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Association Between Stress And Prolactin Hormone Levels: A Mini-Review, Sara Salah Mahdi, Huda S. Abdulghani

Hilla University College Journal For Medical Science

The physiological functions of prolactin are highly varied, despite the fact that it is most commonly recognized for its participation in the inhibition of reproduction and the regulation of breastfeeding. The conditions known as hyperprolactinemia can have a variety of origins, some of which are physiological and others of which are pathologic. The following are examples of physiological causes: pregnancy, breastfeeding, sleep-related, stimulation of the nipples and sexual orgasm, stimulation or trauma to the chest wall. Another significant physiological factor that contributes to hyperprolactinemia is stress, and the clinical importance of this factor is currently being investigated. This paper aims …

Antibiotic Resistance And Sensitivity Patterns In Pneumonia Pathogens: A Comprehensive Study Of Bacterial Isolates And Their Implications For Treatment In Diyala Province, Anfal Abd_Ulmunem Rasheed, Anfal Shakir Motib, Rafid Abdul-Mahdi Hasani

Hilla University College Journal For Medical Science

Background: Pneumonia is an inflammatory process affecting the airways and lung parenchyma, characterized by alveolar inflammation that leads to infiltration and consolidation of the lungs and disruption of gas exchange, which may result in respiratory distress.

Objectives: This study aims to identify the bacterial species that cause pneumonia and to determine their antibiotic resistance patterns.

Methods: This cross-sectional observational study assessed antibiotic resistance among patients with pneumonia in Diyala Province. Patients were identified from hospital and laboratory records over a four-month period (December 1st, 2024 - March 29th, 2025), yielding 100 patients, comprising 55 males and 45 females.

Results: The …

Molecular Detection Of Virulence Genes And Antibiotic Resistance In Uropathogenic Escherichia Coli: Focus On Babylon Province, Iraq, Lara Hashem Abdzaid, Tiba Habeeb Saifi, Jwan Ahmed Ali, Layth Jasim Mohammed, Isaac Karimi

Hilla University College Journal For Medical Science

Background: Urinary tract infections (UTIs) affect individuals of all ages, with uropathogenic Escherichia coli (UPEC) being their primary causative agent. The accumulation rate of antimicrobial resistance poses a major public health challenge, underscoring the need for genetic monitoring of resistant strains.

Objectives: This study aimed to find virulence genes and antibiotic resistance in UPEC.

Materials and Methods: 110 patients, including 65 females and 45 males, aged 15 to 40 years, were screened for UPEC at Al-Hilla city between January and March 2025. Urine samples were collected to identify E. coli and to analyze associated virulence factors.

Results: Biochemical tests confirmed …

Fragile Hope And The Cultural Life Of Law, Shefali Jain

Socio-Legal Review

This review of Sandhya Fuchs’ Fragile Hope: Seeking Justice for Hate Crimes in India (Stanford University Press 2024) highlights that the book makes a genuinely original ethnographic and conceptual contribution to caste studies and hate crime scholarship. At the same time, the essay argues that there are three limitations to its framework that require greater engagement: the book’s failure to engage with the legal consciousness tradition in socio-legal scholarship, an underdeveloped account of “legal meliorism,” and an unresolved tension between the book’s stated commitment to victim-centred analysis and its ethnographic evidence that frequently discusses movement-level aspirations.

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, 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, 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, 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, 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, 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, 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, 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, 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, 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, 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 …

Artificial Intelligence For Deep Earth Science: Key Challenges, Major Application Scenarios And Development Pathways, Qingyun Di, Liang Zhao, Yikang Zheng, Zhi Geng, Zhichao Yu, Xiaocai Shan, Chao Li, Zhiyao Xu, Pengfei Lv

Bulletin of Chinese Academy of Sciences (Chinese Version)

Deep Earth science is central to understanding Earth’s internal architecture and the coupled evolution of its major spheres, while also underpinning energy security, the supply of critical mineral resources, and resilience to major geohazards. Nevertheless, the advancement of deep Earth science is currently hindered by insufficient in situ observations under extreme conditions, the difficulty of integrating multi-source heterogeneous data, and the limited capability to model complex multiphysics coupling processes. Recent advances in artificial intelligence offer a potential route beyond these limitations. By integrating data-driven learning with physical and geological understanding, AI is reshaping deep Earth science from empirical interpretation to …

Artificial Intelligence For Science: Connotations, Characteristics, And System, Kaihua Chen, Heyang Li, Hongxin Liu, Binbin Zhao, Shuo Yang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence is profoundly transforming the fundamental nature of scientific research, reshaping its modes of knowledge production and organizational operation, driving the emergence of a new artificial intelligence for science (AI4S) research paradigm, and accelerating full-chain innovation paradigm transformation. This study defines the basic connotations of AI4S across three dimensions, namely, enabling applications, tools and methods, and epistemic knowledge, and systematically identifies five core characteristics: human-machine symbiosis, autonomous evolution, interdisciplinary integration, resource intensity, and open ecosystems. It further constructs a supporting system and operational architecture encompassing layers of infrastructure, data resources, model tools, task execution, and application scenarios. Building on …

Building Basic Research Ecosystem To Consolidate Foundation Of Strong Nation, Xin Fang, Ke Wen

Bulletin of Chinese Academy of Sciences (Chinese Version)

Basic research is the source of the entire scientific system and the master switch for all technological problems. This study systematically reviews the evolution of the connotation and functions of basic research, and explores the new characteristics of basic research development triggered by the paradigm shift of AI for Science (AI4S): the shift of activity subjects from human‑dominated to human‑machine collaboration, the comprehensive restructuring of organizational models, the increasingly prominent strategic value of public intelligent research infrastructure, and the growing urgency to coordinate security and governance institution building. Addressing the demands of the new era, the study proposes principles and …

Optimizing Institution Of Demand-Oriented Basic Research, Promoting Deep Integration Of Technological Innovation And Industrial Innovation, Wei Lyu

Bulletin of Chinese Academy of Sciences (Chinese Version)

From both theoretical and domestic and international practical perspectives, this study analyzes the connotation and classification of demand-oriented basic research. It examines the expenditure structure, main pathways, and major existing problems of demand-oriented basic research in China. Based on three levels—strategically guided systematic basic research, frontier-guided exploratory basic research, and market-oriented applied basic research—it categorizes and studies the funding mechanisms and organizational models of demand-oriented basic research in combination with practice, and provides relevant suggestions for improving the quality enhancement mechanisms of demand-oriented basic research.

Logic And Path Of Transformation Reform Between Old And New Research Evaluation Models, Fang Xu, Xiaoxuan Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

The national 15th Five-Year Plan once again emphasizes breaking the four-only criteria. Why is it so difficult to dismantle the four-only criteria? This study argues that an in-depth analysis of the underlying logical relationship between the old label-based evaluation model and the new connotation-oriented quality evaluation model is required to address this question. The study finds that the label-based evaluation model is a rational choice under specific historical circumstances and it has delivered positive effects. During the transition toward connotation-oriented quality evaluation, problems concerning indicators such as academic papers have been well resolved. Nevertheless, national science and technology awards and …

Upholding Long-Termism In Basic Research To Shape Leading Advantage Of Automotive Industry, Yubo Lian

Bulletin of Chinese Academy of Sciences (Chinese Version)

General Secretary Xi Jinping has pointed out that basic research is the origin of the entire scientific system and the master switch for all technological issues, emphasizing that it must be advanced with greater efforts and more concrete measures. Upholding long-termism in basic research means placing it at the foundation of the innovation chain and maintaining continuous investment with strategic patience characterized by a long-term horizon and high tolerance for failure. Drawing on the author’s industrial practice, this study systematically reviews the characteristics and roles of basic research throughout the development of China’s new energy vehicle industry. In light of …

Advancing Paradigm Of Quantitative Synthetic Biology And Strengthening Mission-Oriented Basic Research, Chenli Liu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Synthetic biology is an important frontier in the life sciences, yet its further development remains constrained by limited capacity for rational design. Quantitative synthetic biology, which iteratively integrates quantitative modeling with the construction and analysis of synthetic systems, offers a promising paradigm for addressing this challenge. In this perspective, the study discusses the background and motivations underlying the emergence of this field and summarizes recent developments and exploratory efforts. Considering the unique characteristics of quantitative synthetic biology, it is suggested that progress in the field may benefit from strategically organized collaborative research that balances mission-oriented goals with investigator-driven exploration. On …

Viewpoints On Elevating Capability And Appreciation Of Basic Research, Guojie Li, Wei Zhao

Bulletin of Chinese Academy of Sciences (Chinese Version)

The overall capability and appreciation of a country’s basic research are not solely determined by the efforts of individual researchers, but also hinge on the country’s scientific and technological institutional mechanisms and policies. This article presents several viewpoints and suggestions from the perspectives of comprehensively and deeply understanding the connotation of basic research, increasing the proportion of investment in basic research, enhancing the stable support for basic research, and the paradigm shift of AI-driven basic research. These suggestions include: by 2030, adjusting the ratio of pure basic research to oriented basic research from 3.5∶6.5 to 4.5∶5.5, maintaining a balance between …

Problem Formation In Basic Research: Historical Evolution And Contemporary Transformation, Jialing Lyu, Ying Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

“Topic selection” in basic research has long been a central issue in S&T and innovation policy. Traditionally, it has often been understood as the processes of designating promising projects from an existing topic list through peer review and procedural evaluation. Nevertheless, major scientific problems do not always preexist within disciplinary systems, nor are landmark scientific discoveries artificially pre-planned in advance. Rather, they gradually emerge through the continuous interaction among national strategic demands, technological evolution, industrial transformation, and major real-world challenges. This study argues that important directions in basic research are often shaped by the sustained pull of real-world problems on …

Deep Learning Processor: Road To Fundamental Research On Ai Chip, Yunji Chen

Bulletin of Chinese Academy of Sciences (Chinese Version)

Deep learning processor chips serve as an important computation foundation for the artificial intelligence industry, thus has attracted widespread attention from the international communities. The Institute of Computing Technology, Chinese Academy of Sciences took the lead in initiating fundamental research on deep learning processor chips in 2008. At that time, this research direction had not yet entered the mainstream vision of the international communities, with its academic value and development laws yet to gain widespread recognition, and it was confronted with the challenges of three fundamental scientific issues concerning its significance, principle, and architecture.To address the above issues, the research …

Leading Big Science Initiative And Boosting Basic Research, Nianzhi Jiao

Bulletin of Chinese Academy of Sciences (Chinese Version)

As a core model for conducting cutting-edge research through global collaboration, major international science initiative (ISI) has comprehensively reshaped the development scope, resource landscape, research paradigms, talent systems, and governance ecosystems of basic research (BR). ISI and BR are deeply integrated and iteratively coordinated, forming a vital strategy for humanity to tackle major global scientific challenges. Against the backdrop of deep intertwining between scientific and technological competition and global governance, China taking the lead in ISI has become a strategic imperative for the new era, with the UN Ocean Decade Program ocean negative carbon emissions (ONCE) serving as a successful …

On Crucial Role Of The Spirit Of Chinese Scientists In Basic Research, Xin Wang, Chuanxi Wang, Changpu Sun

Bulletin of Chinese Academy of Sciences (Chinese Version)

Basic research is the source of original innovation and the foundation for building a strong nation in science and technology. Compared with applied development research and engineering research, basic research is primarily concerned with exploring the frontiers, proposing new concepts, discovering new laws, and establishing new theories. Its outcomes are often difficult to predict in advance and are rarely subject to sufficient experimental and practical verification within a short time frame. These characteristics expose basic research to three inherent challenges in the philosophy of science. First, the experimental verification of fundamental theories often requires a long period of time. Second, …

Quality Improvement Project: Implementation Of The Patient Health Questionnaire-9 Modified For Teens, Hedy Gerber, Leah Buchko, Jennifer Van Winkle

All Faculty and Staff Scholarship

Background: Adolescent depression is a prevalent and significant public health concern, strongly linked to increased suicidality, poor health outcomes, impaired psychosocial functioning, and substantial societal costs. Although measurement‑based care using validated screening instruments is recommended by clinical practice guidelines, routine use of standardized depression screening tools remains limited in mental health settings.

Objective: The purpose of this quality improvement project was to assess the impact of implementing the Patient Health Questionnaire-9 modified for teens (PHQ-9M) in depression screening rates among adolescents aged 11-17 years at an outpatient mental health clinic in Southern Colorado.

Methods: A quantitative, quasi‑experimental pre- and post-intervention …

Hierarchical Parcel Swapping: A Novel Model In Turbulence, Masoomeh Behrang

Theses and Dissertations

Turbulent mixing plays a central role in a wide range of engineering and natural systems, particularly in reactive flows where turbulence--chemistry interactions strongly influence reaction rates, flame structure, and emissions. Accurately modeling these interactions remains a major challenge due to the multiscale and stochastic nature of turbulence, as well as the nonlinear coupling between transport and chemical kinetics. This dissertation develops and evaluates the Hierarchical Parcel Swapping (HiPS) model, a fully stochastic framework designed to represent turbulence-driven transport and scalar mixing without relying on traditional gradient-based closures. HiPS is investigated both as a standalone turbulence model and as a subgrid …

Open Data From Ligo, Virgo, And Kagra Through The First Part Of The Fourth Observing Run, A. G. Abac, I. Abouelfettouh, Teviet Creighton, Mario C. Diaz, Raul Alberto Espinosa Perez, J. Lawrence, Francisco Llamas Villarreal, Soma Mukherjee, Volker Quetschke, Miriam Ramos Arevalo, Wenhui Wang

Physics & Astronomy Faculty Publications

LIGO, Virgo, and KAGRA form a network of gravitational-wave observatories. Data and analysis results from this network are made publicly available through the Gravitational Wave Open Science Center. This paper describes open data from this network, including the addition of data from the first part of the fourth observing run and selected periods from the preceding engineering run, collected from 2023 May to 2024 January. The public dataset includes calibrated strain time series for each instrument, data from additional channels used for noise subtraction and detector characterization, and analysis data products from version 4.0 of the Gravitational-Wave Transient Catalog.