An effective energy management strategy(EMS)is essential to optimize the energy efficiency of electric vehicles(EVs).With the advent of advanced machine learning techniques,the focus on developing sophisticated EMS fo...An effective energy management strategy(EMS)is essential to optimize the energy efficiency of electric vehicles(EVs).With the advent of advanced machine learning techniques,the focus on developing sophisticated EMS for EVs is increasing.Here,we introduce LearningEMS:a unified framework and open-source benchmark designed to facilitate rapid development and assessment of EMS.LearningEMS is distinguished by its ability to support a variety of EV configurations,including hybrid EVs,fuel cell EVs,and plug-in EVs,offering a general platform for the development of EMS.The framework enables detailed comparisons of several EMS algorithms,encompassing imitation learning,deep reinforcement learning(RL),offline RL,model predictive control,and dynamic programming.We rigorously evaluated these algorithms across multiple perspectives:energy efficiency,consistency,adaptability,and practicability.Furthermore,we discuss state,reward,and action settings for RL in EV energy management,introduce a policy extraction and reconstruction method for learning-based EMS deployment,and conduct hardware-in-the-loop experiments.In summary,we offer a unified and comprehensive framework that comes with three distinct EV platforms,over 10000 km of EMS policy data set,ten state-of-the-art algorithms,and over 160 benchmark tasks,along with three learning libraries.Its flexible design allows easy expansion for additional tasks and applications.The open-source algorithms,models,data sets,and deployment processes foster additional research and innovation in EV and broader engineering domains.展开更多
In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation ...In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation is provided”and that“the validation step is largely overlooked”.This assertion may have been true several years ago,for example,when Ochoa and Urbina-Cardona(2017)made a similar observation.However,there has been much work on ES model validation over the last decade.展开更多
Marine pollution and overfishing induced the biodiversity loss and ecological degradation of the Beibu Gulf ecosystem in Guangxi,SE China.In an effort to restore the ecosystem and fishery resources,artificial reefs we...Marine pollution and overfishing induced the biodiversity loss and ecological degradation of the Beibu Gulf ecosystem in Guangxi,SE China.In an effort to restore the ecosystem and fishery resources,artificial reefs were deployed in the Beibu Gulf as the marine ranching area and their ecological performance need to be investigated.We constructed Ecopath ecological trophic models for the marine ranching area and a nearby control area to compare their ecosystem throughput and food web structure difference,and to calculate the ecological carrying capacity of various functional groups.Results indicate that the total system throughput of the marine ranching area was significantly higher than the control area,and the majority of system throughput occurred at trophic levelsⅠandⅡin both ecosystems.The system connectance indices for the marine ranching and control areas were 0.27 and 0.32,and the omnivory indices were 0.16 and 0.19,indicating simple food web structures;both areas are in a developmental stage with TPP/TR ratios of 2.69 and 9.36,respectively.Compared to the control area,marine ranching area exhibited a higher system maturity,and the ecological carrying capacity of“large and medium-sized demersal fish”and“other bivalves”functional groups in the marine ranching area increased by 43.83%and 233.62%,respectively,allowing for more high-trophic-level predators and large benthic animals.This study provided a reference for the formulation of fishery management policies in the Beibu Gulf,to maintain ecosystem stability and biodiversity.展开更多
Resilience plays a crucial role in maintaining desirable ecosystem states and is a key objective of sustainable ecosystem management.This study synthesizes the concepts and measurement approaches of terrestrial ecosys...Resilience plays a crucial role in maintaining desirable ecosystem states and is a key objective of sustainable ecosystem management.This study synthesizes the concepts and measurement approaches of terrestrial ecosystem resilience and expounded on its spatio-temporal changes and influencing factors based on the literature over the past 50 years.Arid regions exhibited the lowest levels of spatial resilience,and the global ecosystem resilience showed a downward trend.In the focal regions,ecological resilience in Amazonian and Southeast Asian rainforest regions declined primarily driven by human activities such as deforestation and cropland expansion.Precipitation and temperature exerted bidirectional influences the resilience of ecosystems,indicating that ecosystem responses to climatic factors were non-monotonic.Evidence concerning anthropogenic factors such as land management and deforestation on ecosystem resilience were predominantly negative.Overall,this study provides a comprehensive synthesis of large scale terrestrial ecosystem resilience assessments,offering valuable insights for ecosystem protection and restoration policy development.展开更多
Phosphorus (P) is an essential nutrient element that is critical for plant growth and ecosystem functionality.The soil P cycle plays multiple roles,such as sustaining plant growth and productivity,regulating nutrient ...Phosphorus (P) is an essential nutrient element that is critical for plant growth and ecosystem functionality.The soil P cycle plays multiple roles,such as sustaining plant growth and productivity,regulating nutrient balance within ecosystems,and enhancing ecosystem adaptability and resilience.This cycle is influenced by factors such as the restoration approach and microbial community dynamics.However,the extent to which the restoration approach alters the P cycle in karst ecosystems and the underlying microbial mechanisms remain poorly understood.The P-cycle multifunctionality index (P-cycle MFI) serves as a comprehensive indicator for evaluating soil P cycle function,and it provides insights into changes in the P cycle between different restoration approaches.To investigate the shifts in soil P-cycle MFI and microbial mechanisms between different restoration approaches,we analyzed soil available P (AP),total P (TP),microbial biomass P (MBP),and the activities of acid phosphatase (ACP) and alkaline phosphatase (ALP).These data were used to calculate the P-cycle MFI by averaging the Z-scores between two restoration approaches(artificial restoration of forest (AF) and natural restoration of forest (NF)) and a control (cropland,CP) at six subtropical karst ecosystem sites in China.We also determined the soil organic carbon (SOC),exchangeable calcium (Ca) and magnesium (Mg),pH,bulk density (BD),microbial biomass C (MBC),and microbial biomass nitrogen (MBN),as well as the community structure,relative abundance,diversity indices,and co-occurrence networks of phoD-harboring bacteria.The results showed that the community structure of phoD-harboring bacteria varied significantly among AF,NF,and CP and across different temperature gradients.These bacteria exhibited increasing complexity and tightness in co-occurrence networks from CP to AF and then to NF,along with the ACP and ALP activities,but not the TP and AP contents.The P-cycle MFI values were significantly higher in NF compared to AF and CP,and the variation was significantly explained by restoration approach,temperature,MBC,MBN,SOC,exchangeable Ca,BD,community structure of phoD-harboring bacteria,and exchangeable Mg.Furthermore,natural restoration had a more substantial impact on the P-cycle MFI than temperature by enhancing SOC,microbial biomass,the complexity and co-occurrence network tightness of the phoD-harboring bacterial community structure,and ACP and ALP activities,but it reduced soil BD.The rare genera of phoD-harboring bacteria significantly influenced the variation of soil P-cycle MFI compared to the dominant genera.This study highlights the importance of rare genera of phoD-harboring bacteria in driving soil P-cycle multifunctionality in karst ecosystems,with natural restoration being more effective than artificial methods for enhancing soil organic matter and microbial community complexity.展开更多
Livestock farming is a critical pillar of Tajikistan’s national economy and livelihood security.However,significant economic challenges in the country have led to the degradation of grassland ecosystems.This degradat...Livestock farming is a critical pillar of Tajikistan’s national economy and livelihood security.However,significant economic challenges in the country have led to the degradation of grassland ecosystems.This degradation has not only reduced the productivity of grassland ecosystems but also severely impacted their ecological functions.A particularly concerning consequence is the threat to biodiversity,as the survival and persistence of endemic,rare,and endangered plant species are at serious risk,thereby diminishing the value of species’genetic resources.Based on the data from multiple sources such as literature reviews,field observations,and national statistics,this study employed a systematic literature review and meta-analysis to investigate the current status,causes of degradation,and restoration measures for grassland ecosystems in Tajikistan.The results revealed that Tajikistan’s grassland ecosystems support exceptionally high plant species diversity,comprising over 4500 vascular plant species,including nearly 1500 endemic and sub-endemic taxa that constitute a unique genetic reservoir.These ecosystems are experiencing severe degradation,characterized by significantly reduced vegetation cover and declining species richness.Palatable forage species are increasingly being displaced by unpalatable,thorny,and poisonous species.The primary drivers of degradation include excessive grazing pressure,which disrupts plant reproductive cycles and regeneration capacity,habitat fragmentation due to urbanization and infrastructure development,and uncontrolled exploitation of medicinal and edible plants.Climate change,particularly rising temperatures and altered precipitation patterns,further exacerbates these anthropogenic pressures.Ecological restoration experiments suggested that both ecosystem productivity and plant species diversity are significantly enhanced by systematic reseeding trials using altitude-adapted native species.These findings underscore the necessity of establishing scientifically grounded approaches for ecological restoration.展开更多
Floodplain wetlands are invaluable ecosystems providing numerous ecological benefits,yet they face a global crisis necessitating sustainable preservation efforts.This study examines the depletion of floodplain wetland...Floodplain wetlands are invaluable ecosystems providing numerous ecological benefits,yet they face a global crisis necessitating sustainable preservation efforts.This study examines the depletion of floodplain wetlands within the Hastinapur Wildlife Sanctuary(HWLS)in Uttar Pradesh.Encroachment activities such as grazing,agriculture,and human settlements have fragmented and degraded critical wetland ecosystems.Additionally,irrigation projects,dam construction,and water diversion have disrupted natural water flow and availability.To assess wetland inundation in 2023,five classification techniques were employed:Random Forest(RF),Support Vector Machine(SVM),artificial neural network(ANN),Spectral Information Divergence(SID),and Maximum Likelihood Classifier(MLC).SVM emerged as the most precise method,as determined by kappa coefficient and index-based validation.Consequently,the SVM classifier was used to model wetland inundation areas from 1983 to 2023 and analyze spatiotemporal changes and fragmentation patterns.The findings revealed that the SVM clas-sifier accurately mapped 2023 wetland areas.The modeled time-series data demonstrated a 62.55%and 38.12%reduction in inundated wetland areas over the past 40 years in the pre-and post-monsoon periods,respectively.Fragmentation analysis indicated an 86.27%decrease in large core wetland areas in the pre-monsoon period,signifying severe habitat degradation.This rapid decline in wetlands within protected areas raises concerns about their ecological impacts.By linking wetland loss to global sustainability objectives,this study underscores the global urgency for strengthened wetland protection measures and highlights the need for integrating wetland conservation into broader sustainable development goals.Effective policies and adaptive management strategies are crucial for preserving these ecosystems and their vital services,which are essential for biodiversity,climate regulation,and human well-being.展开更多
Arid and semi-arid ecosystems are prone to extensive fires due to specific climatic conditions,sparse vegetation cover,and high density of fine fuels.Understanding the flammability characteristics of land covers is es...Arid and semi-arid ecosystems are prone to extensive fires due to specific climatic conditions,sparse vegetation cover,and high density of fine fuels.Understanding the flammability characteristics of land covers is essential for fire management and designing land restoration programs in arid and semi-arid ecosystems.This study provided a new approach to evaluate the flammability of shrublands and woodlands using flammability indices(FIs)including time to ignition(TI),duration of combustion(DC),and flame height(FH)of plant species and their relative frequencies in the Dalfard Basin of southeastern Iran.The results showed that there was a significant difference in FIs between land covers.Shrublands had higher flammability potential compared with woodlands.Plant moisture content had a negative relationship with TI(P<0.010)and no significant relationship with DC and FH(P>0.050).Artemisia spp.,Astragalus gossypinus Fischer,Amygdalus scoparia Spach,and Cymbopogon jwarancusa(Jones)Schult.had the highest FI.Tree species such as Rhazya stricta Decne.,and Pistacia atlantica Desf.showed greater resistance to fire.Using principal component analysis,the relationship between species and FIs was examined,and TI of wet fuel was the most important FI in relation to species.Structural equation model showed that life form(P<0.001)was the most important flammability driver.Precipitation(P<0.010)and legume species(P<0.010)were significantly related to the flammability in arid land.This study emphasizes the importance of managing high-risk species and using resistant species in vegetation restoration and shows that combining species FIs with their abundance is an effective tool for assessing fire risk and fuel management at the plant community scale.展开更多
Understanding the complex interactions between human activities and ecosystem functions is a prerequisite for achieving sustainable development.Since the implementation of the“Grain for Green”Project in 1999,ecosyst...Understanding the complex interactions between human activities and ecosystem functions is a prerequisite for achieving sustainable development.Since the implementation of the“Grain for Green”Project in 1999,ecosystem functions in China’s Loess Plateau have significantly improved.However,intensified human activities have also exacerbated the pressures on the region’s fragile ecological environment.This study investigates the spatiotemporal variations in the human activity intensity index(HAI)and net ecosystem benefits(NEB)from 2000 to 2020,using expert-based assessments and an enhanced cost-benefit evaluation framework.Results indicate that HAI increased by 16.7% and 16.6% at the grid and county levels,respectively.NEB exhibited pronounced spatial heterogeneity,with a total increase of USD 36.2 trillion at the grid scale.At the county level,the average NEB rose by 75%.The degree of trade-off was higher at the grid scale than at the county scale,while the synergistic areas initially expanded and then declined at both scales.Key areas for improvement and regions of lagging development were identified as priority zones for ecological management and spatial planning at both spatial resolutions.This study offers scientific insights and practical guidance for harmonizing ecological conservation with high-quality development in ecologically vulnerable regions.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
Latest digital advancements have intensified the necessity for adaptive,data-driven and socially-centered learning ecosystems.This paper presents the formulation of a cross-platform,innovative,gamified and personalize...Latest digital advancements have intensified the necessity for adaptive,data-driven and socially-centered learning ecosystems.This paper presents the formulation of a cross-platform,innovative,gamified and personalized Learning Ecosystem,which integrates 3D/VR environments,as well as machine learning algorithms,and business intelligence frameworks to enhance learner-centered education and inferenced decision-making.This Learning System makes use of immersive,analytically assessed virtual learning spaces,therefore facilitating real-time monitoring of not just learning performance,but also overall engagement and behavioral patterns,via a comprehensive set of sustainability-oriented ESG-aligned Key Performance Indicators(KPIs).Machine learning models support predictive analysis,personalized feedback,and hybrid recommendation mechanisms,whilst dedicated dashboards translate complex educational data into actionable insights for all Use Cases of the System(Educational Institutions,Educators and Learners).Additionally,the presented Learning System introduces a structured Mentoring and Consulting Subsystem,thence reinforcing human-centered guidance alongside automated intelligence.The Platform’s modular architecture and simulation-centered evaluation approach actively support personalized,and continuously optimized learning pathways.Thence,it exemplifies a mature,adaptive Learning Ecosystem,supporting immersive technologies,analytics,and pedagogical support,hence,contributing to contemporary digital learning innovation and sociotechnical transformation in education.展开更多
A comprehensive assessment of grain supply,demand,and ecosystem service flows is essential for identifying grain movement pathways,ensuring regional grain security,and guiding sustainable management strategies.However...A comprehensive assessment of grain supply,demand,and ecosystem service flows is essential for identifying grain movement pathways,ensuring regional grain security,and guiding sustainable management strategies.However,current studies primarily focus on short-term grain provision services while neglecting the spatiotemporal variations in grain flows across different scales.This gap limits the identification of dynamic matching relationships and the formulation of optimization strategies for balancing grain flows.This study examined the spatiotemporal evolution of grain supply and demand in the Beijing-Tianjin-Hebei(BTH)region from 1980 to 2020.Using the Enhanced TwoStep Floating Catchment Area method,the grain provision ecosystem service flows were quantified,the changes in supply–demand matching under different grain flow scenarios were analyzed and the optimal distance threshold for grain flows was investigated.The results revealed that grain production follows a spatial distribution pattern characterized by high levels in the southeast and low levels in the northwest.A significant mismatch exists between supply and demand,and it shows a scale effect.Deficit areas are mainly concentrated in the northwest,while surplus areas are mainly located in the central and southern regions.As the spatial scale increases,the ecosystem service supply–demand ratio(SDR)classification becomes more clustered,while it exhibits greater spatial SDR heterogeneity at smaller scales.This study examined two distinct scenarios of grain provision ecosystem service flow dynamics based on 100 and 200 km distance thresholds.The flow increased significantly,from 2.17 to 11.81million tons in the first scenario and from 2.41 to 12.37 million tons in the second scenario over nearly 40 years,forming a spatial movement pattern from the central and southern regions to the surrounding areas.Large flows were mainly concentrated in the interior of urban centers,with significant outflows between cities such as Baoding,Shijiazhuang,Xingtai,and Hengshui.At the county scale,supply–demand matching patterns remained consistent between the grain flows in the two scenarios.Notably,incorporating grain flow dynamics significantly reduced the number of grain-deficit areas compared to scenarios without grain flow.In 2020,grain-deficit counties decreased by28.79 and 37.88%,and cities by 12.50 and 25.0%under the two scenarios,respectively.Furthermore,the distance threshold for achieving optimal supply and demand matching at the county scale was longer than at the city scale in both grain flow scenarios.This study provides valuable insights into the dynamic relationships and heterogeneous patterns of grain matching,and expands the research perspective on grain and ecosystem service flows across various spatiotemporal scales.展开更多
Ecosystems along the eastern margin of the Qinghai-Tibet Plateau(EQTP)are highly fragile and extremely sensitive to climate change and human disturbances.To quantitatively assess climate-induced ecosystem responses,th...Ecosystems along the eastern margin of the Qinghai-Tibet Plateau(EQTP)are highly fragile and extremely sensitive to climate change and human disturbances.To quantitatively assess climate-induced ecosystem responses,this study proposes a Climate-Induced Productivity Index(CIPI)based on the Super Slack-Based Measure(Super-SBM)model using remote sensing data from 2001 to 2020.The results reveal persistently low CIPI values(0.47-0.53)across major ecosystem types,indicating widespread vulnerability to climatic variability.Among these ecosystems,forests exhibit the highest CIPI(0.55),followed by shrublands(0.54),croplands(0.53),grasslands(0.51),and barelands(0.43).The Theil index analysis further demonstrates significant intra-group disparities,suggesting that extreme climatic events amplify CIPI heterogeneity.Moreover,the dominant environmental drivers differ among ecosystem types:the Palmer Drought Severity Index(PDSI)primarily constrains grassland productivity,solar radiation(SRAD)strongly influences shrub and cropland systems,whereas subsurface factors exert greater control in forested regions.This study provides a quantitative framework for evaluating climate-ecosystem interactions and offers a scientific basis for long-term ecological monitoring and security planning across the EQTP.展开更多
The United Nations Sustainable Development Goal(SDG) 2 aims to achieve Zero Hunger by 2030.However,global hunger and food insecurity have continued to rise at an alarming rate(UN 2023).Subtropical regions are home to ...The United Nations Sustainable Development Goal(SDG) 2 aims to achieve Zero Hunger by 2030.However,global hunger and food insecurity have continued to rise at an alarming rate(UN 2023).Subtropical regions are home to more than 30% of the world's population,predominantly in developing countries where per capita farmland and food supply are only 40% of those in developed nations(FAO 2018).Meeting the Zero Hunger target amid ongoing population growth in these regions requires a substantial increase in agricultural production while minimizing soil degradation and adverse ecological impacts.This challenge is shared by many countries across South Asia,Africa,and Central and South America.展开更多
Vegetation in terrestrial ecosystems as a carbon sink is a crucial factor in mitigating global warming and reaching carbon neutrality targets,although the drivers of net ecosystem productivity(NEP)under combined human...Vegetation in terrestrial ecosystems as a carbon sink is a crucial factor in mitigating global warming and reaching carbon neutrality targets,although the drivers of net ecosystem productivity(NEP)under combined human and environmental pressures remain poorly understood.In this study,we analyzed the spatiotemporal evolution of NEP in the Horqin Sandy Land,China from 2000 to 2020,and observed the variation in NEP across different land use types.We further identified and quantified the effects of human activities,topographical features,climatic conditions,and soil properties on NEP through the application of structural equation modeling(SEM)and boosted regression trees(BRT).The results showed that the multi-year average NEP ranged from–137.79 to 461.96 g C/m^(2) in the Horqin Sandy Land,with 88.21%of the area showing a significant increasing trend.Among different land use types,forestland exhibited the highest NEP values,followed by cropland,grassland,impervious land,and unused land.The NEP in carbon sink areas was primarily regulated by potential evapotranspiration(negatively correlated)and precipitation(positively correlated).Slope was identified as the most significant positive determinant in carbon source areas.Forestland exhibited climate–topography interactions driving NEP,whereas cropland and grassland relied on temperature;unused land and impervious land were susceptible to land use/cover change and human footprint.This study has significant implications for maintaining the carbon sink function and promoting ecological engineering programs that aim to enhance the capacity of terrestrial carbon sinks in the semi-arid agro-pastoral ecotone.展开更多
With the rapid development of Open-Source(OS),more and more software projects are maintained and developed in the form of OS.These Open-Source projects depend on and influence each other,gradually forming a huge OS pr...With the rapid development of Open-Source(OS),more and more software projects are maintained and developed in the form of OS.These Open-Source projects depend on and influence each other,gradually forming a huge OS project network,namely an Open-Source Software ECOsystem(OSSECO).Unfortunately,not all OS projects in the open-source ecosystem can be healthy and stable in the long term,and more projects will go from active to inactive and gradually die.In a tightly connected ecosystem,the death of one project can potentially cause the collapse of the entire ecosystem network.How can we effectively prevent such situations from happening?In this paper,we first identify the basic project characteristics that affect the survival of OS projects at both project and ecosystem levels through the proportional hazards model.Then,we utilize graph convolutional networks based on the ecosystem network to extract the ecosystem environment characteristics of OS projects.Finally,we fuse basic project characteristics and environmental project characteristics and construct a Hybrid Structured Prediction Model(HSPM)to predict the OS project survival state.The experimental results show that HSPM significantly improved compared to the traditional prediction model.Our work can substantially assist OS project managers in maintaining their projects’health.It can also provide an essential reference for developers when choosing the right open-source project for their production activities.展开更多
We present a high performance modularly-built open-source software-OpenIFEM.OpenIFEM is a C++implementation of the modified immersed finite element method(mIFEM)to solve fluid-structure interaction(FSI)problems.This s...We present a high performance modularly-built open-source software-OpenIFEM.OpenIFEM is a C++implementation of the modified immersed finite element method(mIFEM)to solve fluid-structure interaction(FSI)problems.This software is modularly built to perform multiple tasks including fluid dynamics(incompressible and slightly compressible fluid models),linear and nonlinear solid mechanics,and fully coupled fluid-structure interactions.Most of open-source software packages are restricted to certain discretization methods;some are under-tested,under-documented,and lack modularity as well as extensibility.OpenIFEM is designed and built to include a set of generic classes for users to adapt so that any fluid and solid solvers can be coupled through the FSI algorithm.In addition,the package utilizes well-developed and tested libraries.It also comes with standard test cases that serve as software and algorithm validation.The software can be built on cross-platform,i.e.,Linux,Windows,and Mac OS,using CMake.Efficient parallelization is also implemented for high-performance computing for large-sized problems.OpenIFEM is documented using Doxygen and publicly available to download on GitHub.It is expected to benefit the future development of FSI algorithms and be applied to a variety of FSI applications.展开更多
Topology optimization(TO),a numerical technique to find the optimalmaterial layoutwith a given design domain,has attracted interest from researchers in the field of structural optimization in recent years.For beginner...Topology optimization(TO),a numerical technique to find the optimalmaterial layoutwith a given design domain,has attracted interest from researchers in the field of structural optimization in recent years.For beginners,opensource codes are undoubtedly the best alternative to learning TO,which can elaborate the implementation of a method in detail and easily engage more people to employ and extend the method.In this paper,we present a summary of various open-source codes and related literature on TO methods,including solid isotropic material with penalization(SIMP),evolutionary method,level set method(LSM),moving morphable components/voids(MMC/MMV)methods,multiscale topology optimization method,etc.Simultaneously,we classify the codes into five levels,fromeasy to difficult,depending on their difficulty,so that beginners can get started and understand the form of code implementation more quickly.展开更多
Scientific research requires the collection of data in order to study, monitor, analyze, describe, or understand a particular process or event. Data collection efforts are often a compromise: manual measurements can b...Scientific research requires the collection of data in order to study, monitor, analyze, describe, or understand a particular process or event. Data collection efforts are often a compromise: manual measurements can be time-consuming and labor-intensive, resulting in data being collected at a low frequency, while automating the data-collection process can reduce labor requirements and increase the frequency of measurements, but at the cost of added expense of electronic data-collecting instrumentation. Rapid advances in electronic technologies have resulted in a variety of new and inexpensive sensing, monitoring, and control capabilities which offer opportunities for implementation in agricultural and natural-resource research applications. An Open Source Hardware project called Arduino consists of a programmable microcontroller development platform, expansion capability through add-on boards, and a programming development environment for creating custom microcontroller software. All circuit-board and electronic component specifications, as well as the programming software, are open-source and freely available for anyone to use or modify. Inexpensive sensors and the Arduino development platform were used to develop several inexpensive, automated sensing and datalogging systems for use in agricultural and natural-resources related research projects. Systems were developed and implemented to monitor soil-moisture status of field crops for irrigation scheduling and crop-water use studies, to measure daily evaporation-pan water levels for quantifying evaporative demand, and to monitor environmental parameters under forested conditions. These studies demonstrate the usefulness of automated measurements, and offer guidance for other researchers in developing inexpensive sensing and monitoring systems to further their research.展开更多
Resource-scarce regions with serious COVID-19 outbreaks do not have enough ventilators to support critically ill patients,and these shortages are especially devastating in developing countries.To help alleviate this s...Resource-scarce regions with serious COVID-19 outbreaks do not have enough ventilators to support critically ill patients,and these shortages are especially devastating in developing countries.To help alleviate this strain,we have designed and tested the accessible low-barrier in vivo-validated economical ventilator(ALIVE Vent),a COVID-19-inspired,cost-effective,open-source,in vivo-validated solution made from commercially available components.The ALIVE Vent operates using compressed oxygen and air to drive inspiration,while two solenoid valves ensure one-way flow and precise cycle timing.The device was functionally tested and profiled using a variable resistance and compliance artificial lung and validated in anesthetized large animals.Our functional test results revealed its effective operation under a wide variety of ventilation conditions defined by the American Association of Respiratory Care guidelines for ventilator stockpiling.The large animal test showed that our ventilator performed similarly if not better than a standard ventilator in maintaining optimal ventilation status.The FiO2,respiratory rate,inspiratory to expiratory time ratio,positive-end expiratory pressure,and peak inspiratory pressure were successfully maintained within normal,clinically validated ranges,and the animals were recovered without any complications.In regions with limited access to ventilators,the ALIVE Vent can help alleviate shortages,and we have ensured that all used materials are publicly available.While this pandemic has elucidated enormous global inequalities in healthcare,innovative,cost-effective solutions aimed at reducing socio-economic barriers,such as the ALIVE Vent,can help enable access to prompt healthcare and life saving technology on a global scale and beyond COVID-19.展开更多
基金supported in part by the National Natural Science Foundation of China(52172377).
文摘An effective energy management strategy(EMS)is essential to optimize the energy efficiency of electric vehicles(EVs).With the advent of advanced machine learning techniques,the focus on developing sophisticated EMS for EVs is increasing.Here,we introduce LearningEMS:a unified framework and open-source benchmark designed to facilitate rapid development and assessment of EMS.LearningEMS is distinguished by its ability to support a variety of EV configurations,including hybrid EVs,fuel cell EVs,and plug-in EVs,offering a general platform for the development of EMS.The framework enables detailed comparisons of several EMS algorithms,encompassing imitation learning,deep reinforcement learning(RL),offline RL,model predictive control,and dynamic programming.We rigorously evaluated these algorithms across multiple perspectives:energy efficiency,consistency,adaptability,and practicability.Furthermore,we discuss state,reward,and action settings for RL in EV energy management,introduce a policy extraction and reconstruction method for learning-based EMS deployment,and conduct hardware-in-the-loop experiments.In summary,we offer a unified and comprehensive framework that comes with three distinct EV platforms,over 10000 km of EMS policy data set,ten state-of-the-art algorithms,and over 160 benchmark tasks,along with three learning libraries.Its flexible design allows easy expansion for additional tasks and applications.The open-source algorithms,models,data sets,and deployment processes foster additional research and innovation in EV and broader engineering domains.
文摘In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation is provided”and that“the validation step is largely overlooked”.This assertion may have been true several years ago,for example,when Ochoa and Urbina-Cardona(2017)made a similar observation.However,there has been much work on ES model validation over the last decade.
基金Supported by the National Key R&D Program of China(No.2022YFD2401301)the Primary Research and Development Plan of Guangxi Province(No.GuiKe AB21220064)+1 种基金the National Natural Science Foundation of China(Nos.42106102,42306151)the Shandong Postdoctoral Science Foundation(No.SDCXZG202301009)。
文摘Marine pollution and overfishing induced the biodiversity loss and ecological degradation of the Beibu Gulf ecosystem in Guangxi,SE China.In an effort to restore the ecosystem and fishery resources,artificial reefs were deployed in the Beibu Gulf as the marine ranching area and their ecological performance need to be investigated.We constructed Ecopath ecological trophic models for the marine ranching area and a nearby control area to compare their ecosystem throughput and food web structure difference,and to calculate the ecological carrying capacity of various functional groups.Results indicate that the total system throughput of the marine ranching area was significantly higher than the control area,and the majority of system throughput occurred at trophic levelsⅠandⅡin both ecosystems.The system connectance indices for the marine ranching and control areas were 0.27 and 0.32,and the omnivory indices were 0.16 and 0.19,indicating simple food web structures;both areas are in a developmental stage with TPP/TR ratios of 2.69 and 9.36,respectively.Compared to the control area,marine ranching area exhibited a higher system maturity,and the ecological carrying capacity of“large and medium-sized demersal fish”and“other bivalves”functional groups in the marine ranching area increased by 43.83%and 233.62%,respectively,allowing for more high-trophic-level predators and large benthic animals.This study provided a reference for the formulation of fishery management policies in the Beibu Gulf,to maintain ecosystem stability and biodiversity.
基金supported by the National Natural Science Foundation of China(Grants No.42522105 and 42171088)the 111 Project of China(Grant No.B23027)the Fundamental Research Funds for the Central Universities of China.
文摘Resilience plays a crucial role in maintaining desirable ecosystem states and is a key objective of sustainable ecosystem management.This study synthesizes the concepts and measurement approaches of terrestrial ecosystem resilience and expounded on its spatio-temporal changes and influencing factors based on the literature over the past 50 years.Arid regions exhibited the lowest levels of spatial resilience,and the global ecosystem resilience showed a downward trend.In the focal regions,ecological resilience in Amazonian and Southeast Asian rainforest regions declined primarily driven by human activities such as deforestation and cropland expansion.Precipitation and temperature exerted bidirectional influences the resilience of ecosystems,indicating that ecosystem responses to climatic factors were non-monotonic.Evidence concerning anthropogenic factors such as land management and deforestation on ecosystem resilience were predominantly negative.Overall,this study provides a comprehensive synthesis of large scale terrestrial ecosystem resilience assessments,offering valuable insights for ecosystem protection and restoration policy development.
基金supported by the National Key Research and Development Program of China (2022YFF1300705)the Key Research and Development Project of Guangxi,China (Guike AB24010051)+1 种基金the National Natural Science Foundation of China (42261011,32271730 and U20A2011)the Central Public Welfare Research Institutes,Chinese Academy of Geological Sciences (2023020)。
文摘Phosphorus (P) is an essential nutrient element that is critical for plant growth and ecosystem functionality.The soil P cycle plays multiple roles,such as sustaining plant growth and productivity,regulating nutrient balance within ecosystems,and enhancing ecosystem adaptability and resilience.This cycle is influenced by factors such as the restoration approach and microbial community dynamics.However,the extent to which the restoration approach alters the P cycle in karst ecosystems and the underlying microbial mechanisms remain poorly understood.The P-cycle multifunctionality index (P-cycle MFI) serves as a comprehensive indicator for evaluating soil P cycle function,and it provides insights into changes in the P cycle between different restoration approaches.To investigate the shifts in soil P-cycle MFI and microbial mechanisms between different restoration approaches,we analyzed soil available P (AP),total P (TP),microbial biomass P (MBP),and the activities of acid phosphatase (ACP) and alkaline phosphatase (ALP).These data were used to calculate the P-cycle MFI by averaging the Z-scores between two restoration approaches(artificial restoration of forest (AF) and natural restoration of forest (NF)) and a control (cropland,CP) at six subtropical karst ecosystem sites in China.We also determined the soil organic carbon (SOC),exchangeable calcium (Ca) and magnesium (Mg),pH,bulk density (BD),microbial biomass C (MBC),and microbial biomass nitrogen (MBN),as well as the community structure,relative abundance,diversity indices,and co-occurrence networks of phoD-harboring bacteria.The results showed that the community structure of phoD-harboring bacteria varied significantly among AF,NF,and CP and across different temperature gradients.These bacteria exhibited increasing complexity and tightness in co-occurrence networks from CP to AF and then to NF,along with the ACP and ALP activities,but not the TP and AP contents.The P-cycle MFI values were significantly higher in NF compared to AF and CP,and the variation was significantly explained by restoration approach,temperature,MBC,MBN,SOC,exchangeable Ca,BD,community structure of phoD-harboring bacteria,and exchangeable Mg.Furthermore,natural restoration had a more substantial impact on the P-cycle MFI than temperature by enhancing SOC,microbial biomass,the complexity and co-occurrence network tightness of the phoD-harboring bacterial community structure,and ACP and ALP activities,but it reduced soil BD.The rare genera of phoD-harboring bacteria significantly influenced the variation of soil P-cycle MFI compared to the dominant genera.This study highlights the importance of rare genera of phoD-harboring bacteria in driving soil P-cycle multifunctionality in karst ecosystems,with natural restoration being more effective than artificial methods for enhancing soil organic matter and microbial community complexity.
基金supported by the National Key Research and Development Program of China(2025YFE0103800,2023YFE0102600,2024YFE0214200).
文摘Livestock farming is a critical pillar of Tajikistan’s national economy and livelihood security.However,significant economic challenges in the country have led to the degradation of grassland ecosystems.This degradation has not only reduced the productivity of grassland ecosystems but also severely impacted their ecological functions.A particularly concerning consequence is the threat to biodiversity,as the survival and persistence of endemic,rare,and endangered plant species are at serious risk,thereby diminishing the value of species’genetic resources.Based on the data from multiple sources such as literature reviews,field observations,and national statistics,this study employed a systematic literature review and meta-analysis to investigate the current status,causes of degradation,and restoration measures for grassland ecosystems in Tajikistan.The results revealed that Tajikistan’s grassland ecosystems support exceptionally high plant species diversity,comprising over 4500 vascular plant species,including nearly 1500 endemic and sub-endemic taxa that constitute a unique genetic reservoir.These ecosystems are experiencing severe degradation,characterized by significantly reduced vegetation cover and declining species richness.Palatable forage species are increasingly being displaced by unpalatable,thorny,and poisonous species.The primary drivers of degradation include excessive grazing pressure,which disrupts plant reproductive cycles and regeneration capacity,habitat fragmentation due to urbanization and infrastructure development,and uncontrolled exploitation of medicinal and edible plants.Climate change,particularly rising temperatures and altered precipitation patterns,further exacerbates these anthropogenic pressures.Ecological restoration experiments suggested that both ecosystem productivity and plant species diversity are significantly enhanced by systematic reseeding trials using altitude-adapted native species.These findings underscore the necessity of establishing scientifically grounded approaches for ecological restoration.
基金support through the“Trans-Disciplinary Research”Grant(No.R/Dev/IoE/TDRProjects/2023-24/61658),which played a crucial role in enabling this research endeavor.
文摘Floodplain wetlands are invaluable ecosystems providing numerous ecological benefits,yet they face a global crisis necessitating sustainable preservation efforts.This study examines the depletion of floodplain wetlands within the Hastinapur Wildlife Sanctuary(HWLS)in Uttar Pradesh.Encroachment activities such as grazing,agriculture,and human settlements have fragmented and degraded critical wetland ecosystems.Additionally,irrigation projects,dam construction,and water diversion have disrupted natural water flow and availability.To assess wetland inundation in 2023,five classification techniques were employed:Random Forest(RF),Support Vector Machine(SVM),artificial neural network(ANN),Spectral Information Divergence(SID),and Maximum Likelihood Classifier(MLC).SVM emerged as the most precise method,as determined by kappa coefficient and index-based validation.Consequently,the SVM classifier was used to model wetland inundation areas from 1983 to 2023 and analyze spatiotemporal changes and fragmentation patterns.The findings revealed that the SVM clas-sifier accurately mapped 2023 wetland areas.The modeled time-series data demonstrated a 62.55%and 38.12%reduction in inundated wetland areas over the past 40 years in the pre-and post-monsoon periods,respectively.Fragmentation analysis indicated an 86.27%decrease in large core wetland areas in the pre-monsoon period,signifying severe habitat degradation.This rapid decline in wetlands within protected areas raises concerns about their ecological impacts.By linking wetland loss to global sustainability objectives,this study underscores the global urgency for strengthened wetland protection measures and highlights the need for integrating wetland conservation into broader sustainable development goals.Effective policies and adaptive management strategies are crucial for preserving these ecosystems and their vital services,which are essential for biodiversity,climate regulation,and human well-being.
文摘Arid and semi-arid ecosystems are prone to extensive fires due to specific climatic conditions,sparse vegetation cover,and high density of fine fuels.Understanding the flammability characteristics of land covers is essential for fire management and designing land restoration programs in arid and semi-arid ecosystems.This study provided a new approach to evaluate the flammability of shrublands and woodlands using flammability indices(FIs)including time to ignition(TI),duration of combustion(DC),and flame height(FH)of plant species and their relative frequencies in the Dalfard Basin of southeastern Iran.The results showed that there was a significant difference in FIs between land covers.Shrublands had higher flammability potential compared with woodlands.Plant moisture content had a negative relationship with TI(P<0.010)and no significant relationship with DC and FH(P>0.050).Artemisia spp.,Astragalus gossypinus Fischer,Amygdalus scoparia Spach,and Cymbopogon jwarancusa(Jones)Schult.had the highest FI.Tree species such as Rhazya stricta Decne.,and Pistacia atlantica Desf.showed greater resistance to fire.Using principal component analysis,the relationship between species and FIs was examined,and TI of wet fuel was the most important FI in relation to species.Structural equation model showed that life form(P<0.001)was the most important flammability driver.Precipitation(P<0.010)and legume species(P<0.010)were significantly related to the flammability in arid land.This study emphasizes the importance of managing high-risk species and using resistant species in vegetation restoration and shows that combining species FIs with their abundance is an effective tool for assessing fire risk and fuel management at the plant community scale.
基金National Natural Science Foundation of China(Grant No.U2243225)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB40000000)+2 种基金the Natural Science Basic Research Program of Shaanxi(Grant No.Z2024-ZYFS-0065)the Funding of Top Young talents of Ten Thousand talents Plan in China(2021)the Fundamental Research Funds for the Central Universities(Grants No.2452023071 and 2023HHZX002).
文摘Understanding the complex interactions between human activities and ecosystem functions is a prerequisite for achieving sustainable development.Since the implementation of the“Grain for Green”Project in 1999,ecosystem functions in China’s Loess Plateau have significantly improved.However,intensified human activities have also exacerbated the pressures on the region’s fragile ecological environment.This study investigates the spatiotemporal variations in the human activity intensity index(HAI)and net ecosystem benefits(NEB)from 2000 to 2020,using expert-based assessments and an enhanced cost-benefit evaluation framework.Results indicate that HAI increased by 16.7% and 16.6% at the grid and county levels,respectively.NEB exhibited pronounced spatial heterogeneity,with a total increase of USD 36.2 trillion at the grid scale.At the county level,the average NEB rose by 75%.The degree of trade-off was higher at the grid scale than at the county scale,while the synergistic areas initially expanded and then declined at both scales.Key areas for improvement and regions of lagging development were identified as priority zones for ecological management and spatial planning at both spatial resolutions.This study offers scientific insights and practical guidance for harmonizing ecological conservation with high-quality development in ecologically vulnerable regions.
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.
文摘Latest digital advancements have intensified the necessity for adaptive,data-driven and socially-centered learning ecosystems.This paper presents the formulation of a cross-platform,innovative,gamified and personalized Learning Ecosystem,which integrates 3D/VR environments,as well as machine learning algorithms,and business intelligence frameworks to enhance learner-centered education and inferenced decision-making.This Learning System makes use of immersive,analytically assessed virtual learning spaces,therefore facilitating real-time monitoring of not just learning performance,but also overall engagement and behavioral patterns,via a comprehensive set of sustainability-oriented ESG-aligned Key Performance Indicators(KPIs).Machine learning models support predictive analysis,personalized feedback,and hybrid recommendation mechanisms,whilst dedicated dashboards translate complex educational data into actionable insights for all Use Cases of the System(Educational Institutions,Educators and Learners).Additionally,the presented Learning System introduces a structured Mentoring and Consulting Subsystem,thence reinforcing human-centered guidance alongside automated intelligence.The Platform’s modular architecture and simulation-centered evaluation approach actively support personalized,and continuously optimized learning pathways.Thence,it exemplifies a mature,adaptive Learning Ecosystem,supporting immersive technologies,analytics,and pedagogical support,hence,contributing to contemporary digital learning innovation and sociotechnical transformation in education.
基金supported by the National Natural Science Foundation of China(42471336,52379021 and 42201278)the Hebei Province Backbone Talent Program,China(Returnee Platform for Overseas Study)(A20240028)+2 种基金the Hebei Province Statistical Science Research Project,China(2024HZ04)the Hebei Province Graduate Education and Teaching Reform Research Project,China(YJG2024046)the Innovation Ability Training Program for Postgraduate Students of Hebei Provincial Department of Education,China(CXZZSS2025048)。
文摘A comprehensive assessment of grain supply,demand,and ecosystem service flows is essential for identifying grain movement pathways,ensuring regional grain security,and guiding sustainable management strategies.However,current studies primarily focus on short-term grain provision services while neglecting the spatiotemporal variations in grain flows across different scales.This gap limits the identification of dynamic matching relationships and the formulation of optimization strategies for balancing grain flows.This study examined the spatiotemporal evolution of grain supply and demand in the Beijing-Tianjin-Hebei(BTH)region from 1980 to 2020.Using the Enhanced TwoStep Floating Catchment Area method,the grain provision ecosystem service flows were quantified,the changes in supply–demand matching under different grain flow scenarios were analyzed and the optimal distance threshold for grain flows was investigated.The results revealed that grain production follows a spatial distribution pattern characterized by high levels in the southeast and low levels in the northwest.A significant mismatch exists between supply and demand,and it shows a scale effect.Deficit areas are mainly concentrated in the northwest,while surplus areas are mainly located in the central and southern regions.As the spatial scale increases,the ecosystem service supply–demand ratio(SDR)classification becomes more clustered,while it exhibits greater spatial SDR heterogeneity at smaller scales.This study examined two distinct scenarios of grain provision ecosystem service flow dynamics based on 100 and 200 km distance thresholds.The flow increased significantly,from 2.17 to 11.81million tons in the first scenario and from 2.41 to 12.37 million tons in the second scenario over nearly 40 years,forming a spatial movement pattern from the central and southern regions to the surrounding areas.Large flows were mainly concentrated in the interior of urban centers,with significant outflows between cities such as Baoding,Shijiazhuang,Xingtai,and Hengshui.At the county scale,supply–demand matching patterns remained consistent between the grain flows in the two scenarios.Notably,incorporating grain flow dynamics significantly reduced the number of grain-deficit areas compared to scenarios without grain flow.In 2020,grain-deficit counties decreased by28.79 and 37.88%,and cities by 12.50 and 25.0%under the two scenarios,respectively.Furthermore,the distance threshold for achieving optimal supply and demand matching at the county scale was longer than at the city scale in both grain flow scenarios.This study provides valuable insights into the dynamic relationships and heterogeneous patterns of grain matching,and expands the research perspective on grain and ecosystem service flows across various spatiotemporal scales.
基金National Key R&D Program of China,No.2022YFF1302401National Natural Science Foundation of China,No.42271007。
文摘Ecosystems along the eastern margin of the Qinghai-Tibet Plateau(EQTP)are highly fragile and extremely sensitive to climate change and human disturbances.To quantitatively assess climate-induced ecosystem responses,this study proposes a Climate-Induced Productivity Index(CIPI)based on the Super Slack-Based Measure(Super-SBM)model using remote sensing data from 2001 to 2020.The results reveal persistently low CIPI values(0.47-0.53)across major ecosystem types,indicating widespread vulnerability to climatic variability.Among these ecosystems,forests exhibit the highest CIPI(0.55),followed by shrublands(0.54),croplands(0.53),grasslands(0.51),and barelands(0.43).The Theil index analysis further demonstrates significant intra-group disparities,suggesting that extreme climatic events amplify CIPI heterogeneity.Moreover,the dominant environmental drivers differ among ecosystem types:the Palmer Drought Severity Index(PDSI)primarily constrains grassland productivity,solar radiation(SRAD)strongly influences shrub and cropland systems,whereas subsurface factors exert greater control in forested regions.This study provides a quantitative framework for evaluating climate-ecosystem interactions and offers a scientific basis for long-term ecological monitoring and security planning across the EQTP.
文摘The United Nations Sustainable Development Goal(SDG) 2 aims to achieve Zero Hunger by 2030.However,global hunger and food insecurity have continued to rise at an alarming rate(UN 2023).Subtropical regions are home to more than 30% of the world's population,predominantly in developing countries where per capita farmland and food supply are only 40% of those in developed nations(FAO 2018).Meeting the Zero Hunger target amid ongoing population growth in these regions requires a substantial increase in agricultural production while minimizing soil degradation and adverse ecological impacts.This challenge is shared by many countries across South Asia,Africa,and Central and South America.
基金funded by the National Major Science and Technology Program for Water Pollution Control and Treatment(2017ZX07101-002)the Discipline Construction Program of ZHANG Huayong,Distinguished Professor of School of Life Sciences,Shandong University(61200082363001).
文摘Vegetation in terrestrial ecosystems as a carbon sink is a crucial factor in mitigating global warming and reaching carbon neutrality targets,although the drivers of net ecosystem productivity(NEP)under combined human and environmental pressures remain poorly understood.In this study,we analyzed the spatiotemporal evolution of NEP in the Horqin Sandy Land,China from 2000 to 2020,and observed the variation in NEP across different land use types.We further identified and quantified the effects of human activities,topographical features,climatic conditions,and soil properties on NEP through the application of structural equation modeling(SEM)and boosted regression trees(BRT).The results showed that the multi-year average NEP ranged from–137.79 to 461.96 g C/m^(2) in the Horqin Sandy Land,with 88.21%of the area showing a significant increasing trend.Among different land use types,forestland exhibited the highest NEP values,followed by cropland,grassland,impervious land,and unused land.The NEP in carbon sink areas was primarily regulated by potential evapotranspiration(negatively correlated)and precipitation(positively correlated).Slope was identified as the most significant positive determinant in carbon source areas.Forestland exhibited climate–topography interactions driving NEP,whereas cropland and grassland relied on temperature;unused land and impervious land were susceptible to land use/cover change and human footprint.This study has significant implications for maintaining the carbon sink function and promoting ecological engineering programs that aim to enhance the capacity of terrestrial carbon sinks in the semi-arid agro-pastoral ecotone.
基金This work was supported by the National Social Science Foundation(NSSF)Research on intelligent recommendation of multi-modal resources for children’s graded reading in smart library(22BTQ033)the Science and Technology Research and Development Program Project of China railway group limited(Project No.2021-Special-08).
文摘With the rapid development of Open-Source(OS),more and more software projects are maintained and developed in the form of OS.These Open-Source projects depend on and influence each other,gradually forming a huge OS project network,namely an Open-Source Software ECOsystem(OSSECO).Unfortunately,not all OS projects in the open-source ecosystem can be healthy and stable in the long term,and more projects will go from active to inactive and gradually die.In a tightly connected ecosystem,the death of one project can potentially cause the collapse of the entire ecosystem network.How can we effectively prevent such situations from happening?In this paper,we first identify the basic project characteristics that affect the survival of OS projects at both project and ecosystem levels through the proportional hazards model.Then,we utilize graph convolutional networks based on the ecosystem network to extract the ecosystem environment characteristics of OS projects.Finally,we fuse basic project characteristics and environmental project characteristics and construct a Hybrid Structured Prediction Model(HSPM)to predict the OS project survival state.The experimental results show that HSPM significantly improved compared to the traditional prediction model.Our work can substantially assist OS project managers in maintaining their projects’health.It can also provide an essential reference for developers when choosing the right open-source project for their production activities.
文摘We present a high performance modularly-built open-source software-OpenIFEM.OpenIFEM is a C++implementation of the modified immersed finite element method(mIFEM)to solve fluid-structure interaction(FSI)problems.This software is modularly built to perform multiple tasks including fluid dynamics(incompressible and slightly compressible fluid models),linear and nonlinear solid mechanics,and fully coupled fluid-structure interactions.Most of open-source software packages are restricted to certain discretization methods;some are under-tested,under-documented,and lack modularity as well as extensibility.OpenIFEM is designed and built to include a set of generic classes for users to adapt so that any fluid and solid solvers can be coupled through the FSI algorithm.In addition,the package utilizes well-developed and tested libraries.It also comes with standard test cases that serve as software and algorithm validation.The software can be built on cross-platform,i.e.,Linux,Windows,and Mac OS,using CMake.Efficient parallelization is also implemented for high-performance computing for large-sized problems.OpenIFEM is documented using Doxygen and publicly available to download on GitHub.It is expected to benefit the future development of FSI algorithms and be applied to a variety of FSI applications.
基金supported by the National Key R&D Program of China[Grant Number 2020YFB1708300]the National Natural Science Foundation of China[Grant Number 52075184].
文摘Topology optimization(TO),a numerical technique to find the optimalmaterial layoutwith a given design domain,has attracted interest from researchers in the field of structural optimization in recent years.For beginners,opensource codes are undoubtedly the best alternative to learning TO,which can elaborate the implementation of a method in detail and easily engage more people to employ and extend the method.In this paper,we present a summary of various open-source codes and related literature on TO methods,including solid isotropic material with penalization(SIMP),evolutionary method,level set method(LSM),moving morphable components/voids(MMC/MMV)methods,multiscale topology optimization method,etc.Simultaneously,we classify the codes into five levels,fromeasy to difficult,depending on their difficulty,so that beginners can get started and understand the form of code implementation more quickly.
文摘Scientific research requires the collection of data in order to study, monitor, analyze, describe, or understand a particular process or event. Data collection efforts are often a compromise: manual measurements can be time-consuming and labor-intensive, resulting in data being collected at a low frequency, while automating the data-collection process can reduce labor requirements and increase the frequency of measurements, but at the cost of added expense of electronic data-collecting instrumentation. Rapid advances in electronic technologies have resulted in a variety of new and inexpensive sensing, monitoring, and control capabilities which offer opportunities for implementation in agricultural and natural-resource research applications. An Open Source Hardware project called Arduino consists of a programmable microcontroller development platform, expansion capability through add-on boards, and a programming development environment for creating custom microcontroller software. All circuit-board and electronic component specifications, as well as the programming software, are open-source and freely available for anyone to use or modify. Inexpensive sensors and the Arduino development platform were used to develop several inexpensive, automated sensing and datalogging systems for use in agricultural and natural-resources related research projects. Systems were developed and implemented to monitor soil-moisture status of field crops for irrigation scheduling and crop-water use studies, to measure daily evaporation-pan water levels for quantifying evaporative demand, and to monitor environmental parameters under forested conditions. These studies demonstrate the usefulness of automated measurements, and offer guidance for other researchers in developing inexpensive sensing and monitoring systems to further their research.
基金the National Institutes of Health(NIH R01 HL089315-01 and NIH R01 HL152155,YJW)the Thoracic Surgery Foundation Resident Research Fellowship(YZ)the National Science Foundation Graduate Research Fellowship Program(AMI).
文摘Resource-scarce regions with serious COVID-19 outbreaks do not have enough ventilators to support critically ill patients,and these shortages are especially devastating in developing countries.To help alleviate this strain,we have designed and tested the accessible low-barrier in vivo-validated economical ventilator(ALIVE Vent),a COVID-19-inspired,cost-effective,open-source,in vivo-validated solution made from commercially available components.The ALIVE Vent operates using compressed oxygen and air to drive inspiration,while two solenoid valves ensure one-way flow and precise cycle timing.The device was functionally tested and profiled using a variable resistance and compliance artificial lung and validated in anesthetized large animals.Our functional test results revealed its effective operation under a wide variety of ventilation conditions defined by the American Association of Respiratory Care guidelines for ventilator stockpiling.The large animal test showed that our ventilator performed similarly if not better than a standard ventilator in maintaining optimal ventilation status.The FiO2,respiratory rate,inspiratory to expiratory time ratio,positive-end expiratory pressure,and peak inspiratory pressure were successfully maintained within normal,clinically validated ranges,and the animals were recovered without any complications.In regions with limited access to ventilators,the ALIVE Vent can help alleviate shortages,and we have ensured that all used materials are publicly available.While this pandemic has elucidated enormous global inequalities in healthcare,innovative,cost-effective solutions aimed at reducing socio-economic barriers,such as the ALIVE Vent,can help enable access to prompt healthcare and life saving technology on a global scale and beyond COVID-19.
