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
With the rise of open-source software,the social development paradigm occupies an indispensable position in the current software development process.This paper puts forward a variant of the PageRank algorithm to build...With the rise of open-source software,the social development paradigm occupies an indispensable position in the current software development process.This paper puts forward a variant of the PageRank algorithm to build the importance assessment model,which provides quantifiable importance assessment metrics for new Java projects based on Java open-source projects or components.The critical point of the model is to use crawlers to obtain relevant information about Java open-source projects in the GitHub open-source community to build a domain knowledge graph.According to the three dimensions of the Java open-source project’s project influence,project activity and project popularity,the project is measured.A modified PageRank algorithm is proposed to construct the importance evaluation model.Thereby providing quantifiable importance evaluation indicators for new Java projects based on or components of Java open-source projects.This article evaluates the importance of 4512 Java open-source projects obtained on GitHub and has a good effect.展开更多
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
China and Laos are close neighbors with a long-standing friendship.Since the early 2000s,China has supported Laos'economic and social development through wide-ranging cooperation projects,all guided by the vision ...China and Laos are close neighbors with a long-standing friendship.Since the early 2000s,China has supported Laos'economic and social development through wide-ranging cooperation projects,all guided by the vision of a community with a shared future.As this vision takes deeper root,many aid projects have moved from blueprint to reality,delivering tangible benefits across towns and villages and improving the lives of ordinary Lao people while further strengthening bilateral ties.展开更多
Projections of future urban land change are essential for a range of sustainability assessments,including those related to biodiversity loss,carbon emissions,and agricultural land conversion.However,to what extent and...Projections of future urban land change are essential for a range of sustainability assessments,including those related to biodiversity loss,carbon emissions,and agricultural land conversion.However,to what extent and where current projections agree or disagree remains unknown.Here,we systematically compare existing global projections that are consistent with the Shared Socioeconomic Pathways.We find that the total global urban land area is expected to increase by 112%between 2020 and 2100(averaged across all projections),with a coefficient of variation of 0.81.This variation is mostly caused by the selection of the underlying drivers that are included in the different models.Regionally,the highest average growth rates are found in sub-Saharan Africa(+679%to+730%),while this region also has the highest variation across projections(coefficient of variation ranging from 2.02 to 2.18).When ranking scenarios within a study from the highest to the lowest projected increase in urban land,rankings are relatively similar for regions in the Global North,but not for regions in the Global South.The large disagreement across projections can lead to high uncertainties in assessments of future urban land change impacts,which can undermine the effectiveness of long-term planning,policymaking,and resource management decisions.展开更多
This study provides potential climate projections for Central Asia(CA)based on multi-regional climate model(RCM)outputs from the Coordinated Regional Climate Downscaling Experiment for Central Asia(CORDEX-CAII).Despit...This study provides potential climate projections for Central Asia(CA)based on multi-regional climate model(RCM)outputs from the Coordinated Regional Climate Downscaling Experiment for Central Asia(CORDEX-CAII).Despite some systematic biases,all RCMs effectively capture the main features of observed temperature and precipitation means and extremes over CA,with notable variations in model performance due to differences in the driving global climate models and the RCMs themselves.Overall,REMO consistently outperforms ALARO in simulating temperature-related indices,and ALARO-0 provides more accurate simulations for precipitation-related indices,and the multimodel ensemble(MME)tends to outperform individual RCMs.Under the representative concentration pathway(RCP)scenarios of RCP2.6 and RCP8.5,the MME results indicate a clear warming trend across CA for all temperature-related indices,except for the diurnal temperature range,with annual temperatures projected to increase by 0.15℃/10 yr and 0.53℃/10 yr,respectively.Both scenarios exhibit similar spatial distributions in projected annual precipitation,characterized by peak increases of~0.2 mm per day in northern CA.The number of consecutive dry days is projected to slightly increase under RCP8.5,while it is expected to slightly decrease under RCP2.6.This study improves our understanding of the applicability of RCMs in CA and provides reliable projections of future climate change.展开更多
当下,小学英语板块教学存在活动形式单一化、探究活动浅表化等问题,综合育人价值未能完全发挥。为改变这一现状,文章以人教版英语(PEP)四年级上册Unit 1“Helping at home”的“Project:Make a poster of a happy family”为例,以项目...当下,小学英语板块教学存在活动形式单一化、探究活动浅表化等问题,综合育人价值未能完全发挥。为改变这一现状,文章以人教版英语(PEP)四年级上册Unit 1“Helping at home”的“Project:Make a poster of a happy family”为例,以项目化学习为支架,围绕项目设计、过程实施、评价反馈、成果展示等维度探究有效教学策略,旨在优化Project板块的教学模式,引导学生在项目化学习中提升语言运用能力和综合实践能力。展开更多
Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both g...Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both global and regional climates.This study assesses the performance of models participating in phase 6 of the Coupled Model Intercomparison Project in simulating interannual variability modes of Northern Hemisphere 500-hPa geopotential height during winter and summer,distinguishing predictable(potentially predictable on seasonal or longer timescales)and unpredictable(intraseasonal and essentially unpredictable at long range)components,using reanalysis data and a variance decomposition method.Although most models effectively capture unpredictable modes in reanalysis,their ability to reproduce dominant predictable modes-specifically the Pacific-North American pattern,Arctic Oscillation,and Western Pacific Oscillation in winter,and the East Atlantic and North Atlantic Oscillations in summer-varies notably.An optimal ensemble is identified to distinguish(a)predictable-external modes,dominated by external forcing,and(b)predictable-internal modes,associated with slow internal variability,during the historical period(1950-2014)and the SSP5-8.5 scenario(2036-2100).Under increased radiative forcing,the leading winter/summer predictable-external mode exhibits a more uniform spatial distribution,remarkably larger trend and annual variance,and enhanced height-sea surface temperature(SST)covariance under SSP5-8.5 compared to historical conditions.The dominant winter/summer predictable-internal modes also exhibit increased variance and height-SST covariance under SSP5-8.5,along with localized changes in spatial configuration.Minimal changes are observed in spatial distribution or variance for dominant winter/summer unpredictable modes under SSP5-8.5.This study,from a predictive perspective,deepens our understanding of model uncertainties and projected changes in circulations.展开更多
Accurate fission cross-sectional data for actinide nuclides are critical for nuclear energy,astrophysics,and defense applications.Traditional detectors,such as fission chambers,face limitations in achieving sub-3% unc...Accurate fission cross-sectional data for actinide nuclides are critical for nuclear energy,astrophysics,and defense applications.Traditional detectors,such as fission chambers,face limitations in achieving sub-3% uncertainty owing to particle identification challenges and dynamic range constraints.The time projection chamber(TPC)can record both the energy deposition dE/dx and the three-dimensional track of an event,providing the ability to identify particles and fission fragments.Based on this characteristic,we developed a novel TPC,INPC-TPC,featuring a symmetrical dual-chamber structure and gas electron multiplier(GEM)-based readout technology.The dual-chamber design isolates fission fragments and recoils protons,thereby reducing the dynamic range requirements of a single chamber,whereas the GEM ensures high spatial resolution and stable gain.Experiments conducted at the Chinese Spallation Neutron Source(CSNS)Back-n white neutron beamline validated the performance of the proposed detector.The INPC-TPC demonstrated effective fission fragment identification through particle energy-length correlation measurements and accurately measured the neutron beam spot size with a diameter relative error of<2%.The results highlight the capability of the system to achieve high-precision measurements of neutroninduced fission cross sections,particularly for ^(235)U and ^(238)U.展开更多
The Antarctic Tianmu Staring Observation Project(ATSOP)entails the deployment of 30 small-aperture,wide-field optical telescopes in the Antarctic region.The system will perform long-term continuous observation campaig...The Antarctic Tianmu Staring Observation Project(ATSOP)entails the deployment of 30 small-aperture,wide-field optical telescopes in the Antarctic region.The system will perform long-term continuous observation campaigns over a period of 100 d(24 h per day)per year,as well as short-time-scale sampling at intervals of 5 min,across a sky area of approximately 1200 square degrees centered near the south celestial pole.We have assessed the types of small solar system bodies detectable by the ATSOP telescopes,as well as the associated scientific research opportunities.Our analysis indicates that the ATSOP is capable of detecting near-Earth objects(NEOs)with all orbital inclinations,as well as high-inclination small bodies located beyond the main asteroid belt.Potential research topics include the discovery and identification of small bodies,orbit determination,physical characterization,investigation into the activity characteristics and evolutionary patterns of active small bodies,and studies on their dynamical evolution.Observations of NEOs can also contribute to planetary defense efforts.On the basis of pilot observational data collected by the Antarctic Tianmu prototype(AT-Proto)between February 20 and October 26,2023,a total of 478 asteroids and 9 comets were successfully identified,demonstrating the effectiveness of the ATSOP system in observing small solar system bodies.Looking ahead,with anticipated performance enhancements in the second-generation AT-Proto,the limiting magnitude will increase from 16 to 18,thereby enabling the detection of an even greater number of small solar system bodies.展开更多
Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods...Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods,based on reliable existing data stored in project management tools’datasets,automating this evaluation process becomes a natural step forward.In this context,our approach focuses on quantifying software developer expertise by using metadata from the task-tracking systems.For this,we mathematically formalize two categories of expertise:technology-specific expertise,which denotes the skills required for a particular technology,and general expertise,which encapsulates overall knowledge in the software industry.Afterward,we automatically classify the zones of expertise associated with each task a developer has worked on using Bidirectional Encoder Representations from Transformers(BERT)-like transformers to handle the unique characteristics of project tool datasets effectively.Finally,our method evaluates the proficiency of each software specialist across already completed projects from both technology-specific and general perspectives.The method was experimentally validated,yielding promising results.展开更多
The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risk...The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risks,including floods and droughts.Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms.Observational data reveal a 20th-century shift:increased rainfall pre-1950s,followed by aridification and partial recovery post-1980s,driven by both internal variability(e.g.,Atlantic Multidecadal Oscillation)and external forcings(greenhouse gases,aerosols),while ENSO drives interannual variability through ocean-atmosphere interactions.Future projections under greenhouse forcing suggest long-term monsoon intensification,though regional disparities and model uncertainties persist.Models indicate robust trends but struggle to quantify extremes,where thermodynamic effects(warming-induced moisture rise)uniformly boost heavy rainfall,while dynamical shifts(circulation changes)create spatial heterogeneity.Volcanic eruptions and proposed solar radiation modification(SRM)further complicate predictions:tropical eruptions suppress monsoons,whereas high-latitude events alter cross-equatorial flows,highlighting unresolved feedbacks.The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons.Critical challenges remain.Model biases and sparse 20th-century observational data hinder accurate attribution.The interplay between natural variability and anthropogenic forcings,along with nonlinear extreme precipitation risks under warming,demands deeper mechanistic insights.Additionally,SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation.Addressing these gaps necessitates enhanced observational networks,refined climate models,and interdisciplinary efforts to disentangle multiscale drivers,ultimately improving resilience strategies for monsoon-dependent regions.展开更多
Understanding how ecological engineering influences the trade-offs and synergies among regional ecosystem services can provide valuable insights for enhancing ecosystem functionality and promoting a virtuous and susta...Understanding how ecological engineering influences the trade-offs and synergies among regional ecosystem services can provide valuable insights for enhancing ecosystem functionality and promoting a virtuous and sustainable ecological cycle.This study focuses on the Changbai Mountain region,a key ecological conservation area in northeastern China.It employs global spatial autocorrelation analysis and bivariate spatial correlation methods to explore the spatial patterns of five key ecosystem services—soil retention,carbon sequestration,water purification,habitat quality,and water yield—as well as the spatial heterogeneity of the trade-offs and synergies among them.The results indicate that:(1)Forest land is the dominant land-use type in the study area,with land-use changes primarily occurring among grassland,forest,and cropland.(2)The implementation of the“Mountain-River Project”has significantly enhanced ecosystem service capacities.Specifically,the average habitat quality has remained stable at 0.97;average water yield increased from 716 mm to 743 mm;average nitrogen purification rose from 0.025 to 0.028;and total soil retention increased from 8.7×10^(7)tons to 5.09×10^(8)tons.(3)Synergistic relationships dominate the interactions among individual ecosystem services in the Changbai Mountain region.The implementation of ecological engineering has further strengthened synergies—particularly among soil retention,water yield,and other services.However,the short-term impacts of the project have somewhat weakened the synergies between water purification and other ecosystem services.These findings offer a novel perspective for understanding the effects of ecological engineering on ecosystem services and provide a scientific basis for future ecological restoration planning and management.展开更多
Andrew Wangota,a 48-year-old Ugandan farmer,has been using agrivoltaics technology,a solar technology that uses agricultural land for both food production and solar power generation,on his farm in Bunashimolo Parish,B...Andrew Wangota,a 48-year-old Ugandan farmer,has been using agrivoltaics technology,a solar technology that uses agricultural land for both food production and solar power generation,on his farm in Bunashimolo Parish,Bukyiende Subcounty in Uganda where he has been cultivating plantain,coffee and Irish potatoes for the past 16 years.展开更多
Dear Editor,Serotonin(5-HT),a pivotal neuromodulator,plays a central role in the social impairments characteristic of autism spectrum disorder(ASD).Clinical evidence reveals elevated blood 5-HT levels and reduced sero...Dear Editor,Serotonin(5-HT),a pivotal neuromodulator,plays a central role in the social impairments characteristic of autism spectrum disorder(ASD).Clinical evidence reveals elevated blood 5-HT levels and reduced serotonin transporter(5-HTT)availability in ASD patients[1],implicating serotonergic dysregulation in social behavior.展开更多
A veteran materials engineer and NPC deputy has spent 30 years developing aluminum alloys for strategic national projects,while championing industrial upgrading and skills development for China’s manufacturing transf...A veteran materials engineer and NPC deputy has spent 30 years developing aluminum alloys for strategic national projects,while championing industrial upgrading and skills development for China’s manufacturing transformation.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
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.
基金This work has been supported by the National Science Foundation of China Grant No.61762092“Dynamic multi-objective requirement optimization based on transfer learning,”and the Open Foundation of the Key Laboratory in Software Engineering of Yunnan Province,Grant No.2017SE204+1 种基金“Research on extracting software feature models using transfer learning,”and the National Science Foundation of China Grant No.61762089“The key research of high order tensor decomposition in a distributed environment”.
文摘With the rise of open-source software,the social development paradigm occupies an indispensable position in the current software development process.This paper puts forward a variant of the PageRank algorithm to build the importance assessment model,which provides quantifiable importance assessment metrics for new Java projects based on Java open-source projects or components.The critical point of the model is to use crawlers to obtain relevant information about Java open-source projects in the GitHub open-source community to build a domain knowledge graph.According to the three dimensions of the Java open-source project’s project influence,project activity and project popularity,the project is measured.A modified PageRank algorithm is proposed to construct the importance evaluation model.Thereby providing quantifiable importance evaluation indicators for new Java projects based on or components of Java open-source projects.This article evaluates the importance of 4512 Java open-source projects obtained on GitHub and has a good effect.
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.
基金supported by the Yunnan Provincial Philosophy and Social Science Planning Projectthe Yunnan Academy of Social Sciences。
文摘China and Laos are close neighbors with a long-standing friendship.Since the early 2000s,China has supported Laos'economic and social development through wide-ranging cooperation projects,all guided by the vision of a community with a shared future.As this vision takes deeper root,many aid projects have moved from blueprint to reality,delivering tangible benefits across towns and villages and improving the lives of ordinary Lao people while further strengthening bilateral ties.
基金supported by the Netherlands Organization for Scientific Research NWO in the form of a VIDI grant(Grant No.VI.Vidi.198.008).
文摘Projections of future urban land change are essential for a range of sustainability assessments,including those related to biodiversity loss,carbon emissions,and agricultural land conversion.However,to what extent and where current projections agree or disagree remains unknown.Here,we systematically compare existing global projections that are consistent with the Shared Socioeconomic Pathways.We find that the total global urban land area is expected to increase by 112%between 2020 and 2100(averaged across all projections),with a coefficient of variation of 0.81.This variation is mostly caused by the selection of the underlying drivers that are included in the different models.Regionally,the highest average growth rates are found in sub-Saharan Africa(+679%to+730%),while this region also has the highest variation across projections(coefficient of variation ranging from 2.02 to 2.18).When ranking scenarios within a study from the highest to the lowest projected increase in urban land,rankings are relatively similar for regions in the Global North,but not for regions in the Global South.The large disagreement across projections can lead to high uncertainties in assessments of future urban land change impacts,which can undermine the effectiveness of long-term planning,policymaking,and resource management decisions.
基金jointly supported by the Second Tibetan Plateau Scientific Expedition and Research Program[grant number 2019QZKK0103]the National Natural Science Foundation of China[grant number 42293294]the China Meteorological Administration Climate Change Special Program[grant number QBZ202303]。
文摘This study provides potential climate projections for Central Asia(CA)based on multi-regional climate model(RCM)outputs from the Coordinated Regional Climate Downscaling Experiment for Central Asia(CORDEX-CAII).Despite some systematic biases,all RCMs effectively capture the main features of observed temperature and precipitation means and extremes over CA,with notable variations in model performance due to differences in the driving global climate models and the RCMs themselves.Overall,REMO consistently outperforms ALARO in simulating temperature-related indices,and ALARO-0 provides more accurate simulations for precipitation-related indices,and the multimodel ensemble(MME)tends to outperform individual RCMs.Under the representative concentration pathway(RCP)scenarios of RCP2.6 and RCP8.5,the MME results indicate a clear warming trend across CA for all temperature-related indices,except for the diurnal temperature range,with annual temperatures projected to increase by 0.15℃/10 yr and 0.53℃/10 yr,respectively.Both scenarios exhibit similar spatial distributions in projected annual precipitation,characterized by peak increases of~0.2 mm per day in northern CA.The number of consecutive dry days is projected to slightly increase under RCP8.5,while it is expected to slightly decrease under RCP2.6.This study improves our understanding of the applicability of RCMs in CA and provides reliable projections of future climate change.
文摘当下,小学英语板块教学存在活动形式单一化、探究活动浅表化等问题,综合育人价值未能完全发挥。为改变这一现状,文章以人教版英语(PEP)四年级上册Unit 1“Helping at home”的“Project:Make a poster of a happy family”为例,以项目化学习为支架,围绕项目设计、过程实施、评价反馈、成果展示等维度探究有效教学策略,旨在优化Project板块的教学模式,引导学生在项目化学习中提升语言运用能力和综合实践能力。
基金supported by the National Natural Science Foundation of China(Grant Nos.U2342210 and 42275043)the National Institute of Natural Hazards,Ministry of Emergency Management of China(Grant Nos.J2223806,ZDJ2024-25 and ZDJ2025-34)。
文摘Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both global and regional climates.This study assesses the performance of models participating in phase 6 of the Coupled Model Intercomparison Project in simulating interannual variability modes of Northern Hemisphere 500-hPa geopotential height during winter and summer,distinguishing predictable(potentially predictable on seasonal or longer timescales)and unpredictable(intraseasonal and essentially unpredictable at long range)components,using reanalysis data and a variance decomposition method.Although most models effectively capture unpredictable modes in reanalysis,their ability to reproduce dominant predictable modes-specifically the Pacific-North American pattern,Arctic Oscillation,and Western Pacific Oscillation in winter,and the East Atlantic and North Atlantic Oscillations in summer-varies notably.An optimal ensemble is identified to distinguish(a)predictable-external modes,dominated by external forcing,and(b)predictable-internal modes,associated with slow internal variability,during the historical period(1950-2014)and the SSP5-8.5 scenario(2036-2100).Under increased radiative forcing,the leading winter/summer predictable-external mode exhibits a more uniform spatial distribution,remarkably larger trend and annual variance,and enhanced height-sea surface temperature(SST)covariance under SSP5-8.5 compared to historical conditions.The dominant winter/summer predictable-internal modes also exhibit increased variance and height-SST covariance under SSP5-8.5,along with localized changes in spatial configuration.Minimal changes are observed in spatial distribution or variance for dominant winter/summer unpredictable modes under SSP5-8.5.This study,from a predictive perspective,deepens our understanding of model uncertainties and projected changes in circulations.
基金supported by the auspices of the Youth Doctoral Talent Incubation Program of the Second Affiliated Hospital of Army Medical University(No.2024YQB060)。
文摘Accurate fission cross-sectional data for actinide nuclides are critical for nuclear energy,astrophysics,and defense applications.Traditional detectors,such as fission chambers,face limitations in achieving sub-3% uncertainty owing to particle identification challenges and dynamic range constraints.The time projection chamber(TPC)can record both the energy deposition dE/dx and the three-dimensional track of an event,providing the ability to identify particles and fission fragments.Based on this characteristic,we developed a novel TPC,INPC-TPC,featuring a symmetrical dual-chamber structure and gas electron multiplier(GEM)-based readout technology.The dual-chamber design isolates fission fragments and recoils protons,thereby reducing the dynamic range requirements of a single chamber,whereas the GEM ensures high spatial resolution and stable gain.Experiments conducted at the Chinese Spallation Neutron Source(CSNS)Back-n white neutron beamline validated the performance of the proposed detector.The INPC-TPC demonstrated effective fission fragment identification through particle energy-length correlation measurements and accurately measured the neutron beam spot size with a diameter relative error of<2%.The results highlight the capability of the system to achieve high-precision measurements of neutroninduced fission cross sections,particularly for ^(235)U and ^(238)U.
基金supported by the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted by the Ministry of Finance of China(MOF)and administered by the Chinese Academy of Sciences(CAS),the National Natural Science Foundation of China(Nos.12173093 and 11973094)a science research grant from the China Manned Space Project(No.CMS-CSST-2021-B08).
文摘The Antarctic Tianmu Staring Observation Project(ATSOP)entails the deployment of 30 small-aperture,wide-field optical telescopes in the Antarctic region.The system will perform long-term continuous observation campaigns over a period of 100 d(24 h per day)per year,as well as short-time-scale sampling at intervals of 5 min,across a sky area of approximately 1200 square degrees centered near the south celestial pole.We have assessed the types of small solar system bodies detectable by the ATSOP telescopes,as well as the associated scientific research opportunities.Our analysis indicates that the ATSOP is capable of detecting near-Earth objects(NEOs)with all orbital inclinations,as well as high-inclination small bodies located beyond the main asteroid belt.Potential research topics include the discovery and identification of small bodies,orbit determination,physical characterization,investigation into the activity characteristics and evolutionary patterns of active small bodies,and studies on their dynamical evolution.Observations of NEOs can also contribute to planetary defense efforts.On the basis of pilot observational data collected by the Antarctic Tianmu prototype(AT-Proto)between February 20 and October 26,2023,a total of 478 asteroids and 9 comets were successfully identified,demonstrating the effectiveness of the ATSOP system in observing small solar system bodies.Looking ahead,with anticipated performance enhancements in the second-generation AT-Proto,the limiting magnitude will increase from 16 to 18,thereby enabling the detection of an even greater number of small solar system bodies.
基金supported by the project“Romanian Hub for Artificial Intelligence-HRIA”,Smart Growth,Digitization and Financial Instruments Program,2021–2027,MySMIS No.334906.
文摘Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods,based on reliable existing data stored in project management tools’datasets,automating this evaluation process becomes a natural step forward.In this context,our approach focuses on quantifying software developer expertise by using metadata from the task-tracking systems.For this,we mathematically formalize two categories of expertise:technology-specific expertise,which denotes the skills required for a particular technology,and general expertise,which encapsulates overall knowledge in the software industry.Afterward,we automatically classify the zones of expertise associated with each task a developer has worked on using Bidirectional Encoder Representations from Transformers(BERT)-like transformers to handle the unique characteristics of project tool datasets effectively.Finally,our method evaluates the proficiency of each software specialist across already completed projects from both technology-specific and general perspectives.The method was experimentally validated,yielding promising results.
基金supported by the National Key Research and Development Program of China(Grant No.2020YFA0608904)the International Partnership Program of the Chinese Academy of Sciences(Grant Nos.060GJHZ2023079GC and 134111KYSB20160031)+1 种基金supported by the Office of Science,U.S.Department of Energy(DOE)Biological and Environmental Research as part of the Regional and Global Model Analysis program area through the Water Cycle and Climate Extremes Modeling(WACCEM)scientific focus areaoperated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830。
文摘The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risks,including floods and droughts.Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms.Observational data reveal a 20th-century shift:increased rainfall pre-1950s,followed by aridification and partial recovery post-1980s,driven by both internal variability(e.g.,Atlantic Multidecadal Oscillation)and external forcings(greenhouse gases,aerosols),while ENSO drives interannual variability through ocean-atmosphere interactions.Future projections under greenhouse forcing suggest long-term monsoon intensification,though regional disparities and model uncertainties persist.Models indicate robust trends but struggle to quantify extremes,where thermodynamic effects(warming-induced moisture rise)uniformly boost heavy rainfall,while dynamical shifts(circulation changes)create spatial heterogeneity.Volcanic eruptions and proposed solar radiation modification(SRM)further complicate predictions:tropical eruptions suppress monsoons,whereas high-latitude events alter cross-equatorial flows,highlighting unresolved feedbacks.The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons.Critical challenges remain.Model biases and sparse 20th-century observational data hinder accurate attribution.The interplay between natural variability and anthropogenic forcings,along with nonlinear extreme precipitation risks under warming,demands deeper mechanistic insights.Additionally,SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation.Addressing these gaps necessitates enhanced observational networks,refined climate models,and interdisciplinary efforts to disentangle multiscale drivers,ultimately improving resilience strategies for monsoon-dependent regions.
基金supported by the coupling mechanism and system restoration modes of Mountains-Rivers-Forests-Farmlands-Lakes-Grasslands,National Key Research and Development Program of the 14th Five-Year,China(2022YFF1303201).
文摘Understanding how ecological engineering influences the trade-offs and synergies among regional ecosystem services can provide valuable insights for enhancing ecosystem functionality and promoting a virtuous and sustainable ecological cycle.This study focuses on the Changbai Mountain region,a key ecological conservation area in northeastern China.It employs global spatial autocorrelation analysis and bivariate spatial correlation methods to explore the spatial patterns of five key ecosystem services—soil retention,carbon sequestration,water purification,habitat quality,and water yield—as well as the spatial heterogeneity of the trade-offs and synergies among them.The results indicate that:(1)Forest land is the dominant land-use type in the study area,with land-use changes primarily occurring among grassland,forest,and cropland.(2)The implementation of the“Mountain-River Project”has significantly enhanced ecosystem service capacities.Specifically,the average habitat quality has remained stable at 0.97;average water yield increased from 716 mm to 743 mm;average nitrogen purification rose from 0.025 to 0.028;and total soil retention increased from 8.7×10^(7)tons to 5.09×10^(8)tons.(3)Synergistic relationships dominate the interactions among individual ecosystem services in the Changbai Mountain region.The implementation of ecological engineering has further strengthened synergies—particularly among soil retention,water yield,and other services.However,the short-term impacts of the project have somewhat weakened the synergies between water purification and other ecosystem services.These findings offer a novel perspective for understanding the effects of ecological engineering on ecosystem services and provide a scientific basis for future ecological restoration planning and management.
文摘Andrew Wangota,a 48-year-old Ugandan farmer,has been using agrivoltaics technology,a solar technology that uses agricultural land for both food production and solar power generation,on his farm in Bunashimolo Parish,Bukyiende Subcounty in Uganda where he has been cultivating plantain,coffee and Irish potatoes for the past 16 years.
基金supported by Research Center for Brain Cognition and Human Development,Guangdong,China(2024B0303390003)Guangdong Basic and Applied Basic Research Foundation(2023A1515010477)+4 种基金the National Social Science Foundation of China(20&ZD296,CH)Key-Area Research and Development Program of Guangdong Province(2019B030335001)Special Funds for the Cultivation of Guangdong College Students’Scientific and Technological Innovation(“Climbing Program”Special Funds pdjh2024b118)Autism Research Special Fund of Zhejiang Foundation For Disabled Persons(2023003)Scientific Research Innovation Project of Graduate School of South China Normal University(43204021,RZ&CH).
文摘Dear Editor,Serotonin(5-HT),a pivotal neuromodulator,plays a central role in the social impairments characteristic of autism spectrum disorder(ASD).Clinical evidence reveals elevated blood 5-HT levels and reduced serotonin transporter(5-HTT)availability in ASD patients[1],implicating serotonergic dysregulation in social behavior.
文摘A veteran materials engineer and NPC deputy has spent 30 years developing aluminum alloys for strategic national projects,while championing industrial upgrading and skills development for China’s manufacturing transformation.
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.
