Molecular Characterization And Genotyping Of Candida Species Isolated From The Nasal Cavity Of Patients With Nasal Infections In Iraq, Amran M. Al-Erjan, Hind Tahseen Ibrahim

Hilla University College Journal For Medical Science

Background: Nasal infections are commonly associated with opportunistic microorganisms, particularly Staphylococcus aureus and Candida species.

Objectives: This study aimed to molecularly characterize Candida species isolated from the nasal cavity of patients with nasal infections and to determine their phylogenetic relationships using the internal transcribed spacer (ITS) region.

Methods: A total of 88 nasal swab samples were collected from patients aged 1–80 years in Thi-Qar Province, Iraq, between December 2023 and March 2024. Samples were cultured on Sabouraud Dextrose Agar and Mannitol Salt Agar. Yeast isolates were identified phenotypically using CHROMagar Candida and germ tube tests. Molecular identification and genotyping were …

Malondialdehyde And Ceruloplasmin: A More Sensitive And Specific Marker Than Other Obesity Markers For Diagnosis Of Obese Individuals, Sawen Tahseen Taha

Hilla University College Journal For Medical Science

Background: Higher levels of lipid peroxidation are associated with obesity. Malondialdehyde (MDA) is a byproduct of this process and acts as a biomarker. Plasma ceruloplasmin (Cp) is also connected to obesity and is considered a risk factor for cardiovascular disease.

Objectives: This study aimed to measure MDA and CP levels in obese people and compare them with levels in people of normal weight, including both men and women.

Methods: Case and control study was conducted on a total (90) participants, consisting of (45) Normal individuals with BMI <25 Kg/m2, (45) Obese individuals with BMI ≥ 30 Kg/m2 were enrolled in the study. Serum MDA and CP were estimated using the ELISA technique. The present study was carried out from 8th January 2024, to 1st May 2024, at Rizgary Hospital, Cardiac Center, and Cihan University.

Results: Malondialdehyde (MDA) was assessed in both groups. Sensitivity and specificity for MDA …

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 …

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 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 …

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, …

2026issue6content

Bulletin of Chinese Academy of Sciences (Chinese Version)

No abstract provided.

Engineering 3d Optical Interconnects And Low-Power Radio Frequency Gaze Tracking, Blake P. Crosby

Theses and Dissertations

This thesis presents two independent research works in optical in- terconnects and radio-frequency (RF)-based gaze tracking. The first work demonstrates a silicon optical waveguide fabricated from four through-silicon vias (TSVs) produced using two-photon-absorption- assisted photo-electrochemical etching. Unlike conventional TSV fabrica- tion methods, this approach enables highly localized, non-line-of-sight etching in silicon using a focused femtosecond laser. Four approximately 5 μm diameter TSVs were etched through a 200 μm silicon wafer in a 7 μm by 7 μm pattern, leaving a central silicon region that functions as a waveguide. The fabricated structure achieved an aspect ratio of approxi- mately 40:1 with …

Effects Of A Peer Mentoring Program For Adolescent Newcomers On Feelings Of Peer Connectedness And School Belonging, Eden Elizabeth Moon Barnhill

Theses and Dissertations

There is a significant lack of empirical evidence regarding the effectiveness of peer mentoring to support newcomer students, particularly for refugee populations. This study evaluated the effects of a peer mentor program for newcomer students on their feelings of peer connectedness and school belonging in a high school setting. Participants were made up of 15 newcomer student mentees across three high schools. Measures were administered pre- and post-intervention, and participants were also interviewed about their experience. Results indicated no quantitative findings of significance but did yield a small positive effect size for peer connectedness. According to qualitative data, many participants …

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 …

Service Providers' Descriptions Of Survivors' Experiences With Mental Health Treatment, Melanie Gonzales Puente

Theses and Dissertations

Human trafficking survivors experience significant mental health challenges and barriers that limit their engagement towards treatment. A qualitative study was conducted that included semi-structured interviews of 33 professionals working with survivors of human trafficking in the United States. Findings indicate that survivors' engagement in treatment is limited by mistrust of providers, stigma, and a lack of access to services. Providers emphasize that addressing basic needs (e.g., safety and housing) must occur before engaging in trauma-focused therapy. Positive outcomes are associated with strong therapeutic relationships, autonomy, trauma-informed, individualized care, and offering comprehensive services. Furthermore, mental health providers should have certain abilities …

2026-06-20 Commencement Struggle Prompts Outcry Over Palestine And Treatment Of Muslim Students, Dylan Berman, Tristan Scott

The Spectator Online

No abstract provided.

Can Hope Be Changed In 30 Minutes? The Development, Refinement, And Pilot Evaluation Of A Hope-Based Single-Session Intervention, Aileen Kangavary

USF Tampa Graduate Theses and Dissertations

Background: Although mental health problems are on the rise among youth, nearly 80% do not access treatment. Schools serve as key settings to address adolescent mental health and wellness needs given the substantial barriers that limit access to community-based mental health services. Despite this potential, schools often face implementation challenges. Therefore, scalable and accessible approaches are needed to meet the growing demand for adolescent mental health support. Single-Session Interventions (SSIs) represent a promising, cost-effective, and digital avenue for providing timely mental health support to youth. Increasingly, research conceptualizes mental health through a two-dimensional framework that includes the presence of well-being …

Rheological Protocol To Assess And Optimize Latex Coagulation Dynamics For The Thin Glove Coagulant Dipping Process, Monday U. Okoronkwo, Kok Kong Ng, Wolfram Franke, Gaurav Sant

Chemical and Biochemical Engineering Faculty Research & Creative Works

Many products that directly impact the quality of human life today — gloves, catheters, condoms, and baby bottle teats — are made through the latex-dipping technology. While a variety of methods have been developed – e.g., particle counting, turbidimetry, microscopy, and light scattering – which are suitable for studying the coagulation of latex at very low concentrations, much less work has focused on methods suitable for in-situ characterization of latex coagulation in concentrated solutions (e.g., as relevant to the dipping process). This paper presents a process-relevant rheological protocol for assessing and optimizing latex coagulation dynamics for the thin glove coagulant …

The Use Of Mobile Applications By Non-Governmental Organizations For Volunteer Recruitment And Retention In Egypt, Mona Sami Morshidy

Theses and Dissertations

Abstract 

Non-governmental organizations (NGOs) have increasingly used digital technology and mobile applications to facilitate volunteerism. In Egypt, mobile applications offer significant opportunities to enhance volunteer management. This study explores how mobile applications and digital platforms facilitate volunteering recruitment and retention in Egypt. The study employs a qualitative research design based on 34 semi-structured interviews with NGO representatives and volunteers with varying years of volunteering experience. The findings highlight the mobile application's effects on recruitment, retention, and management, as well as the challenges of adapting it. The results indicate that NGOs primarily use mobile applications to manage existing volunteers, with only …

Disaster Preparedness, Prevention And Management In Lagos State University Library, Mausi A. Bokoh, Sophia V. Adeyeye Dr, Oluwaseun Adeola Abiodun-Asanre, Mrs

Library Philosophy and Practice (e-journal)

Disasters pose significant threats to human lives, infrastructure, and national socioeconomic development. Effective disaster preparedness, prevention, and management are therefore vital for mitigating their impact and ensuring continuity of operations. This study examined disaster preparedness, prevention, and management practices at Lagos State University Library. A survey research design was adopted, and data were collected through a structured questionnaire covering key aspects of disaster management. Frequency counts, percentages, mean, and standard deviations were used to analyze data.  The findings revealed that the library employs basic preventive strategies such as turning off electricity after work hours and ensuring timely evacuation during emergencies. …

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 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 …

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.

Gwtc-4.0: Updating The Gravitational-Wave Transient Catalog With Observations From The First Part Of The Fourth Ligo–Virgo–Kagra 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

Version 4.0 of the Gravitational-Wave Transient Catalog (GWTC-4.0) adds new candidates detected by the LIGO, Virgo, and KAGRA observatories through the first part of the fourth observing run (O4a: 2023 May 24 15:00:00 to 2024 January 16 16:00:00 UTC) and a preceding engineering run. In these new data, we find 128 compact binary coalescence candidates that are identified by at least one of our search algorithms with a probability of astrophysical origin pastro ≥ 0.5 and that are not vetoed during event validation. We also provide detailed source property measurements for 86 of these that have a false-alarm rate …