Progress And Prospective Of New Pollutants Study,
2026
Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Progress And Prospective Of New Pollutants Study, Ruan Ting, Chunyang Liao, Yawei Wang, Maoyong Song, Yaqi Cai, Guibin Jiang
Bulletin of Chinese Academy of Sciences (Chinese Version)
The governance of new pollutants has been becoming a critical strategic demand for the high-quality development of China. The policy will be further advanced during the coming National 15th Five-Year Plan period. Nevertheless, significant challenges remain in aspects such as list of controlled chemicals, standard development, measurement methods, alternative approaches, and remediation techniques. Existing experience in addressing traditional pollutants remains insufficient to adequately address the concealed and complex ecological and/or health risks associated with new pollutants. Thus, a strengthening of basic research is the optimal approach to tackling these challenges and avoiding detours. To better identify the critical scientific challenges …
Black Soil Organic Carbon Plays A Critical Role In Ensuring Food Security,
2026
State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin 150081, China
Black Soil Organic Carbon Plays A Critical Role In Ensuring Food Security, Zhang Xingyi, Qingsong Shen, Mingming Guo, Na Li, Qiang Chen, Wei Hu, Jianye Li, Yimin Chen, Yansheng Li, Xiaobin Liu
Bulletin of Chinese Academy of Sciences (Chinese Version)
Carbon-rich Black Soils are an important natural resource ensuring China’s food security, and their soil carbon stocks are closely related to grain production capacity. Based on nearly two decades of regional survey data and long-term field experiments, this study systematically investigated the dynamics of soil organic matter (SOM), its response relationship with crop productivity, and strategies for soil fertility improvement. The results showed that soil carbon stocks in the topsoil (0–20 cm) of the Black Soil region in Northeast China have declined by approximately 60%. In 2019, the regional average SOM content was approximately 36 g/kg and was decreasing at …
Open Sharing And Collaborative Governance: Practices And Implications Of National Institutes Of Health’S Digital Transformation,
2026
Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China; School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China
Open Sharing And Collaborative Governance: Practices And Implications Of National Institutes Of Health’S Digital Transformation, Long Yuntao, Bingzhi Wang, Zheping Xu, Yang Wang
Bulletin of Chinese Academy of Sciences (Chinese Version)
With the rapid development of information technology, research projects and tasks of research institutes are increasing rapidly. Scientific and technological resources are the core and foundation of scientific research work, and scientific research institutes are faced with the needs of processing, management and coordination of a large number of scientific and technological resources. Digital transformation has become an inevitable choice for the high-quality development of scientific research institutes. The U.S. National Institutes of Health (NIH), as the world’s top scientific research institute, has continuously introduced a number of initiatives in the field of digital transformation, such as institutional reform policies, …
Gao Fu: Breaking Through Constraints Of “Brain Block” And Unleashing Potential Of Scientific And Technological Innovation,
2026
Chinese Academy of Sciences, Beijing 100864, China
Gao Fu: Breaking Through Constraints Of “Brain Block” And Unleashing Potential Of Scientific And Technological Innovation, Editorial Board Of Bulletin Of Chinese Academy Of Sciences, Fu Gao
Bulletin of Chinese Academy of Sciences (Chinese Version)
No abstract provided.
A Study On Adaptive Governance Of "Open Competition Mechanism For Selecting Best Candidates" Projects From An Information Asymmetry Perspective,
2026
Shaanxi Institute of Science and Technology Information, Xi'an, 710054
A Study On Adaptive Governance Of "Open Competition Mechanism For Selecting Best Candidates" Projects From An Information Asymmetry Perspective, Xi Wu, Wei Zhang, Lei Li, Jie Chen, Xiuni Zhang
Journal of Scientific Information Research
[Purpose/significance] "Open Competition Mechanism for Selecting Best Candidates" is a new research management model proposed by China to break through key core technologies, which is of great significance for addressing "bottleneck" technical problems.[Methods/process] Based on information asymmetry theory, complexity science theory, and adaptive governance theory, this paper adopts theoretical interpretation, case study, and comparative analysis. It systematically diagnoses information asymmetry issues in the project management of this mechanism; constructs a three-dimensional adaptive governance framework of" Perception—Diagnosis, Response—Design, Accumulation—Learning"; designs adaptive governance tools by drawing on the experience of the U.S. Defense Advanced Research Projects Agency(DARPA)model; and conducts empirical verification with …
Changes And Impacts Of American Open Science Policies Against The Background Of De-Globalization: With A Discussion On China's Responses And Actions,
2026
Northwest University School of Public Administration, Xi’an 710127
Changes And Impacts Of American Open Science Policies Against The Background Of De-Globalization: With A Discussion On China's Responses And Actions, Mujun Li, Zheng Wang, Xingzhu Li, Wei Li
Journal of Scientific Information Research
[Purpose/significance] The wave of deglobalization has impacted the global development trajectory of Open Science, with U.S. Open Science policies undergoing a drastic contraction. It is necessary to understand this reconstructive trend of Open Science and identify the development opportunities therein. [Method/process] By introducing a "deglobalization" perspective and drawing on the policy tracking audit method, this study examines samples of U.S. Open Science policies and conducts an in-depth analysis of the underlying motivations and impacts. [Result/conclusion] During the era of deglobalization, the United States has significantly reduced the implementation and on-the-ground effectiveness of its Open Science policies through executive orders, funding …
Made In America, Hidden By Ai: Ai Shopping Chatbots Reveal How Amazon And Walmart Hurt American Manufacturers And Deceive Shoppers,
2026
Columbia Law School, Center for Law and the Economy
Made In America, Hidden By Ai: Ai Shopping Chatbots Reveal How Amazon And Walmart Hurt American Manufacturers And Deceive Shoppers, Erie Meyer, Zachary Harris
Center for Law and the Economy
This article investigates the capabilities of two AI shopping agents — Alexa for Shopping and Sparky, operated by Amazon and Walmart respectively — to identify country of origin for products on their respective platforms and flag potential “Made in USA” misrepresentations — where products with “Made in USA” in their title or listing have another country or “imported” listed as their country of origin. This article finds that (1) Amazon and Walmart have the technical capability to detect and flag “Made in USA” fraud; (2) “Made in USA” fraud appears to be common on both Amazon and Walmart; (3) Amazon …
Expanding The Cognitive Attentional Standards Platform Through Artificial Influence Assessment (Aia): Rationale, Development, And Measurement Design,
2026
University of Central Florida
Expanding The Cognitive Attentional Standards Platform Through Artificial Influence Assessment (Aia): Rationale, Development, And Measurement Design, Delante Clark
Graduate Scholarship and Creative Works
Artificial intelligence is increasingly shaping how individuals access information, make decisions, and interact with digital environments. The Cognitive Attentional Standards Platform (C.A.S.) was developed to assess attention related harms, cognitive safety, digital autonomy, and platform influence across digital systems (Clark, 2026). However, the growth of generative AI, conversational agents, and algorithmic decision support technologies has introduced new forms of influence that may not be fully captured by existing assessment domains. This paper proposes the Artificial Influence Assessment (AIA) as an expansion of the C.A.S. framework designed to measure AI mediated influence on cognition, behavior, autonomy, and information processing. Drawing on …
Governing Algorithmic Attention: Attention Safeguard Models And The Cognitive Attentional Standard As System Level Interventions In Human Computer Interaction, Behavioral Economics, And Artificial Intelligence,
2026
University of Central Florida
Governing Algorithmic Attention: Attention Safeguard Models And The Cognitive Attentional Standard As System Level Interventions In Human Computer Interaction, Behavioral Economics, And Artificial Intelligence, Delante Clark
Graduate Scholarship and Creative Works
Algorithmic recommendation systems and interface designs shape attention by combining visually salient cues with uncertain reward timing and low friction interaction. These conditions can sustain anticipatory checking, extend time on task, and reduce natural disengagement points through patterns such as infinite scrolling and autoplay. This paper synthesizes research across neuroscience, human computer interaction, behavioral economics, and artificial intelligence to argue that attention capture is a predictable outcome of incentive driven design rather than an individual failure of self regulation. It advances the Attention Safeguard Models and the Cognitive Attentional Standard as system level interventions that regulate exposure conditions, pacing, and …
Preface Of National Think Tank In Science And Technology: Ai Empowers Scientific Research,
2026
Chinese Academy of Sciences
Preface Of National Think Tank In Science And Technology: Ai Empowers Scientific Research
Bulletin of Chinese Academy of Sciences (Chinese Version)
No abstract provided.
Disciplinary System Of Artificial Intelligence: Connotation, Architecture, And Development Suggestions,
2026
Chinese Academy of Sciences, Beijing 100864, China
Disciplinary System Of Artificial Intelligence: Connotation, Architecture, And Development Suggestions, Academic Divisions Of The Chinese Academy Of Sciences Discipline Group Of Advisory Project On Ai-Empowered Scientific Research
Bulletin of Chinese Academy of Sciences (Chinese Version)
The discipline of artificial intelligence studies the theories, methods, systems, applications, enabling functions, ethics, and governance of artificial intelligence, and is a typical interdisciplinary field. With the rapid development of artificial intelligence in recent years, its disciplinary connotations and system architecture urgently require renewed examination. Based on the analysis of development trends of artificial intelligence, this paper elucidates the connotations of the AI discipline from four perspectives: theoretical methods, forms of intelligence, disciplinary integration, and application empowerment. It further proposes a disciplinary system framework for artificial intelligence comprising foundational supporting disciplines, core body of knowledge, major forms of intelligence, and …
Artificial Intelligence Empowers Particle Physics And Nuclear Physics: From Fundamental Research To Major Applications,
2026
Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
Artificial Intelligence Empowers Particle Physics And Nuclear Physics: From Fundamental Research To Major Applications, Yifang Wang, Yuan He, Yao Huang, Wanbing He, Yi Jiao, Congqiao Li, Ke Li, Beijiang Liu, Yingqi Ma, Yugang Ma, Longgang Pang, Fazhi Qi, Sichao Tan, Chunpeng Wang, Meng Wang, Xiaoheng Xu, Xing Xu, Zhentang Zhao, Yingxun Zhang, Zhengde Zhang, Hongwei Zhao, Lina Zhao
Bulletin of Chinese Academy of Sciences (Chinese Version)
Particle physics and nuclear physics are core foundational disciplines for exploring the fundamental structure of matter and the origin of the universe. The deep integration of artificial intelligence (AI) technology is providing entirely new pathways to address systemic challenges such as the processing of massive amounts of multimodal data, the realization of extreme experimental conditions, bottlenecks in theoretical calculations, and the intelligent control of large-scale scientific facilities. The article systematically elaborates on how AI deeply empowers particle physics and nuclear physics, particularly in major application scenarios such as research on the fundamental structure and origin of mass of matter, the …
Consolidating Chemical Substance Creation Capability Through Ai For Science-Enabled Innovation Equity,
2026
National Key Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China, Hefei 230026, China
Consolidating Chemical Substance Creation Capability Through Ai For Science-Enabled Innovation Equity, Mengchu Jin, Wandong Wang, Jun Zhang, Yi Luo, Zaiku Xie, Jinlong Yang, Jun Jiang
Bulletin of Chinese Academy of Sciences (Chinese Version)
AI for Science (hereinafter referred to as AI4S) is driving profound changes in the paradigm of scientific research. Chemistry, as a central discipline for creating new substances and supporting major national strategic needs such as energy, health, dual carbon goals, advanced manufacturing, and ecological governance, is an important application scenario of AI4S. At present, innovation in the discipline of chemistry by young researchers still faces knowledge silos, capability silos, and resource silos: the accumulation of professional knowledge requires years of effort, frontier knowledge is highly differentiated, experimental capabilities are difficult to reuse, and high-end resources are difficult to coordinate, which …
Artificial Intelligence-Enabled Materials Innovation: Implementation Levels And Strategic Layout,
2026
Dongguan Institute of Materials Science and Technology, Chinese Academy of Sciences, Dongguan 523830, China; Songshan Lake Materials Laboratory, Dongguan 523830, China
Artificial Intelligence-Enabled Materials Innovation: Implementation Levels And Strategic Layout, Ziwei Zhao, Fengxiang Zhou, Yanglili Zhou, Can Wang, Pei Zhang, Weihua Wang
Bulletin of Chinese Academy of Sciences (Chinese Version)
Materials innovation has long been constrained by vast design spaces, complex processing routes, lengthy validation cycles, and difficulties in engineering translation. Traditional research and development models, which mainly rely on accumulated experience, theoretical deduction, and experimental trial and error, have become increasingly insufficient to meet the demand for rapid breakthroughs in critical materials. In recent years, artificial intelligence has been increasingly integrated into materials design, synthesis, and processing, characterization, evaluation, optimization, and application feedback, promoting the transformation of materials innovation from experience-driven exploration to data-driven development and from discrete trial and error to closed-loop optimization. Based on an analysis of …
Artificial Intelligence Empowered Biological Research: Paradigm Shifts, Application Scenarios, And Strategic Layout,
2026
Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200032, China
Artificial Intelligence Empowered Biological Research: Paradigm Shifts, Application Scenarios, And Strategic Layout, Xinguang Zhu, Yiming Bao, Zhenong Jin, Xin Li, Sijia Wang, Yueming Wang, Yungui Yang, Cao Xu, Yan Xiong, Bin Han
Bulletin of Chinese Academy of Sciences (Chinese Version)
Life related processes are characterized by high dimensionality and multi-scale properties. Understanding mechanisms underpinning life processes helps promote national healthcare, agricultural development, sustainable ecological civilization, and national security. Current life science research is confronted with an enormous challenge of dimensionality stemming from data explosion and data fragmentation, for which the recent rapid advancement of artificial intelligence (AI) provides novel solutions. AI will catalyze a paradigm shift in life science research from the current experiment based empirical induction to a new closed-loop knowledge acquisition including large scale data collection, model building, model prediction, experimental validation, and iterative of these procedures. Life …
Artificial Intelligence–Driven Paradigm Transformation In Biopharmaceutical R&D: Applications And Emerging Scenarios,
2026
Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
Artificial Intelligence–Driven Paradigm Transformation In Biopharmaceutical R&D: Applications And Emerging Scenarios, Lili Liu, Mingyue Zheng, Ye Yuan, Xutong Li, Rong Fan, Wei Wei, Jinxin Zhao, Guobin Qi, Hua Yue, Likun Gong, Songping Zhang, Jiachen Li, Yuchen Sun, Xiaoyan Chen, Yao Chen, Xin Liu, Xiao Zhang, Yuehong Gao, Jianfeng Li, Kaixian Chen, Guanghui Ma, Jianmin Yue
Bulletin of Chinese Academy of Sciences (Chinese Version)
The biopharmaceutical industry is a critical domain underpinning national scientific and technological innovation development and public health. With the rapid advancement of artificial intelligence (AI) and its deep integration with the life sciences, biomedicine research is undergoing a paradigm shift from traditional experience-driven trial-and-error approaches to data-driven and predictive validation-based models. This study systematically examines the pathways for reshaping research in biomedicine paradigms under the convergence of data-driven, mechanism-driven, and intelligence-driven approaches. It focuses on recent advances in the application of AI across key stages, including drug discovery and design, druggability evaluation, delivery system design and optimization, nonclinical and clinical …
Artificial Intelligence For Cybersecurity: Opportunities, Challenges, And Approaches,
2026
Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100085, China
Artificial Intelligence For Cybersecurity: Opportunities, Challenges, And Approaches, Kai Chen, Ding Li, Guozhu Meng, Shouling Ji, Changjiang Li, Yi Yang, Dengguo Feng
Bulletin of Chinese Academy of Sciences (Chinese Version)
Cybersecurity research, institutional structures, and governance policies are undergoing profound transformations. Currently, increasingly covert and rapidly evolving intelligent attacks, coupled with the national urgent expectations for high-level security, are driving significant shifts in the roles and interactions of governments, research institutions, and enterprises. Consequently, this study, based on analyzing the challenges and opportunities of the AI era, explores core application scenarios such as critical information infrastructure protection, national data security, and the maintenance of cyberspace sovereignty. It provides an analysis of artificial intelligence in dimensions such as correlation and causality, and proposes a governance framework, aiming to provide insights for …
Artificial Intelligence For Astronomy: Strategic Opportunities, Policy Challenges And Development Strategies,
2026
University of Science and Technology of China, Hefei 230026, China
Artificial Intelligence For Astronomy: Strategic Opportunities, Policy Challenges And Development Strategies, Jin Chang, Yihan Song, Bing Du, Kefei Wu, Ali Luo, Jifeng Liu
Bulletin of Chinese Academy of Sciences (Chinese Version)
To alleviate the bottlenecks hindering the integrated development of artificial intelligence and astronomy in China and to reinforce the country’s strategic edge in science and technology, this study uses systematic analysis and path-comparison approaches to examine the policy requirements for their deep integration. The findings indicate that this topic is closely tied to global competition in science and technology, strategic security, and industrial upgrading. At present, the world has entered a new “astronomy + AI” paradigm, with the United States and the European Union already having taken the lead in establishing corresponding strategic frameworks. Leveraging major scientific infrastructures such as …
Artificial Intelligence Empowering Space Science—Case Study Of Space Weather,
2026
National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
Artificial Intelligence Empowering Space Science—Case Study Of Space Weather, Chi Wang, Hui Li, Bingxian Luo, Fang Shen, Jingjing Wang, Lingqian Zhang, Yi Yang, Dong Zhao
Bulletin of Chinese Academy of Sciences (Chinese Version)
Space science is currently confronted with a triple challenge: the explosive growth of observational data, the strongly coupled cross-scale nature of physical processes, and the increasingly urgent national strategic demands. The limitations of traditional research paradigms in analytical efficiency, forecast accuracy, and autonomous capability hinder their effectiveness in meeting critical requirements such as safeguarding on-orbit satellites and ensuring the successful execution of major space missions. This study proposes a three-layer “perception–cognition–decision-making” architecture for intelligent space science. Taking space weather—a domain with strong operational relevance—as a representative case, the four-dimensional paradigm transformation driven by artificial intelligence is systematically examined across key …
Artificial Intelligence Empowering Remote Sensing: Challenges, Paradigms And Strategic Layout,
2026
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; National Key Laboratory of Target Cognition and Application Technology, Beijing 100190, China
Artificial Intelligence Empowering Remote Sensing: Challenges, Paradigms And Strategic Layout, Jiayuan Shen, Peirui Cheng, Zhirui Wang, Wei Liang, Xian Sun, Yirong Wu
Bulletin of Chinese Academy of Sciences (Chinese Version)
Remote sensing science and technology, as a key discipline for Earth observation and global change research, faces systemic challenges in processing massive multi-source data, accurately extracting complex information, and delivering high-timeliness application services. The rapid advances in artificial intelligence (AI) provide a new opportunity to address the deep-seated dilemma in remote sensing of being “data-rich but insufficient in effective information mining”. Guided by a problem-oriented approach, this study first systematically analyzes the core challenges facing the development of remote sensing across four dimensions: data understanding, technical methods, scientific mechanisms, and application ecosystems. It then reviews the technical evolution of AI-empowered …
