The smart meter communication system has substantial application value for the construction and upgrading of the entire power system.The deployment of the transmitter(Tx)of the smart meter system in the residential sc...The smart meter communication system has substantial application value for the construction and upgrading of the entire power system.The deployment of the transmitter(Tx)of the smart meter system in the residential scenarios is vexed by the need for more theoretical support.This paper mainly studies the communication channel between the Tx at semibasement and receiver(Rx)at outdoor.The design of an effective communication system relies on an accurate understanding of channel characteristics.Channel measurements and ray-tracing channel modeling are conducted to obtain channel data.The influence of different positions at same semi-basement is studied.Typical channel characteristics are analyzed,such as power delay profile(PDP),power angular profile(PAP),root-mean-square(RMS)delay spread(DS),channel capacity,received power,and path loss.The influence of different semi-basement placements and different floor heights is also compared.Besides,the channel measurements and simulation data fit well,which can illustrate the validity and reliability of the acquired channel data.This paper can provide theoretical support for the design and optimization of smart meter communication systems in semi-basement scenarios.展开更多
Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the...Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the coordination with virtual power plants(VPPs).The proposed strategy improves systemflexibility and responsiveness by optimizing the power adjustment of flexible resources.In the proposed strategy,theGaussian Process Regression(GPR)is firstly employed to determine the adjustable range of aggregated power within the VPP,facilitating an assessment of its potential contribution to power supply support.Then,an optimal dispatch model based on a leader-follower game is developed to maximize the benefits of the VPP and flexible resources while guaranteeing the power balance at the same time.To solve the proposed optimal dispatch model efficiently,the constraints of the problem are reformulated and resolved using the Karush-Kuhn-Tucker(KKT)optimality conditions and linear programming duality theorem.The effectiveness of the strategy is illustrated through a detailed case study.展开更多
This paper proposes that China,under the challenge of balancing its development and security,can aim for the Paris Agreement's goal to limit global warming to no more than 2℃by actively seeking carbonpeak and car...This paper proposes that China,under the challenge of balancing its development and security,can aim for the Paris Agreement's goal to limit global warming to no more than 2℃by actively seeking carbonpeak and carbon-neutrality pathways that align with China's national conditions,rather than following the idealized path toward the 1.5℃target by initially relying on extensive negative-emission technologies such as direct air carbon capture and storage(DACCS).This work suggests that pursuing a 1.5℃target is increasingly less feasible for China,as it would potentially incur 3–4 times the cost of pursuing the 2℃target.With China being likely to achieve a peak in its emissions around 2028,at about 12.8 billion tonnes of anthropogenic carbon dioxide(CO_(2)),and become carbon neutral,projected global warming levels may be less severe after the 2050s than previously estimated.This could reduce the risk potential of climate tipping points and extreme events,especially considering that the other two major carbon emitters in the world(Europe and North America)have already passed their carbon peaks.While natural carbon sinks will contribute to China's carbon neutrality efforts,they are not expected to be decisive in the transition stages.This research also addresses the growing focus on climate overshoot,tipping points,extreme events,loss and damage,and methane reductions in international climate cooperation,emphasizing the need to balance these issues with China's development,security,and fairness considerations.China's pursuit of carbon neutrality will have significant implications for global emissions scenarios,warming levels,and extreme event projections,as well as for climate change hotspots of international concern,such as climate tipping points,the climate crisis,and the notion that the world has moved from a warming to a boiling era.Possible research recommendations for global emissions scenarios based on China's 2℃target pathway are also summarized.展开更多
Precision actuation is a foundational technology in high-end equipment domains,where stroke,velocity,and accuracy are critical for processing and/or detection quality,precision in spacecraft flight trajectories,and ac...Precision actuation is a foundational technology in high-end equipment domains,where stroke,velocity,and accuracy are critical for processing and/or detection quality,precision in spacecraft flight trajectories,and accuracy in weapon system strikes.Piezoelectric actuators(PEAs),known for their nanometer-level precision,flexible stroke,resistance to electromagnetic interference,and scalable structure,have been widely adopted across various fields.Therefore,this study focuses on extreme scenarios involving ultra-high precision(micrometer and beyond),minuscule scales,and highly complex operational conditions.It provides a comprehensive overview of the types,working principles,advantages,and disadvantages of PEAs,along with their potential applications in piezo-actuated smart mechatronic systems(PSMSs).To address the demands of extreme scenarios in high-end equipment fields,we have identified five representative application areas:positioning and alignment,biomedical device configuration,advanced manufacturing and processing,vibration mitigation,micro robot system.Each area is further divided into specific subcategories,where we explore the underlying relationships,mechanisms,representative schemes,and characteristics.Finally,we discuss the challenges and future development trends related to PEAs and PSMSs.This work aims to showcase the latest advancements in the application of PEAs and provide valuable guidance for researchers in this field.展开更多
With the rapid development of virtual reality(VR)and augmented reality(AR)technologies,their application potential in the field of education has become increasingly significant.For a long time,fire safety education in...With the rapid development of virtual reality(VR)and augmented reality(AR)technologies,their application potential in the field of education has become increasingly significant.For a long time,fire safety education in university laboratories has faced numerous challenges,and traditional teaching methods have been insufficiently effective,with high-risk scenarios difficult to realistically recreate.Especially in special scenarios involving hazardous chemicals,conventional training methods struggle to enable learners to achieve deep understanding and behavioral formation.This study systematically integrates immersive technology theory with safety education needs,providing a replicable technical solution for safety education in high-risk environments.Its modular design approach has reference value for expansion into other professional fields,offering practical evidence for innovation in safety education models in the digital age.展开更多
The frequent outbreaks of crop diseases pose a serious threat to global agricultural production and food security.Data-driven forecasting models have emerged as an effective approach to support early warning and manag...The frequent outbreaks of crop diseases pose a serious threat to global agricultural production and food security.Data-driven forecasting models have emerged as an effective approach to support early warning and management,yet the lack of user-friendly tools for model development remains a major bottleneck.This study presents the Multi-Scenario Crop Disease Forecasting Modeling System(MSDFS),an open-source platform that enables end-to-end model construction-from multi-source data ingestion and feature engineering to training,evaluation,and deployment-across four representative scenarios:static point-based,static grid-based,dynamic point-based,and dynamic grid-based.Unlike conventional frameworks,MSDFS emphasizes modeling flexibility,allowing users to build,compare,and interpret diverse forecasting approaches within a unified workflow.A notable feature of the system is the integration of a weather scenario generator,which facilitates comprehensive testing of model performance and adaptability under extreme climatic conditions.Case studies corresponding to the four scenarios were used to validate the system,with overall accuracy(OA)ranging from 73%to 93%.By lowering technical barriers,the system is designed to serve plant protection managers and agricultural producers without advanced programming expertise,providing a practical modeling tool that supports the construction of smart plant protection systems.展开更多
Climate change and anthropogenic pressures increasingly threaten the ecological integrity of inland water bodies,particularly saline lakes due to their unique hydrological and biological features.This review focuses o...Climate change and anthropogenic pressures increasingly threaten the ecological integrity of inland water bodies,particularly saline lakes due to their unique hydrological and biological features.This review focuses on Lake Tudakul,one of Uzbekistan’s largest saline lakes and a Ramsar-listed wetland,assessing its vulnerability under future climate scenarios.The study integrates climate scenario modeling(RCP4.5 and RCP8.5)with standardized ecotoxicological bioassays—Microtox®,MARA,algal growth inhibition,Lemna minor,and Daphnia magna toxicity tests—to evaluate combined effects of rising temperatures(2.0℃and 4.5℃)and chemical pollutants.Results reveal increased biological sensitivity to contaminants under elevated temperatures,suggesting potential synergistic impacts that may disrupt lake ecosystem structure and function.Lake Tudakul,a regional biodiversity hotspot,is exposed to agrochemical runoff,increasing salinity,and microplastic pollution,threatening aquatic organisms and ecological services.The accumulation and trophic transfer of pollutants—such as heavy metals,persistent organic compounds,and micro(nano)plastics—pose risks to food webs,public health,and water safety.These stressors may also increase the likelihood of harmful algal blooms and cyanotoxin outbreaks.The study emphasizes the urgent need for early-warning systems,adaptive management,and transboundary cooperation to mitigate ecological risks.Lake Tudakul exemplifies the vulnerability of semi-arid lakes under compounding climate and human pressures,highlighting the importance of integrative,ecosystem-based strategies to safeguard biodiversity and freshwater resources.展开更多
Purpose:Explore the factors affecting medical data sharing in clinical research scenarios from the user’s perspective,reveal the differences between different user groups,and deepen the understanding of medical data ...Purpose:Explore the factors affecting medical data sharing in clinical research scenarios from the user’s perspective,reveal the differences between different user groups,and deepen the understanding of medical data sharing mechanisms.Design/methodology/approach:By integrating the UTAUT model,trust theory and self-efficacy theory,introducing the concepts of data transparency and individual innovation,and combining internal and external motivators,we constructed a conceptual model of medical data users’sharing behavior in clinical research scenarios.We conducted empirical research by collecting 360 pieces of first-hand data from clinical researchers.Findings:Among the internal motivators,effort expectation had a higher impact on sharing intention than performance expectation,individual innovation and self-efficacy had a higher impact on sharing behavior than trust.Trust does not show a significant impact on sharing intention,but it has a significant positive influence on sharing behavior.Among the external motivators,community influence and data transparency both positively affect sharing intention.In addition,users with different working years,professional status,data level needs,and different sharing experiences showed significant differences in healthcare data sharing.Research limitations:Our sample of clinical researchers from China was used as empirical data.Further research is needed to examine the generality of the study findings.Practical implications:The findings enhance healthcare data stakeholders’understanding of healthcare data sharing in clinical research scenarios and provide theoretical and practical insights for relevant researchers.Originality/value:In this study,the UTAUT model,trust theory and self-efficacy theory were integrated and applied to clinical research scenarios for the first time,and the concepts of data transparency and individual innovation were introduced,and the CRS-USB conceptual model was constructed and validated to extend the UTAUT model.展开更多
Wind power generation is subjected to complex and variable meteorological conditions,resulting in intermittent and volatile power generation.Accurate wind power prediction plays a crucial role in enabling the power gr...Wind power generation is subjected to complex and variable meteorological conditions,resulting in intermittent and volatile power generation.Accurate wind power prediction plays a crucial role in enabling the power grid dispatching departments to rationally plan power transmission and energy storage operations.This enhances the efficiency of wind power integration into the grid.It allows grid operators to anticipate and mitigate the impact of wind power fluctuations,significantly improving the resilience of wind farms and the overall power grid.Furthermore,it assists wind farm operators in optimizing the management of power generation facilities and reducing maintenance costs.Despite these benefits,accurate wind power prediction especially in extreme scenarios remains a significant challenge.To address this issue,a novel wind power prediction model based on learning approach is proposed by integrating wavelet transform and Transformer.First,a conditional generative adversarial network(CGAN)generates dynamic extreme scenarios guided by physical constraints and expert rules to ensure realism and capture critical features of wind power fluctuations under extremeconditions.Next,thewavelet transformconvolutional layer is applied to enhance sensitivity to frequency domain characteristics,enabling effective feature extraction fromextreme scenarios for a deeper understanding of input data.The model then leverages the Transformer’s self-attention mechanism to capture global dependencies between features,strengthening its sequence modelling capabilities.Case analyses verify themodel’s superior performance in extreme scenario prediction by effectively capturing local fluctuation featureswhile maintaining a grasp of global trends.Compared to other models,it achieves R-squared(R^(2))as high as 0.95,and the mean absolute error(MAE)and rootmean square error(RMSE)are also significantly lower than those of othermodels,proving its high accuracy and effectiveness in managing complex wind power generation conditions.展开更多
Soil and water matching in a land basin is important for securing land demand,alleviating human-land conflicts,and promoting sustainable development in the region.The Tarim River Basin(TRB)is the largest inland river ...Soil and water matching in a land basin is important for securing land demand,alleviating human-land conflicts,and promoting sustainable development in the region.The Tarim River Basin(TRB)is the largest inland river basin in China and primarily sustains an agricultural economy centered around oases.This study employs the Patch-generating Land-Use Simulation(PLUS)model to forecast the changing patterns of land use across various future scenarios.The connection between land development and the ecological environment is examined through the lens of relative ecological value and ecological impact.The results indicate that:(1)From 1992 to 2020,the ecology of the basin showed an improving trend,with the area of new cropland increasing by 18,850.51 km^(2)at a growth rate of 56.13%.Grassland area increased by 10,235.29 km^(2)and barren land area decreased by 20,597.29 km^(2).(2)Under the four tested scenarios of Natural Development,Cropland Conservation,Ecological Protection,and Urban Expansion(scenarios Ⅰ-Ⅳ,respectively),the PLUS results for the year 2050 show an increase in cropland area of 12.69% under Scenario Ⅱ,an increase in grassland area of 20,374.82 km^(2)under Scenario Ⅳ,and an increase in built-up land area of 1,105.57 km^(2)under Scenario Ⅲ.(3)A simulation of the basin's ecology in 2050 shows a significant improvement trend under Scenario Ⅳ.Specifically,the development of a large amount of barren land into grassland and woodland has significant ecological benefits,with a contribution rate of 61.88%to 70.18%.This study provides a strong scientific foundation for future land management and ecological sustainable development in the TRB.展开更多
A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These...A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These approaches exploit railway safety data once the transport system has received authorization for commissioning.However,railway standards and regulations require the development of a safety management system(SMS)from the specification and design phases of the railway system.This article proposes a new AI approach for analyzing and assessing safety from the specification and design phases of the railway system with a view to improving the development of the SMS.Unlike some learning methods,the proposed approach,which is dedicated in particular to safety assessment bodies,is based on semi-supervised learning carried out in close collaboration with safety experts who contributed to the development of a database of potential accident scenarios(learning example database)relating to the risk of rail collision.The proposed decision support is based on the use of an expert system whose knowledge base is automatically generated by inductive learning in the form of an association rule(rule base)and whose main objective is to suggest to the safety expert possible hazards not considered during the development of the SMS to complete the initial hazard register.展开更多
Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the c...Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the current emergency resource allocation of chemical enterprises lacks scientific analysis of accident scenarios,and the individual allocation method of enterprises increases the cost of emergency resource allocation.Given the above problems,this paper proposes a regional collaborative allocation method of emergency resources for enterprises within the chemical industry park(CIP)based on the worst credible accident scenario(WCAS).Firstly,the concept and analysis method of the WCAS is proposed.Then,based on the characteristics and consequences of the accident,the mapping relationship between accident scenarios and emergency resources is established.Finally,an optimization model for regional collaborative allocation of emergency resources is constructed to determine the amount of emergency resource allocation for each enterprise.Through the case study,the emergency resource allocation method based on the WCAS analysis can better meet the demands of accident emergency rescue.Simultaneously,the regional collaborative allocation optimization model can strengthen the cooperation ability among enterprises,greatly reducing the cost of emergency resource allocation for each enterprise.展开更多
Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational s...Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational scenarios,considering the large amount of historical operational snapshot data.Specifically,DTSAs analyse the intrinsic mechanisms of different scheduling operational scenario switching to mathematically represent typical operational scenarios.A Gramian angular summation field-based operational scenario image encoder was designed to convert operational scenario sequences into highdimensional spaces.This enables DTSAs to fully capture the spatiotemporal characteristics of new power systems using deep feature iterative aggregation models.The encoder also facilitates the generation of typical operational scenarios that conform to historical data distributions while ensuring the integrity of grid operational snapshots.Case studies demonstrate that the proposed method extracted new fine-grained power system dispatch schemes and outperformed the latest high-dimensional feature-screening methods.In addition,experiments with different new energy access ratios were conducted to verify the robustness of the proposed method.DTSAs enable dispatchers to master the operation experience of the power system in advance,and actively respond to the dynamic changes of the operation scenarios under the high access rate of new energy.展开更多
Compared with traditional energy sources,wind power has a lower environmental impact.However,emissions are still generated across the life cycle of wind turbines,from production to recycling.As wind power rapidly deve...Compared with traditional energy sources,wind power has a lower environmental impact.However,emissions are still generated across the life cycle of wind turbines,from production to recycling.As wind power rapidly develops and deployment increases,these impacts are becoming increasingly evident.A comprehensive understanding of these impacts is crucial for sustainable development.Based on the harmonization of previous detailed life cycle assessment(LCA)studies,this study develops a simplified LCA model that estimates the life cycle environmental impacts of wind turbines based on their nominal power.Using this simplified LCA model,we assess the global warming potential(GWP),acidification potential(AP),and cumulative energy demand(CED)of wind power at the regional scale for 2022 and under three future scenarios(high-power wind turbine promotion,reduced wind curtailment,and a comprehensive development scenario).The results indicate that in 2022,the life cycle GWP,AP,and CED of wind power in western China were 10.76 g CO_(2) eq/kWh,0.177 g SO_(2) eq/kWh,and 17.6 kJ/kWh,respectively.Scenario simulations suggest that reducing wind curtailment is the most effective approach for reducing emissions in Inner Mongolia,Gansu,Qinghai,Ningxia,and Xinjiang,producing average decreases of 8.64%in GWP,8.39%in AP,and 9.26%in CED.In contrast,for Guangxi,Chongqing,Sichuan,Guizhou,Yunnan,Xizang,and Shaanxi,the promotion of high-power wind turbines provides greater environmental benefits than reducing curtailment,producing average decreases of 3.45%,3.09%,and 4.29%in GWP,AP,and CED,respectively.These findings help clarify the environmental impact of wind power across its life cycle at the regional scale and provide theoretical references for the direction of future wind power development and the formulation of related policies.展开更多
There exists great potential of rural land consolidation in China due to the aggra- vated hollowed villages against the background of rapid rural-urban transformation. The pa- per aims to investigate the potential of ...There exists great potential of rural land consolidation in China due to the aggra- vated hollowed villages against the background of rapid rural-urban transformation. The pa- per aims to investigate the potential of rural land consolidation within four urbanization sce- narios： Complete urbanization, Semi-urbanization, Urbanization in batches and prospective urbanization in 2020. Research findings show that, （1） the potentials of rural land consolida- tion in complete and semi-urbanization are 809.89×104 hm2 and 699.19×104 hm2 respectively while rural consolidation rates are 50.70% and 43.77%. As for the urbanization in batches and urbanization in 2020, the potentials are 757.89×104 hm2 and 992.16×104 hm2. （2） Beside Tibet and Ningxia, rural consolidation rates in most provinces are between 40% and 60%, and the land increase rates are between 3% and 12%. Significant correlation between potential of rural land consolidation and the degree of hollowed villages is also found. （3） Evident differ- ences of potential of rural land consolidation exist across provinces. Rural consolidation rates in the East and Central provinces are higher than that in the West provinces. Villages in the developed areas have higher consolidation rates than those in the less developed areas, and villages in the plain areas tend to have higher consolidation rates than those in the moun- tainous areas.展开更多
This paper applies the newest emission scenarios of the sulfur and greenhouse gases, namely IPCC SRES A2 and B2 scenarios, to investigate the change of the North China climate with an atmosphere-ocean coupled general ...This paper applies the newest emission scenarios of the sulfur and greenhouse gases, namely IPCC SRES A2 and B2 scenarios, to investigate the change of the North China climate with an atmosphere-ocean coupled general circulation model. In the last three decades of the 21st century, the global warming enlarges the land-sea thermal contrast, and hence, causes the East Asian summer (winter) monsoon circulation to he strengthened (weakened). The rainfall seasonality strengthens and the summer precipitation increases significantly in North China. It is suggested that the East Asian rainy area would expand northward to North China in the last three decades of the 21st century. In addition, the North China precipitation would increase significantly in September. In July, August, and September, the interannual variability of the precipitation enlarges evidently over North China, implying a risk of flooding in the future.展开更多
Assessment of vulnerability for natural ecosystem to climate change is a hot topic in climate change and ecology, and will support adapting and mitigating climate change. In this study, LPJ model modified according to...Assessment of vulnerability for natural ecosystem to climate change is a hot topic in climate change and ecology, and will support adapting and mitigating climate change. In this study, LPJ model modified according to features of China＇s natural ecosystems was em- ployed to simulate ecosystem dynamics under A2, B2 and A1B scenarios. Vulnerability of natural ecosystem to climate change was assessed according to the vulnerability assessment model. Based on eco-geographical regions, vulnerability of natural ecosystem to climate change was analyzed. Results suggest that vulnerability for China＇s natural ecosystems would strengthen in the east and weaken in the west, but the pattern of ecosystem vulner- ability would not be altered by climate change, which rises from southeast to northeast gradually. Increase in ecosystem vulnerable degree would mainly concentrate in temperate humid/sub-humid region and warm temperate humid/sub-humid region. Decrease in eco- system vulnerable degree may emerge in northwestern arid region and Qinghai-Tibet Plateau region. In the near-term scale, natural ecosystem in China would be slightly affected by cli- mate change. However, in mid-term and long-term scales, there would be severely adverse effect, particularly in the east with better water and thermal condition.展开更多
There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties...There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project （CMIP2） are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.展开更多
基金supported by the Natural Science Foundation of Shandong Province under Grant ZR2024MF062the open research fund of National Mobile Communications Research Laboratory,Southeast University under Grants 2025D03+1 种基金the Future Plan Program for Young Scholars of Shandong University,and the Innovation and Technology Support Program for Young Scholars of Colleges and Universities in Shandong Province under Grant 2022KJ009The B6G R&D Group in Shandong University is greatly thanked for channel measurements.
文摘The smart meter communication system has substantial application value for the construction and upgrading of the entire power system.The deployment of the transmitter(Tx)of the smart meter system in the residential scenarios is vexed by the need for more theoretical support.This paper mainly studies the communication channel between the Tx at semibasement and receiver(Rx)at outdoor.The design of an effective communication system relies on an accurate understanding of channel characteristics.Channel measurements and ray-tracing channel modeling are conducted to obtain channel data.The influence of different positions at same semi-basement is studied.Typical channel characteristics are analyzed,such as power delay profile(PDP),power angular profile(PAP),root-mean-square(RMS)delay spread(DS),channel capacity,received power,and path loss.The influence of different semi-basement placements and different floor heights is also compared.Besides,the channel measurements and simulation data fit well,which can illustrate the validity and reliability of the acquired channel data.This paper can provide theoretical support for the design and optimization of smart meter communication systems in semi-basement scenarios.
基金supported by the Science and Technology Project of Sichuan Electric Power Company“Power Supply Guarantee Strategy for Urban Distribution Networks Considering Coordination with Virtual Power Plant during Extreme Weather Event”(No.521920230003).
文摘Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the coordination with virtual power plants(VPPs).The proposed strategy improves systemflexibility and responsiveness by optimizing the power adjustment of flexible resources.In the proposed strategy,theGaussian Process Regression(GPR)is firstly employed to determine the adjustable range of aggregated power within the VPP,facilitating an assessment of its potential contribution to power supply support.Then,an optimal dispatch model based on a leader-follower game is developed to maximize the benefits of the VPP and flexible resources while guaranteeing the power balance at the same time.To solve the proposed optimal dispatch model efficiently,the constraints of the problem are reformulated and resolved using the Karush-Kuhn-Tucker(KKT)optimality conditions and linear programming duality theorem.The effectiveness of the strategy is illustrated through a detailed case study.
基金supported by the top-level design of the National Natural Science Foundation of China(NSFC)Major Project“Realization of optimal carbon neutral pathway and coupling of multi-scale interaction patterns of natural-social systems in China”(42341202)the Basic Scientific Research Fund of the Chinese Academy of Meteorological Sciences(2021Z014)。
文摘This paper proposes that China,under the challenge of balancing its development and security,can aim for the Paris Agreement's goal to limit global warming to no more than 2℃by actively seeking carbonpeak and carbon-neutrality pathways that align with China's national conditions,rather than following the idealized path toward the 1.5℃target by initially relying on extensive negative-emission technologies such as direct air carbon capture and storage(DACCS).This work suggests that pursuing a 1.5℃target is increasingly less feasible for China,as it would potentially incur 3–4 times the cost of pursuing the 2℃target.With China being likely to achieve a peak in its emissions around 2028,at about 12.8 billion tonnes of anthropogenic carbon dioxide(CO_(2)),and become carbon neutral,projected global warming levels may be less severe after the 2050s than previously estimated.This could reduce the risk potential of climate tipping points and extreme events,especially considering that the other two major carbon emitters in the world(Europe and North America)have already passed their carbon peaks.While natural carbon sinks will contribute to China's carbon neutrality efforts,they are not expected to be decisive in the transition stages.This research also addresses the growing focus on climate overshoot,tipping points,extreme events,loss and damage,and methane reductions in international climate cooperation,emphasizing the need to balance these issues with China's development,security,and fairness considerations.China's pursuit of carbon neutrality will have significant implications for global emissions scenarios,warming levels,and extreme event projections,as well as for climate change hotspots of international concern,such as climate tipping points,the climate crisis,and the notion that the world has moved from a warming to a boiling era.Possible research recommendations for global emissions scenarios based on China's 2℃target pathway are also summarized.
基金financially supported by the National Key R&D Program of China(Grant No.2022YFC2204203)the National Natural Science Foundation of China(Grant No.52305107)。
文摘Precision actuation is a foundational technology in high-end equipment domains,where stroke,velocity,and accuracy are critical for processing and/or detection quality,precision in spacecraft flight trajectories,and accuracy in weapon system strikes.Piezoelectric actuators(PEAs),known for their nanometer-level precision,flexible stroke,resistance to electromagnetic interference,and scalable structure,have been widely adopted across various fields.Therefore,this study focuses on extreme scenarios involving ultra-high precision(micrometer and beyond),minuscule scales,and highly complex operational conditions.It provides a comprehensive overview of the types,working principles,advantages,and disadvantages of PEAs,along with their potential applications in piezo-actuated smart mechatronic systems(PSMSs).To address the demands of extreme scenarios in high-end equipment fields,we have identified five representative application areas:positioning and alignment,biomedical device configuration,advanced manufacturing and processing,vibration mitigation,micro robot system.Each area is further divided into specific subcategories,where we explore the underlying relationships,mechanisms,representative schemes,and characteristics.Finally,we discuss the challenges and future development trends related to PEAs and PSMSs.This work aims to showcase the latest advancements in the application of PEAs and provide valuable guidance for researchers in this field.
文摘With the rapid development of virtual reality(VR)and augmented reality(AR)technologies,their application potential in the field of education has become increasingly significant.For a long time,fire safety education in university laboratories has faced numerous challenges,and traditional teaching methods have been insufficiently effective,with high-risk scenarios difficult to realistically recreate.Especially in special scenarios involving hazardous chemicals,conventional training methods struggle to enable learners to achieve deep understanding and behavioral formation.This study systematically integrates immersive technology theory with safety education needs,providing a replicable technical solution for safety education in high-risk environments.Its modular design approach has reference value for expansion into other professional fields,offering practical evidence for innovation in safety education models in the digital age.
基金supported by Zhejiang Provincial Natural Science Foundation of China(Grant No.LR25D010003)The Zhejiang Provincial Key Research and Development Program(Grant No.2023C02018)National Natural Science Foundation of China(Grant No.42401400).
文摘The frequent outbreaks of crop diseases pose a serious threat to global agricultural production and food security.Data-driven forecasting models have emerged as an effective approach to support early warning and management,yet the lack of user-friendly tools for model development remains a major bottleneck.This study presents the Multi-Scenario Crop Disease Forecasting Modeling System(MSDFS),an open-source platform that enables end-to-end model construction-from multi-source data ingestion and feature engineering to training,evaluation,and deployment-across four representative scenarios:static point-based,static grid-based,dynamic point-based,and dynamic grid-based.Unlike conventional frameworks,MSDFS emphasizes modeling flexibility,allowing users to build,compare,and interpret diverse forecasting approaches within a unified workflow.A notable feature of the system is the integration of a weather scenario generator,which facilitates comprehensive testing of model performance and adaptability under extreme climatic conditions.Case studies corresponding to the four scenarios were used to validate the system,with overall accuracy(OA)ranging from 73%to 93%.By lowering technical barriers,the system is designed to serve plant protection managers and agricultural producers without advanced programming expertise,providing a practical modeling tool that supports the construction of smart plant protection systems.
基金supported by Türkiye Council of Higher Education Research Universities Support Program(Project Number:32762).
文摘Climate change and anthropogenic pressures increasingly threaten the ecological integrity of inland water bodies,particularly saline lakes due to their unique hydrological and biological features.This review focuses on Lake Tudakul,one of Uzbekistan’s largest saline lakes and a Ramsar-listed wetland,assessing its vulnerability under future climate scenarios.The study integrates climate scenario modeling(RCP4.5 and RCP8.5)with standardized ecotoxicological bioassays—Microtox®,MARA,algal growth inhibition,Lemna minor,and Daphnia magna toxicity tests—to evaluate combined effects of rising temperatures(2.0℃and 4.5℃)and chemical pollutants.Results reveal increased biological sensitivity to contaminants under elevated temperatures,suggesting potential synergistic impacts that may disrupt lake ecosystem structure and function.Lake Tudakul,a regional biodiversity hotspot,is exposed to agrochemical runoff,increasing salinity,and microplastic pollution,threatening aquatic organisms and ecological services.The accumulation and trophic transfer of pollutants—such as heavy metals,persistent organic compounds,and micro(nano)plastics—pose risks to food webs,public health,and water safety.These stressors may also increase the likelihood of harmful algal blooms and cyanotoxin outbreaks.The study emphasizes the urgent need for early-warning systems,adaptive management,and transboundary cooperation to mitigate ecological risks.Lake Tudakul exemplifies the vulnerability of semi-arid lakes under compounding climate and human pressures,highlighting the importance of integrative,ecosystem-based strategies to safeguard biodiversity and freshwater resources.
基金supported by the National Natural Science Foundation of China(Grant No.72374081)the Key Research and Development Project of the Department of Science and Technology of Jilin Province(Grant No.20240304164SF).
文摘Purpose:Explore the factors affecting medical data sharing in clinical research scenarios from the user’s perspective,reveal the differences between different user groups,and deepen the understanding of medical data sharing mechanisms.Design/methodology/approach:By integrating the UTAUT model,trust theory and self-efficacy theory,introducing the concepts of data transparency and individual innovation,and combining internal and external motivators,we constructed a conceptual model of medical data users’sharing behavior in clinical research scenarios.We conducted empirical research by collecting 360 pieces of first-hand data from clinical researchers.Findings:Among the internal motivators,effort expectation had a higher impact on sharing intention than performance expectation,individual innovation and self-efficacy had a higher impact on sharing behavior than trust.Trust does not show a significant impact on sharing intention,but it has a significant positive influence on sharing behavior.Among the external motivators,community influence and data transparency both positively affect sharing intention.In addition,users with different working years,professional status,data level needs,and different sharing experiences showed significant differences in healthcare data sharing.Research limitations:Our sample of clinical researchers from China was used as empirical data.Further research is needed to examine the generality of the study findings.Practical implications:The findings enhance healthcare data stakeholders’understanding of healthcare data sharing in clinical research scenarios and provide theoretical and practical insights for relevant researchers.Originality/value:In this study,the UTAUT model,trust theory and self-efficacy theory were integrated and applied to clinical research scenarios for the first time,and the concepts of data transparency and individual innovation were introduced,and the CRS-USB conceptual model was constructed and validated to extend the UTAUT model.
基金funded by the Science and Technology Project of State Grid Corporation of China under Grant No.5108-202218280A-2-299-XG.
文摘Wind power generation is subjected to complex and variable meteorological conditions,resulting in intermittent and volatile power generation.Accurate wind power prediction plays a crucial role in enabling the power grid dispatching departments to rationally plan power transmission and energy storage operations.This enhances the efficiency of wind power integration into the grid.It allows grid operators to anticipate and mitigate the impact of wind power fluctuations,significantly improving the resilience of wind farms and the overall power grid.Furthermore,it assists wind farm operators in optimizing the management of power generation facilities and reducing maintenance costs.Despite these benefits,accurate wind power prediction especially in extreme scenarios remains a significant challenge.To address this issue,a novel wind power prediction model based on learning approach is proposed by integrating wavelet transform and Transformer.First,a conditional generative adversarial network(CGAN)generates dynamic extreme scenarios guided by physical constraints and expert rules to ensure realism and capture critical features of wind power fluctuations under extremeconditions.Next,thewavelet transformconvolutional layer is applied to enhance sensitivity to frequency domain characteristics,enabling effective feature extraction fromextreme scenarios for a deeper understanding of input data.The model then leverages the Transformer’s self-attention mechanism to capture global dependencies between features,strengthening its sequence modelling capabilities.Case analyses verify themodel’s superior performance in extreme scenario prediction by effectively capturing local fluctuation featureswhile maintaining a grasp of global trends.Compared to other models,it achieves R-squared(R^(2))as high as 0.95,and the mean absolute error(MAE)and rootmean square error(RMSE)are also significantly lower than those of othermodels,proving its high accuracy and effectiveness in managing complex wind power generation conditions.
基金supported by the National Natural Science Foundation of China(Grant No.W2412135)the Tianshan Yingcai Program of Xinjiang Uygur Autonomous Region(Grant No.2022TSYCCX0038)the International Cooperation Program of Chinese Academy of Sciences(Grant No.131965KYSB20210045)。
文摘Soil and water matching in a land basin is important for securing land demand,alleviating human-land conflicts,and promoting sustainable development in the region.The Tarim River Basin(TRB)is the largest inland river basin in China and primarily sustains an agricultural economy centered around oases.This study employs the Patch-generating Land-Use Simulation(PLUS)model to forecast the changing patterns of land use across various future scenarios.The connection between land development and the ecological environment is examined through the lens of relative ecological value and ecological impact.The results indicate that:(1)From 1992 to 2020,the ecology of the basin showed an improving trend,with the area of new cropland increasing by 18,850.51 km^(2)at a growth rate of 56.13%.Grassland area increased by 10,235.29 km^(2)and barren land area decreased by 20,597.29 km^(2).(2)Under the four tested scenarios of Natural Development,Cropland Conservation,Ecological Protection,and Urban Expansion(scenarios Ⅰ-Ⅳ,respectively),the PLUS results for the year 2050 show an increase in cropland area of 12.69% under Scenario Ⅱ,an increase in grassland area of 20,374.82 km^(2)under Scenario Ⅳ,and an increase in built-up land area of 1,105.57 km^(2)under Scenario Ⅲ.(3)A simulation of the basin's ecology in 2050 shows a significant improvement trend under Scenario Ⅳ.Specifically,the development of a large amount of barren land into grassland and woodland has significant ecological benefits,with a contribution rate of 61.88%to 70.18%.This study provides a strong scientific foundation for future land management and ecological sustainable development in the TRB.
文摘A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These approaches exploit railway safety data once the transport system has received authorization for commissioning.However,railway standards and regulations require the development of a safety management system(SMS)from the specification and design phases of the railway system.This article proposes a new AI approach for analyzing and assessing safety from the specification and design phases of the railway system with a view to improving the development of the SMS.Unlike some learning methods,the proposed approach,which is dedicated in particular to safety assessment bodies,is based on semi-supervised learning carried out in close collaboration with safety experts who contributed to the development of a database of potential accident scenarios(learning example database)relating to the risk of rail collision.The proposed decision support is based on the use of an expert system whose knowledge base is automatically generated by inductive learning in the form of an association rule(rule base)and whose main objective is to suggest to the safety expert possible hazards not considered during the development of the SMS to complete the initial hazard register.
基金support provided by the Qingdao Science and Technology Benefits People Demonstration and Guidance Project(21-1-4-sf-4-nsh).
文摘Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the current emergency resource allocation of chemical enterprises lacks scientific analysis of accident scenarios,and the individual allocation method of enterprises increases the cost of emergency resource allocation.Given the above problems,this paper proposes a regional collaborative allocation method of emergency resources for enterprises within the chemical industry park(CIP)based on the worst credible accident scenario(WCAS).Firstly,the concept and analysis method of the WCAS is proposed.Then,based on the characteristics and consequences of the accident,the mapping relationship between accident scenarios and emergency resources is established.Finally,an optimization model for regional collaborative allocation of emergency resources is constructed to determine the amount of emergency resource allocation for each enterprise.Through the case study,the emergency resource allocation method based on the WCAS analysis can better meet the demands of accident emergency rescue.Simultaneously,the regional collaborative allocation optimization model can strengthen the cooperation ability among enterprises,greatly reducing the cost of emergency resource allocation for each enterprise.
基金The Key R&D Project of Jilin Province,Grant/Award Number:20230201067GX。
文摘Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational scenarios,considering the large amount of historical operational snapshot data.Specifically,DTSAs analyse the intrinsic mechanisms of different scheduling operational scenario switching to mathematically represent typical operational scenarios.A Gramian angular summation field-based operational scenario image encoder was designed to convert operational scenario sequences into highdimensional spaces.This enables DTSAs to fully capture the spatiotemporal characteristics of new power systems using deep feature iterative aggregation models.The encoder also facilitates the generation of typical operational scenarios that conform to historical data distributions while ensuring the integrity of grid operational snapshots.Case studies demonstrate that the proposed method extracted new fine-grained power system dispatch schemes and outperformed the latest high-dimensional feature-screening methods.In addition,experiments with different new energy access ratios were conducted to verify the robustness of the proposed method.DTSAs enable dispatchers to master the operation experience of the power system in advance,and actively respond to the dynamic changes of the operation scenarios under the high access rate of new energy.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFF1303405).
文摘Compared with traditional energy sources,wind power has a lower environmental impact.However,emissions are still generated across the life cycle of wind turbines,from production to recycling.As wind power rapidly develops and deployment increases,these impacts are becoming increasingly evident.A comprehensive understanding of these impacts is crucial for sustainable development.Based on the harmonization of previous detailed life cycle assessment(LCA)studies,this study develops a simplified LCA model that estimates the life cycle environmental impacts of wind turbines based on their nominal power.Using this simplified LCA model,we assess the global warming potential(GWP),acidification potential(AP),and cumulative energy demand(CED)of wind power at the regional scale for 2022 and under three future scenarios(high-power wind turbine promotion,reduced wind curtailment,and a comprehensive development scenario).The results indicate that in 2022,the life cycle GWP,AP,and CED of wind power in western China were 10.76 g CO_(2) eq/kWh,0.177 g SO_(2) eq/kWh,and 17.6 kJ/kWh,respectively.Scenario simulations suggest that reducing wind curtailment is the most effective approach for reducing emissions in Inner Mongolia,Gansu,Qinghai,Ningxia,and Xinjiang,producing average decreases of 8.64%in GWP,8.39%in AP,and 9.26%in CED.In contrast,for Guangxi,Chongqing,Sichuan,Guizhou,Yunnan,Xizang,and Shaanxi,the promotion of high-power wind turbines provides greater environmental benefits than reducing curtailment,producing average decreases of 3.45%,3.09%,and 4.29%in GWP,AP,and CED,respectively.These findings help clarify the environmental impact of wind power across its life cycle at the regional scale and provide theoretical references for the direction of future wind power development and the formulation of related policies.
基金The Key Project of National Natural Science Foundation of China, No.41130748.
文摘There exists great potential of rural land consolidation in China due to the aggra- vated hollowed villages against the background of rapid rural-urban transformation. The pa- per aims to investigate the potential of rural land consolidation within four urbanization sce- narios： Complete urbanization, Semi-urbanization, Urbanization in batches and prospective urbanization in 2020. Research findings show that, （1） the potentials of rural land consolida- tion in complete and semi-urbanization are 809.89×104 hm2 and 699.19×104 hm2 respectively while rural consolidation rates are 50.70% and 43.77%. As for the urbanization in batches and urbanization in 2020, the potentials are 757.89×104 hm2 and 992.16×104 hm2. （2） Beside Tibet and Ningxia, rural consolidation rates in most provinces are between 40% and 60%, and the land increase rates are between 3% and 12%. Significant correlation between potential of rural land consolidation and the degree of hollowed villages is also found. （3） Evident differ- ences of potential of rural land consolidation exist across provinces. Rural consolidation rates in the East and Central provinces are higher than that in the West provinces. Villages in the developed areas have higher consolidation rates than those in the less developed areas, and villages in the plain areas tend to have higher consolidation rates than those in the moun- tainous areas.
基金supported by the Key Project of the Chinese Academy of Sciences(KZCX2-SW-210)the Key Project of the Chinese Academy of Sciences(KZCX2-203)the National Key Programme for Developing Basic Sciences(G1998040904).
文摘This paper applies the newest emission scenarios of the sulfur and greenhouse gases, namely IPCC SRES A2 and B2 scenarios, to investigate the change of the North China climate with an atmosphere-ocean coupled general circulation model. In the last three decades of the 21st century, the global warming enlarges the land-sea thermal contrast, and hence, causes the East Asian summer (winter) monsoon circulation to he strengthened (weakened). The rainfall seasonality strengthens and the summer precipitation increases significantly in North China. It is suggested that the East Asian rainy area would expand northward to North China in the last three decades of the 21st century. In addition, the North China precipitation would increase significantly in September. In July, August, and September, the interannual variability of the precipitation enlarges evidently over North China, implying a risk of flooding in the future.
基金The"Strategic Priority Research Program"of the Chinese Academy of Sciences,No.XDA05090308Na-tional Key Technologies R&D Program during the 12th Five-Year Plan of China,No.2012BAC19B04No.2012BAC19B10
文摘Assessment of vulnerability for natural ecosystem to climate change is a hot topic in climate change and ecology, and will support adapting and mitigating climate change. In this study, LPJ model modified according to features of China＇s natural ecosystems was em- ployed to simulate ecosystem dynamics under A2, B2 and A1B scenarios. Vulnerability of natural ecosystem to climate change was assessed according to the vulnerability assessment model. Based on eco-geographical regions, vulnerability of natural ecosystem to climate change was analyzed. Results suggest that vulnerability for China＇s natural ecosystems would strengthen in the east and weaken in the west, but the pattern of ecosystem vulner- ability would not be altered by climate change, which rises from southeast to northeast gradually. Increase in ecosystem vulnerable degree would mainly concentrate in temperate humid/sub-humid region and warm temperate humid/sub-humid region. Decrease in eco- system vulnerable degree may emerge in northwestern arid region and Qinghai-Tibet Plateau region. In the near-term scale, natural ecosystem in China would be slightly affected by cli- mate change. However, in mid-term and long-term scales, there would be severely adverse effect, particularly in the east with better water and thermal condition.
文摘There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project （CMIP2） are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.
