The 23rd World Congress of Soil Science(23rd WCSS),to be held on June 7-12,2026 in Nanjing,China,marks a historic coming of this century-old scientific gathering to one of the world's ancient agricultural civiliza...The 23rd World Congress of Soil Science(23rd WCSS),to be held on June 7-12,2026 in Nanjing,China,marks a historic coming of this century-old scientific gathering to one of the world's ancient agricultural civilizations.Since its inception in1927,this will be the first time the Congress is hosted in China,a land whose agricultural resilience has been nurtured by millennia of soil stewardship.展开更多
Soil science has remained basically an agricultural science since its establishment more than a century ago.However,given its multi-dimensional connections with human society and multi-functions and services to be uti...Soil science has remained basically an agricultural science since its establishment more than a century ago.However,given its multi-dimensional connections with human society and multi-functions and services to be utilized in the future,the theoretical and technological boundary of soil science is expanding from agricultural science to newly emerged soil science sectors,which can be termed as nontraditional soil science.To build a more comprehensive and up-to-date soil science system,new description methods,recommendation standards,interpretation principles,and criteria for non-agricultural applications should be developed.展开更多
0 INTRODUCTION Earth science is a natural science concerned with the composition,dynamics,spatiotemporal evolution,and formation mechanisms of Earth materials(Chen and Yang,2023).Traditional Earth science research has...0 INTRODUCTION Earth science is a natural science concerned with the composition,dynamics,spatiotemporal evolution,and formation mechanisms of Earth materials(Chen and Yang,2023).Traditional Earth science research has largely been discipline-based,relying on field investigations,data collection,experimental analyses,and data interpretation to study individual components of the Earth system.展开更多
Background:With the rapid development of modern emerging technologies,the ethical dilemmas and social controversies triggered by scientific and technological activities have become increasingly prominent.How to guide ...Background:With the rapid development of modern emerging technologies,the ethical dilemmas and social controversies triggered by scientific and technological activities have become increasingly prominent.How to guide technology for good and prevent and control technological risks has become an important issue of global concern.Research on science and technology ethics is dedicated to integrating ethical theories into governance practices and constructing ethical models that adapt to the development of the times.Methods:This article systematically reviews the six core approaches of scientific and technological ethics thought,including technological autonomy and political philosophy criticism,responsibility ethics and intergenerational obligations,technological intermediation and the integration of life and the world,ethical principles and normative frameworks,participatory governance and ethical practice innovation,as well as domain-specific ethical norms,thereby constructing an ethical analysis framework applicable to medical technology risks.And cross-analysis was conducted by taking medical events such as gene editing and xenotransplantation as examples.Results:Research shows that a single ethical approach has limitations in addressing complex medical ethical challenges,while the six approaches are complementary and synergistic.By criticizing technological autonomy,establishing a responsibility ethics orientation,setting the bottom line of ethical principles,promoting participatory governance,formulating domain norms,and continuously reflecting on the intermediary nature of technology,a multi-level and dynamically adaptive governance system for scientific and technological ethics can be constructed.Conclusion:The key to addressing contemporary medical ethics challenges lies in the comprehensive application of science and technology ethics theories and the integration of ethical considerations throughout the entire process of scientific and technological research and development.In the future,a governance framework that adapts to the development of new technologies should be established to promote cross-cultural and cross-disciplinary ethical dialogue and public participation,ensuring that scientific and technological innovation always serves the dignity of human life and overall well-being.展开更多
I offer suggestions to increase the probability of success of an international research project.Collaborative studies often produce more innovative and transformative scientific results than work done by a single inve...I offer suggestions to increase the probability of success of an international research project.Collaborative studies often produce more innovative and transformative scientific results than work done by a single investigator or an isolated team.My advice is intended for early-career scientists.The product of the collaboration may be high-impact research publications,enhanced geophysical monitoring capabilities in a foreign country,or an advanced training course.Choosing the right international partner is the most important step.Keeping an open mind and being receptive to suggestions to modify the initial concept is critical.Other key steps include having a mutually agreed upon plan with achievable goals and well-defined expected outcomes.International cooperation is a richly rewarding experience that accelerates progress in the Earth Sciences.展开更多
Tilt-to-length(TTL)coupling noise is a critical issue in space-based gravitational wave detection due to its complex dependence on multiple interacting factors,which complicates the identification of dominant paramete...Tilt-to-length(TTL)coupling noise is a critical issue in space-based gravitational wave detection due to its complex dependence on multiple interacting factors,which complicates the identification of dominant parameters.To address this challenge,we develop a simulation model of the Taiji scientific interferometer,generating noise datasets under multiparameter conditions.Given the uniqueness of the telescope as well as the convergence behavior of the algorithm,the analysis is structured hierarchically:(i)the telescope level and(ii)the optical bench level.A hierarchical framework combining XGBoost and SHapley Additive exPlanations(SHAP)values is employed to model the intricate relationships between parameters and TTL coupling noise,supplemented by sensitivity analysis.Our results identify pointing jitter and telescope radius as the dominant parameters at the telescope level,while the angles of the plane mirrors and beam splitters are most influential at the optical bench level.The parameter space is reduced from 86 dimensions to 14 dimensions without sacrificing model accuracy.This approach offers actionable insights for optimizing the Taiji interferometer design.展开更多
The year 2024 marked the 40th anniversary of Advances in Atmospheric Sciences(AAS),as well as the centenary of the Chinese Meteorological Society(CMS).The inaugural issue of AAS was published in 1984,initially being s...The year 2024 marked the 40th anniversary of Advances in Atmospheric Sciences(AAS),as well as the centenary of the Chinese Meteorological Society(CMS).The inaugural issue of AAS was published in 1984,initially being sponsored primarily by Chinese National Committee for the International Association of Meteorological and Atmospheric Sciences(IAMAS)and the Institute of Atmospheric Physics at the Chinese Academy of Sciences.In 2006,Springer became AAS’s international publisher.Then,in 2015,the CMS joined in sponsoring AAS,and in the same year,AAS also became an affiliated journal of the IAMAS.These milestone events helped broaden the reach of AAS,culminating in the journal establishing itself as a truly international journal supporting the advancement of the atmospheric sciences.展开更多
Raman imaging,as a molecular spectroscopy technique,has been widely studied and applied in research fields such as life sciences and food safety due to its excellent specificity and high resolution.However,its develop...Raman imaging,as a molecular spectroscopy technique,has been widely studied and applied in research fields such as life sciences and food safety due to its excellent specificity and high resolution.However,its development still faces challenges such as weak signals,slow acquisition speed,and insufficient penetration depth.In recent years,the rapid development of aggregate science has provided new insights for addressing these limitations.Aggregation-induced emission(AIE)materials exhibit enhanced signals in the aggregated state,which may compensate for the inherent weak Raman signals.This article reviews the cutting-edge progress of Raman imaging technology and its current status in cross-disciplinary research with aggregate science,emphasizing the strategy of constructing AIE-Raman dual-responsive probes through molecular engineering to achieve functional complementarity between fluorescence localization and Raman quantification,thereby significantly improving detection sensitivity and specificity.These probes have demonstrated single-cell resolution and high spatiotemporal accuracy in applications such as tumor surgical navigation,diagnosis and treatment of drug-resistant bacteria,and dynamic monitoring of organelles.We also analyze the bottlenecks in this field,such as biological safety and the complexity of molecular design,and outline the future development directions,including intelligent responsive probes,artificial intelligence-assisted analysis,and multimodal fusion platforms.The integration of Raman imaging and AIE sheds new light in the field of medical imaging.展开更多
In an academic environment increasingly shaped by metrics and the imperatives of“publish or perish”,it is rare to encounter a leading scientist willing to interweave personal narrative with conceptual reflection.The...In an academic environment increasingly shaped by metrics and the imperatives of“publish or perish”,it is rare to encounter a leading scientist willing to interweave personal narrative with conceptual reflection.The Soul of Geography by Fu(2025)achieves precisely this.The book resists simple categorisation:it is neither a conventional monograph nor a memoir,but rather a hybrid text that integrates autobiography,disciplinary reflection,and scientific arguments.In doing so,Fu articulates not only the trajectory of his own career but also a vision of geography as a discipline of theoretical depth and practical relevance.展开更多
1.Introduction Artificial intelligence(AI)is rapidly reshaping geoscience,from Earth observation interpretation and hazard forecasting to subsurface characterisation and Earth system modelling(Kochupillai et al.,2022;...1.Introduction Artificial intelligence(AI)is rapidly reshaping geoscience,from Earth observation interpretation and hazard forecasting to subsurface characterisation and Earth system modelling(Kochupillai et al.,2022;Sun et al.,2024).These capabilities emerge at a time when geoscientific evidence is increasingly informing high-stakes decisions about climate adaptation,resource development,and disaster risk reduction(McGovern et al.,2022).展开更多
The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-lear...The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-learning(DL)-driven CV in four key areas of materials science:microstructure-based performance prediction,microstructure information generation,microstructure defect detection,and crystal structure-based property prediction.The CV has significantly reduced the cost of traditional experimental methods used in material performance prediction.Moreover,recent progress made in generating microstructure images and detecting microstructural defects using CV has led to increased efficiency and reliability in material performance assessments.The DL-driven CV models can accelerate the design of new materials with optimized performance by integrating predictions based on both crystal and microstructural data,thereby allowing for the discovery and innovation of next-generation materials.Finally,the review provides insights into the rapid interdisciplinary developments in the field of materials science and future prospects.展开更多
Taking the Changli Institute of Pomology,Hebei Academy of Agriculture and Forestry Sciences(hereinafter referred to as the Changli Institute of Pomology)as a case study,this paper explores the practical pathways throu...Taking the Changli Institute of Pomology,Hebei Academy of Agriculture and Forestry Sciences(hereinafter referred to as the Changli Institute of Pomology)as a case study,this paper explores the practical pathways through which Party building leads to the high-quality development of fruit tree research from three dimensions:theoretical convergence points,current development status,and functional mechanisms.It proposes that Party building should focus on its core roles of steering political direction,enhancing team cohesion,and upholding ethical standards.Deep integration of Party building and scientific research should be achieved through concrete platforms,with the effectiveness measured by breakthroughs in critical"bottleneck"technologies and increased income for fruit growers.The study aims to provide a practical reference for integrating Party building with professional work in the agricultural research sector.展开更多
Periodontitis has emerged as one of the most critical oral diseases, and research on this condition holds great importance for the advancement of stomatology. As the most authoritative national scientific research fun...Periodontitis has emerged as one of the most critical oral diseases, and research on this condition holds great importance for the advancement of stomatology. As the most authoritative national scientific research funding institution in China, the National Natural Science Foundation of China (NSFC) has played a pivotal role in driving the progress of periodontal science by supporting research on periodontitis. This article provides a comprehensive review of the research and development progress related to periodontitis in China from 2014 to 2023, highlighting the significant contributions of the NSFC to this field. We have summarized the detailed funding information from the NSFC, including the number of applicant codes, funded programs and the distribution of funded scholars. These data illustrate the efforts of the NSFC in cultivating young scientists and building research groups to address key challenges in national scientific research. This study offers an overview of the current hot topics, recent breakthroughs and future research prospects related to periodontitis in China.展开更多
The integration of machine learning(ML)into geohazard assessment has successfully instigated a paradigm shift,leading to the production of models that possess a level of predictive accuracy previously considered unatt...The integration of machine learning(ML)into geohazard assessment has successfully instigated a paradigm shift,leading to the production of models that possess a level of predictive accuracy previously considered unattainable.However,the black-box nature of these systems presents a significant barrier,hindering their operational adoption,regulatory approval,and full scientific validation.This paper provides a systematic review and synthesis of the emerging field of explainable artificial intelligence(XAI)as applied to geohazard science(GeoXAI),a domain that aims to resolve the long-standing trade-off between model performance and interpretability.A rigorous synthesis of 87 foundational studies is used to map the intellectual and methodological contours of this rapidly expanding field.The analysis reveals that current research efforts are concentrated predominantly on landslide and flood assessment.Methodologically,tree-based ensembles and deep learning models dominate the literature,with SHapley Additive exPlanations(SHAP)frequently adopted as the principal post-hoc explanation technique.More importantly,the review further documents how the role of XAI has shifted:rather than being used solely as a tool for interpreting models after training,it is increasingly integrated into the modeling cycle itself.Recent applications include its use in feature selection,adaptive sampling strategies,and model evaluation.The evidence also shows that GeoXAI extends beyond producing feature rankings.It reveals nonlinear thresholds and interaction effects that generate deeper mechanistic insights into hazard processes and mechanisms.Nevertheless,several key challenges remain unresolved within the field.These persistent issues are especially pronounced when considering the crucial necessity for interpretation stability,the demanding scholarly task of reliably distinguishing correlation from causation,and the development of appropriate methods for the treatment of complex spatio-temporal dynamics.展开更多
Mortality prediction in respiratory health is challenging,especially when using large-scale clinical datasets composed primarily of categorical variables.Traditional digital twin(DT)frameworks often rely on longi-tudi...Mortality prediction in respiratory health is challenging,especially when using large-scale clinical datasets composed primarily of categorical variables.Traditional digital twin(DT)frameworks often rely on longi-tudinal or sensor-based data,which are not always available in public health contexts.In this article,we propose a novel proto-DT framework for mortality prediction in respiratory health using a large-scale categorical biomedical dataset.This dataset contains 415,711 severe acute respiratory infection cases from the Brazilian Unified Health System,including both COVID-19 and non-COVID-19 patients.Four classification models—extreme gradient boosting(XGBoost),logistic regression,random forest,and a deep neural network(DNN)—are trained using cost-sensitive learning to address class imbalance.The models are evaluated using accuracy,precision,recall,F1-score,and area under the curve(AUC)related to the receiver operating characteristic(ROC).The framework supports simulated interventions by modifying selected inputs and recalculating predicted mortality.Additionally,we incorporate multiple correspondence analysis and K-means clustering to explore model sensitivity.A Python library has been developed to ensure reproducibility.All models achieve AUC-ROC values near or above 0.85.XGBoost yields the highest accuracy(0.84),while the DNN achieves the highest recall(0.81).Scenario-based simulations reveal how key clinical factors,such as intensive care unit admission and oxygen support,affect predicted outcomes.The proposed proto-DT framework demonstrates the feasibility of mortality prediction and intervention simulation using categorical data alone.This framework provides a foundation for data-driven explainable DTs in public health,even in the absence of time-series data.展开更多
The Intelligent Internet of Things(IIoT)involves real-world things that communicate or interact with each other through networking technologies by collecting data from these“things”and using intelligent approaches,s...The Intelligent Internet of Things(IIoT)involves real-world things that communicate or interact with each other through networking technologies by collecting data from these“things”and using intelligent approaches,such as Artificial Intelligence(AI)and machine learning,to make accurate decisions.Data science is the science of dealing with data and its relationships through intelligent approaches.Most state-of-the-art research focuses independently on either data science or IIoT,rather than exploring their integration.Therefore,to address the gap,this article provides a comprehensive survey on the advances and integration of data science with the Intelligent IoT(IIoT)system by classifying the existing IoT-based data science techniques and presenting a summary of various characteristics.The paper analyzes the data science or big data security and privacy features,including network architecture,data protection,and continuous monitoring of data,which face challenges in various IoT-based systems.Extensive insights into IoT data security,privacy,and challenges are visualized in the context of data science for IoT.In addition,this study reveals the current opportunities to enhance data science and IoT market development.The current gap and challenges faced in the integration of data science and IoT are comprehensively presented,followed by the future outlook and possible solutions.展开更多
Deep-time Earth research plays a pivotal role in deciphering the rates,patterns,and mechanisms of Earth's evolutionary processes throughout geological history,providing essential scientific foundations for climate...Deep-time Earth research plays a pivotal role in deciphering the rates,patterns,and mechanisms of Earth's evolutionary processes throughout geological history,providing essential scientific foundations for climate prediction,natural resource exploration,and sustainable planetary stewardship.To advance Deep-time Earth research in the era of big data and artificial intelligence,the International Union of Geological Sciences initiated the“Deeptime Digital Earth International Big Science Program”(DDE)in 2019.At the core of this ambitious program lies the development of geoscience knowledge graphs,serving as a transformative knowledge infrastructure that enables the integration,sharing,mining,and analysis of heterogeneous geoscience big data.The DDE knowledge graph initiative has made significant strides in three critical dimensions:(1)establishing a unified knowledge structure across geoscience disciplines that ensures consistent representation of geological entities and their interrelationships through standardized ontologies and semantic frameworks;(2)developing a robust and scalable software infrastructure capable of supporting both expert-driven and machine-assisted knowledge engineering for large-scale graph construction and management;(3)implementing a comprehensive three-tiered architecture encompassing basic,discipline-specific,and application-oriented knowledge graphs,spanning approximately 20 geoscience disciplines.Through its open knowledge framework and international collaborative network,this initiative has fostered multinational research collaborations,establishing a robust foundation for next-generation geoscience research while propelling the discipline toward FAIR(Findable,Accessible,Interoperable,Reusable)data practices in deep-time Earth systems research.展开更多
Musculoskeletal injuries are among the most common causes of disability worldwide,with early detection and appropriate intervention critical to minimizing long-term complications.Infrared thermography(IRT)has emerged ...Musculoskeletal injuries are among the most common causes of disability worldwide,with early detection and appropriate intervention critical to minimizing long-term complications.Infrared thermography(IRT)has emerged as a noninvasive,real-time imaging modality that captures superficial temperature changes reflecting underlying physiological processes such as inflammation and vascular alterations.This review explores the fundamental principles of medical thermography,differentiates between passive and active approaches,and outlines key technological advancements including artificial intelligence integration.The clinical utility of IRT is discussed in various contexts–ranging from acute soft tissue injuries and overuse syndromes to chronic pain and rehabilitation monitoring.Comparative insights with conventional imaging techniques such as ultrasound and magnetic resonance imaging are also presented.While IRT offers functional imaging capabilities with advantages in portability,safety,and speed,its limitations–such as lack of deep-tissue penetration and protocol standardization–remain significant barriers to broader adoption.Future directions include the integration of IRT with other imaging modalities and digital health platforms to enhance musculoskeletal assessment and injury prevention strategies.展开更多
Editorial message Every advancement in the field of laboratory animal science and technology,from exploring basic mechanisms to validating the development of new drugs,and from establishing disease models to respondin...Editorial message Every advancement in the field of laboratory animal science and technology,from exploring basic mechanisms to validating the development of new drugs,and from establishing disease models to responding to public health emergencies,strengthens the foundation for human health and well-being,serving as an important cornerstone for promoting global scientific innovation.For this reason.展开更多
Background:The advent of the self-media age,digital humanities,and artificial intelligence(AI)technologies is gradually reshaping the narrative frameworks of the history of science and technology in general and the hi...Background:The advent of the self-media age,digital humanities,and artificial intelligence(AI)technologies is gradually reshaping the narrative frameworks of the history of science and technology in general and the history of medicine in particular,as it transforms the specific shape of contemporary medical science and health communication practice with the help of interactive,scenario-based communication ecosystems.Methods:This paper focuses on the interactive relationship between the history of science and science communication,employing historical tracing and case study comparison as research methods to explore the pathways and innovative models for reintegrating the history of science and technology including the history of medicine into contemporary scientific discourse.Results:The study finds that in the Chinese context,three key pathways facilitate the engagement of the history of science and technology including the history of medicine in science communication:administrative intervention,value reconstruction,and personalized adaptation.Specifically,administrative intervention promotes the integration of the history of science education into talent development through policy design;value reconstruction,centered on the scientific spirit,enhances societal cultural recognition of technological progress;and personalized adaptation leverages big data and social media technologies to enable precise and tailored knowledge dissemination.Conclusion:The rise of the“web-based knowledge brokering model”in the era of social media has introduced professional knowledge brokers,ensuring the accuracy and accessibility of science communication.These innovations not only serve as decision-making simulation tools for medical science and health communication,linking historical insights with contemporary practice,but also provide theoretical foundations and practical paradigms for realizing the value of the history of science and technology in the digital era.展开更多
文摘The 23rd World Congress of Soil Science(23rd WCSS),to be held on June 7-12,2026 in Nanjing,China,marks a historic coming of this century-old scientific gathering to one of the world's ancient agricultural civilizations.Since its inception in1927,this will be the first time the Congress is hosted in China,a land whose agricultural resilience has been nurtured by millennia of soil stewardship.
基金supported by the National Natural Science Foundation of China(No.42130715)the National Key Research and Development Program of China(No.2023YFD1500101)。
文摘Soil science has remained basically an agricultural science since its establishment more than a century ago.However,given its multi-dimensional connections with human society and multi-functions and services to be utilized in the future,the theoretical and technological boundary of soil science is expanding from agricultural science to newly emerged soil science sectors,which can be termed as nontraditional soil science.To build a more comprehensive and up-to-date soil science system,new description methods,recommendation standards,interpretation principles,and criteria for non-agricultural applications should be developed.
基金supported by National Key R&D Program of China(No.2021YFF0501301)the National Natural Science Foundation of China(No.42172231)。
文摘0 INTRODUCTION Earth science is a natural science concerned with the composition,dynamics,spatiotemporal evolution,and formation mechanisms of Earth materials(Chen and Yang,2023).Traditional Earth science research has largely been discipline-based,relying on field investigations,data collection,experimental analyses,and data interpretation to study individual components of the Earth system.
基金supported by the National Key Research and Development Program(Grant No.2024YFA0917200)the Projects of the Chinese Center for Disease Control and Prevention(Grant No.BB2110240093)World Medical History under the Education Innovation Plan of the University of Science and Technology of China(Grant No.2024YCHX07).
文摘Background:With the rapid development of modern emerging technologies,the ethical dilemmas and social controversies triggered by scientific and technological activities have become increasingly prominent.How to guide technology for good and prevent and control technological risks has become an important issue of global concern.Research on science and technology ethics is dedicated to integrating ethical theories into governance practices and constructing ethical models that adapt to the development of the times.Methods:This article systematically reviews the six core approaches of scientific and technological ethics thought,including technological autonomy and political philosophy criticism,responsibility ethics and intergenerational obligations,technological intermediation and the integration of life and the world,ethical principles and normative frameworks,participatory governance and ethical practice innovation,as well as domain-specific ethical norms,thereby constructing an ethical analysis framework applicable to medical technology risks.And cross-analysis was conducted by taking medical events such as gene editing and xenotransplantation as examples.Results:Research shows that a single ethical approach has limitations in addressing complex medical ethical challenges,while the six approaches are complementary and synergistic.By criticizing technological autonomy,establishing a responsibility ethics orientation,setting the bottom line of ethical principles,promoting participatory governance,formulating domain norms,and continuously reflecting on the intermediary nature of technology,a multi-level and dynamically adaptive governance system for scientific and technological ethics can be constructed.Conclusion:The key to addressing contemporary medical ethics challenges lies in the comprehensive application of science and technology ethics theories and the integration of ethical considerations throughout the entire process of scientific and technological research and development.In the future,a governance framework that adapts to the development of new technologies should be established to promote cross-cultural and cross-disciplinary ethical dialogue and public participation,ensuring that scientific and technological innovation always serves the dignity of human life and overall well-being.
文摘I offer suggestions to increase the probability of success of an international research project.Collaborative studies often produce more innovative and transformative scientific results than work done by a single investigator or an isolated team.My advice is intended for early-career scientists.The product of the collaboration may be high-impact research publications,enhanced geophysical monitoring capabilities in a foreign country,or an advanced training course.Choosing the right international partner is the most important step.Keeping an open mind and being receptive to suggestions to modify the initial concept is critical.Other key steps include having a mutually agreed upon plan with achievable goals and well-defined expected outcomes.International cooperation is a richly rewarding experience that accelerates progress in the Earth Sciences.
基金Project supported by the National Key Research and Development Program of China(Grant No.2020YFC2200100)the CAS's Strategic Pioneer Program on Space Science(Grant No.XDA1502110201)。
文摘Tilt-to-length(TTL)coupling noise is a critical issue in space-based gravitational wave detection due to its complex dependence on multiple interacting factors,which complicates the identification of dominant parameters.To address this challenge,we develop a simulation model of the Taiji scientific interferometer,generating noise datasets under multiparameter conditions.Given the uniqueness of the telescope as well as the convergence behavior of the algorithm,the analysis is structured hierarchically:(i)the telescope level and(ii)the optical bench level.A hierarchical framework combining XGBoost and SHapley Additive exPlanations(SHAP)values is employed to model the intricate relationships between parameters and TTL coupling noise,supplemented by sensitivity analysis.Our results identify pointing jitter and telescope radius as the dominant parameters at the telescope level,while the angles of the plane mirrors and beam splitters are most influential at the optical bench level.The parameter space is reduced from 86 dimensions to 14 dimensions without sacrificing model accuracy.This approach offers actionable insights for optimizing the Taiji interferometer design.
文摘The year 2024 marked the 40th anniversary of Advances in Atmospheric Sciences(AAS),as well as the centenary of the Chinese Meteorological Society(CMS).The inaugural issue of AAS was published in 1984,initially being sponsored primarily by Chinese National Committee for the International Association of Meteorological and Atmospheric Sciences(IAMAS)and the Institute of Atmospheric Physics at the Chinese Academy of Sciences.In 2006,Springer became AAS’s international publisher.Then,in 2015,the CMS joined in sponsoring AAS,and in the same year,AAS also became an affiliated journal of the IAMAS.These milestone events helped broaden the reach of AAS,culminating in the journal establishing itself as a truly international journal supporting the advancement of the atmospheric sciences.
文摘Raman imaging,as a molecular spectroscopy technique,has been widely studied and applied in research fields such as life sciences and food safety due to its excellent specificity and high resolution.However,its development still faces challenges such as weak signals,slow acquisition speed,and insufficient penetration depth.In recent years,the rapid development of aggregate science has provided new insights for addressing these limitations.Aggregation-induced emission(AIE)materials exhibit enhanced signals in the aggregated state,which may compensate for the inherent weak Raman signals.This article reviews the cutting-edge progress of Raman imaging technology and its current status in cross-disciplinary research with aggregate science,emphasizing the strategy of constructing AIE-Raman dual-responsive probes through molecular engineering to achieve functional complementarity between fluorescence localization and Raman quantification,thereby significantly improving detection sensitivity and specificity.These probes have demonstrated single-cell resolution and high spatiotemporal accuracy in applications such as tumor surgical navigation,diagnosis and treatment of drug-resistant bacteria,and dynamic monitoring of organelles.We also analyze the bottlenecks in this field,such as biological safety and the complexity of molecular design,and outline the future development directions,including intelligent responsive probes,artificial intelligence-assisted analysis,and multimodal fusion platforms.The integration of Raman imaging and AIE sheds new light in the field of medical imaging.
文摘In an academic environment increasingly shaped by metrics and the imperatives of“publish or perish”,it is rare to encounter a leading scientist willing to interweave personal narrative with conceptual reflection.The Soul of Geography by Fu(2025)achieves precisely this.The book resists simple categorisation:it is neither a conventional monograph nor a memoir,but rather a hybrid text that integrates autobiography,disciplinary reflection,and scientific arguments.In doing so,Fu articulates not only the trajectory of his own career but also a vision of geography as a discipline of theoretical depth and practical relevance.
基金supported by the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20240937)the Natural Science Foundation of Shandong Province(Grant No.ZR2021QE187)+2 种基金the Shandong Higher Education“Young Entrepreneurship Talents Introduction and Cultivation Program”Project(Grant No.ZXQT20221228001)the Natural Science Foundation of China(Grant No.42502273)the Science and Technology Innovation Program of Hunan Province(Grant No.2022RC4028).
文摘1.Introduction Artificial intelligence(AI)is rapidly reshaping geoscience,from Earth observation interpretation and hazard forecasting to subsurface characterisation and Earth system modelling(Kochupillai et al.,2022;Sun et al.,2024).These capabilities emerge at a time when geoscientific evidence is increasingly informing high-stakes decisions about climate adaptation,resource development,and disaster risk reduction(McGovern et al.,2022).
基金financially supported by the National Science Fund for Distinguished Young Scholars,China(No.52025041)the National Natural Science Foundation of China(Nos.52450003,U2341267,and 52174294)+1 种基金the National Postdoctoral Program for Innovative Talents,China(No.BX20240437)the Fundamental Research Funds for the Central Universities,China(Nos.FRF-IDRY-23-037 and FRF-TP-20-02C2)。
文摘The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-learning(DL)-driven CV in four key areas of materials science:microstructure-based performance prediction,microstructure information generation,microstructure defect detection,and crystal structure-based property prediction.The CV has significantly reduced the cost of traditional experimental methods used in material performance prediction.Moreover,recent progress made in generating microstructure images and detecting microstructural defects using CV has led to increased efficiency and reliability in material performance assessments.The DL-driven CV models can accelerate the design of new materials with optimized performance by integrating predictions based on both crystal and microstructural data,thereby allowing for the discovery and innovation of next-generation materials.Finally,the review provides insights into the rapid interdisciplinary developments in the field of materials science and future prospects.
基金Supported by Qinhuangdao Social Sciences Development Research Project(2025LX378).
文摘Taking the Changli Institute of Pomology,Hebei Academy of Agriculture and Forestry Sciences(hereinafter referred to as the Changli Institute of Pomology)as a case study,this paper explores the practical pathways through which Party building leads to the high-quality development of fruit tree research from three dimensions:theoretical convergence points,current development status,and functional mechanisms.It proposes that Party building should focus on its core roles of steering political direction,enhancing team cohesion,and upholding ethical standards.Deep integration of Party building and scientific research should be achieved through concrete platforms,with the effectiveness measured by breakthroughs in critical"bottleneck"technologies and increased income for fruit growers.The study aims to provide a practical reference for integrating Party building with professional work in the agricultural research sector.
文摘Periodontitis has emerged as one of the most critical oral diseases, and research on this condition holds great importance for the advancement of stomatology. As the most authoritative national scientific research funding institution in China, the National Natural Science Foundation of China (NSFC) has played a pivotal role in driving the progress of periodontal science by supporting research on periodontitis. This article provides a comprehensive review of the research and development progress related to periodontitis in China from 2014 to 2023, highlighting the significant contributions of the NSFC to this field. We have summarized the detailed funding information from the NSFC, including the number of applicant codes, funded programs and the distribution of funded scholars. These data illustrate the efforts of the NSFC in cultivating young scientists and building research groups to address key challenges in national scientific research. This study offers an overview of the current hot topics, recent breakthroughs and future research prospects related to periodontitis in China.
文摘The integration of machine learning(ML)into geohazard assessment has successfully instigated a paradigm shift,leading to the production of models that possess a level of predictive accuracy previously considered unattainable.However,the black-box nature of these systems presents a significant barrier,hindering their operational adoption,regulatory approval,and full scientific validation.This paper provides a systematic review and synthesis of the emerging field of explainable artificial intelligence(XAI)as applied to geohazard science(GeoXAI),a domain that aims to resolve the long-standing trade-off between model performance and interpretability.A rigorous synthesis of 87 foundational studies is used to map the intellectual and methodological contours of this rapidly expanding field.The analysis reveals that current research efforts are concentrated predominantly on landslide and flood assessment.Methodologically,tree-based ensembles and deep learning models dominate the literature,with SHapley Additive exPlanations(SHAP)frequently adopted as the principal post-hoc explanation technique.More importantly,the review further documents how the role of XAI has shifted:rather than being used solely as a tool for interpreting models after training,it is increasingly integrated into the modeling cycle itself.Recent applications include its use in feature selection,adaptive sampling strategies,and model evaluation.The evidence also shows that GeoXAI extends beyond producing feature rankings.It reveals nonlinear thresholds and interaction effects that generate deeper mechanistic insights into hazard processes and mechanisms.Nevertheless,several key challenges remain unresolved within the field.These persistent issues are especially pronounced when considering the crucial necessity for interpretation stability,the demanding scholarly task of reliably distinguishing correlation from causation,and the development of appropriate methods for the treatment of complex spatio-temporal dynamics.
文摘Mortality prediction in respiratory health is challenging,especially when using large-scale clinical datasets composed primarily of categorical variables.Traditional digital twin(DT)frameworks often rely on longi-tudinal or sensor-based data,which are not always available in public health contexts.In this article,we propose a novel proto-DT framework for mortality prediction in respiratory health using a large-scale categorical biomedical dataset.This dataset contains 415,711 severe acute respiratory infection cases from the Brazilian Unified Health System,including both COVID-19 and non-COVID-19 patients.Four classification models—extreme gradient boosting(XGBoost),logistic regression,random forest,and a deep neural network(DNN)—are trained using cost-sensitive learning to address class imbalance.The models are evaluated using accuracy,precision,recall,F1-score,and area under the curve(AUC)related to the receiver operating characteristic(ROC).The framework supports simulated interventions by modifying selected inputs and recalculating predicted mortality.Additionally,we incorporate multiple correspondence analysis and K-means clustering to explore model sensitivity.A Python library has been developed to ensure reproducibility.All models achieve AUC-ROC values near or above 0.85.XGBoost yields the highest accuracy(0.84),while the DNN achieves the highest recall(0.81).Scenario-based simulations reveal how key clinical factors,such as intensive care unit admission and oxygen support,affect predicted outcomes.The proposed proto-DT framework demonstrates the feasibility of mortality prediction and intervention simulation using categorical data alone.This framework provides a foundation for data-driven explainable DTs in public health,even in the absence of time-series data.
基金supported in part by the National Natural Science Foundation of China under Grant 62371181in part by the Changzhou Science and Technology International Cooperation Program under Grant CZ20230029+1 种基金supported by a National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(2021R1A2B5B02087169)supported under the framework of international cooperation program managed by the National Research Foundation of Korea(2022K2A9A1A01098051)。
文摘The Intelligent Internet of Things(IIoT)involves real-world things that communicate or interact with each other through networking technologies by collecting data from these“things”and using intelligent approaches,such as Artificial Intelligence(AI)and machine learning,to make accurate decisions.Data science is the science of dealing with data and its relationships through intelligent approaches.Most state-of-the-art research focuses independently on either data science or IIoT,rather than exploring their integration.Therefore,to address the gap,this article provides a comprehensive survey on the advances and integration of data science with the Intelligent IoT(IIoT)system by classifying the existing IoT-based data science techniques and presenting a summary of various characteristics.The paper analyzes the data science or big data security and privacy features,including network architecture,data protection,and continuous monitoring of data,which face challenges in various IoT-based systems.Extensive insights into IoT data security,privacy,and challenges are visualized in the context of data science for IoT.In addition,this study reveals the current opportunities to enhance data science and IoT market development.The current gap and challenges faced in the integration of data science and IoT are comprehensively presented,followed by the future outlook and possible solutions.
基金Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDB0740000National Key Research and Development Program of China,No.2022YFB3904200,No.2022YFF0711601+1 种基金Key Project of Innovation LREIS,No.PI009National Natural Science Foundation of China,No.42471503。
文摘Deep-time Earth research plays a pivotal role in deciphering the rates,patterns,and mechanisms of Earth's evolutionary processes throughout geological history,providing essential scientific foundations for climate prediction,natural resource exploration,and sustainable planetary stewardship.To advance Deep-time Earth research in the era of big data and artificial intelligence,the International Union of Geological Sciences initiated the“Deeptime Digital Earth International Big Science Program”(DDE)in 2019.At the core of this ambitious program lies the development of geoscience knowledge graphs,serving as a transformative knowledge infrastructure that enables the integration,sharing,mining,and analysis of heterogeneous geoscience big data.The DDE knowledge graph initiative has made significant strides in three critical dimensions:(1)establishing a unified knowledge structure across geoscience disciplines that ensures consistent representation of geological entities and their interrelationships through standardized ontologies and semantic frameworks;(2)developing a robust and scalable software infrastructure capable of supporting both expert-driven and machine-assisted knowledge engineering for large-scale graph construction and management;(3)implementing a comprehensive three-tiered architecture encompassing basic,discipline-specific,and application-oriented knowledge graphs,spanning approximately 20 geoscience disciplines.Through its open knowledge framework and international collaborative network,this initiative has fostered multinational research collaborations,establishing a robust foundation for next-generation geoscience research while propelling the discipline toward FAIR(Findable,Accessible,Interoperable,Reusable)data practices in deep-time Earth systems research.
文摘Musculoskeletal injuries are among the most common causes of disability worldwide,with early detection and appropriate intervention critical to minimizing long-term complications.Infrared thermography(IRT)has emerged as a noninvasive,real-time imaging modality that captures superficial temperature changes reflecting underlying physiological processes such as inflammation and vascular alterations.This review explores the fundamental principles of medical thermography,differentiates between passive and active approaches,and outlines key technological advancements including artificial intelligence integration.The clinical utility of IRT is discussed in various contexts–ranging from acute soft tissue injuries and overuse syndromes to chronic pain and rehabilitation monitoring.Comparative insights with conventional imaging techniques such as ultrasound and magnetic resonance imaging are also presented.While IRT offers functional imaging capabilities with advantages in portability,safety,and speed,its limitations–such as lack of deep-tissue penetration and protocol standardization–remain significant barriers to broader adoption.Future directions include the integration of IRT with other imaging modalities and digital health platforms to enhance musculoskeletal assessment and injury prevention strategies.
文摘Editorial message Every advancement in the field of laboratory animal science and technology,from exploring basic mechanisms to validating the development of new drugs,and from establishing disease models to responding to public health emergencies,strengthens the foundation for human health and well-being,serving as an important cornerstone for promoting global scientific innovation.For this reason.
基金The National Key R&D project granted by the Ministry of Science and Technology(2024YFA0917200)Digital Museum Construction Project of Chinese Centre for Disease Control and Prevention(BB2110240080)Science Communication Project of Chinese Academy of Sciences(CX2090000008).
文摘Background:The advent of the self-media age,digital humanities,and artificial intelligence(AI)technologies is gradually reshaping the narrative frameworks of the history of science and technology in general and the history of medicine in particular,as it transforms the specific shape of contemporary medical science and health communication practice with the help of interactive,scenario-based communication ecosystems.Methods:This paper focuses on the interactive relationship between the history of science and science communication,employing historical tracing and case study comparison as research methods to explore the pathways and innovative models for reintegrating the history of science and technology including the history of medicine into contemporary scientific discourse.Results:The study finds that in the Chinese context,three key pathways facilitate the engagement of the history of science and technology including the history of medicine in science communication:administrative intervention,value reconstruction,and personalized adaptation.Specifically,administrative intervention promotes the integration of the history of science education into talent development through policy design;value reconstruction,centered on the scientific spirit,enhances societal cultural recognition of technological progress;and personalized adaptation leverages big data and social media technologies to enable precise and tailored knowledge dissemination.Conclusion:The rise of the“web-based knowledge brokering model”in the era of social media has introduced professional knowledge brokers,ensuring the accuracy and accessibility of science communication.These innovations not only serve as decision-making simulation tools for medical science and health communication,linking historical insights with contemporary practice,but also provide theoretical foundations and practical paradigms for realizing the value of the history of science and technology in the digital era.
