of utility equipments,involving boilers,steam turbines,combined heat and power（CHP）units,and waste heat and energy recovery generators（WHERG）,were separately modeled using thermodynamic balance equations and regression method.In order to solve this complex nonlinear optimization model,a new improved particle swarm optimization（IPSO）algorithm was proposed by incorporating time-variant parameters,a selfadaptive mutation scheme and efficient constraint handling strategies.Finally,a case study for a real industrial example was used for illustrating the model and validating the effectiveness of the proposed approach.
