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Enhancing Emotional Support For Advanced Placement Students, Laine Mckay Nesbitt

Theses and Dissertations

Although they may struggle with their emotional well-being, academically accelerated students are underrepresented in the research literature. Teachers are in a position to influence students' emotional well-being. Minimal qualitative research with student voices has been conducted. This study highlights the perspectives of students who have participated in an academically accelerated program. Students were interviewed about what their teachers do to help or hinder their emotional well-being and what they wish that teachers could do to support their emotional well-being. A total of 14 high school students were interviewed using the critical incident technique (CIT). The participants emphasized the importance of …

Practical Implementation Of Ethnomathematics To Increase The Engagement, Math Self-Efficacy, And Hawaiian Cultural Identity Of HawaiʻI Algebra 2 Students, Kamalani George Mamatuki Kaluhiokalani

Theses and Dissertations

The underrepresentation of Hawaiian cultural practices in mathematics education has contributed to a disconnect between students' cultural identities and their academic experiences, resulting in diminished engagement among Native Hawaiian learners. This design-based research examines the integration of ethnomathematics into high school mathematics curricula, with a focus on Hawaiian cultural practices as frameworks for teaching mathematical concepts. Participants include approximately 100 students in Hawaiʻi from a public school and a private school, as well as two mathematics teachers with varying degrees of experience in culturally responsive pedagogy and ethnomathematics. Employing a mixed-methods approach, the study collects data through classroom observations, teacher …

Beyond The Bell Curve: Understanding Native American Academic Placements, Sarah-Margaret Clark

Theses and Dissertations

This study examined biases regarding the referrals that teachers make regarding student placement recommendations for Native American students. Special education teachers (n = 97) from around the United States completed a digital card sort task involving 24 fictitious student record cards. The student record cards contained subtle information about the ethnicity of the student, as indicated through the use of racial identification (Native American, Asian, or White) on the student records and the use of student names that may be associated with these three categories. Academic information was equal among each of these three groups. Each group contained identical male …

Calibration And Validation Of An Ogden Material Model For Thermoplastic Polyurethane In 3d-Printed Tensegrity Structures, Caleb C. Swain

Theses and Dissertations

This work is motivated by ongoing efforts within the Smart Materials, Adaptronics, and Shock Laboratory (SMASH Lab) at Brigham Young University (BYU) to develop variable-stiffness, external fixators using 3D-printed tensegrity structures. In the process of designing and evaluating these systems, the need arose to accurately model the nonlinear mechanical behavior of thermoplastic polyurethane (TPU), the primary material used in prototype fabrication. This thesis investigates how accurately a calibrated Ogden material model can predict the nonlinear mechanical response of TPU in 3D-printed tensegrity structures. Experimental data were used to calibrate the parameters of the hyperelastic constitutive model through nonlinear optimization. An …

Integration Of Intraoperative Data In Interpretable Machine Learning Models To Predict Postoperative Aki In Noncardiac Surgery Patients, Justin Do, Karan H. Shah, Melissa Xu, Andrew Hyunwoo Kim, Vivaswat Suresh, Nidhir Guggilla, Michael Li, Rishi Kothari

Department of Anesthesiology Faculty Papers

OBJECTIVES: We aimed to (1) quantify changes in discrimination when adding intraoperative data to preoperative data and (2) compare tabular machine learning with feature engineering against a time-aware LSTM-based model.

MATERIALS AND METHODS: Retrospective cohort of 46 204 adults undergoing 57 055 eligible noncardiac surgery in the INSPIRE database. We extracted 38 preoperative and 49 intraoperative variables; acute kidney injury (AKI) was defined by KDIGO serum creatinine criteria and modeled as stage 2/3 postoperative AKI. Models were trained on preoperative-only and combined pre- and intraoperative data. Intraoperative series were summarized using eight statistical features for tabular models or integrated directly …

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 …

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 …

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 …

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.

Gw230814: Investigation Of A Loud Gravitational-Wave Signal Observed With A Single Detector, 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

GW230814, detected by the LIGO Livingston observatory with a signal-to-noise ratio of 42.4, represents the loudest gravitational-wave signal in the GWTC-4.0 catalog. Its source is consistent with a binary black hole coalescence with component masses m1=33.7+2.9−2.2M⊙, m2=29.9+2.1−2.8M⊙, and a small effective inspiral spin χeff=−0.01+0.06−0.07. The high signal-to-noise ratio enabled us to detect an ℓ = ∣m∣ = 4 mode in the inspiral–merger–ringdown signal for the first time (with Bayes factor ≈10), as well as enabling a range of tests of consistency between theoretical predictions and the observed waveform. While most of these tests show agreement with theoretical predictions, there are …

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 …

Searches For Continuous Gravitational Waves From Supernova Remnants In The First Part Of The Ligo-Virgo-Kagra 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

We present results from directed searches for continuous gravitational waves from a sample of 15 nearby supernova remnants, likely hosting young neutron star candidates, using data from the first eight months of the fourth observing run (O4) of the LIGO–Virgo–KAGRA Collaboration. The analysis employs five pipelines: four semicoherent methods—the Band-Sampled-Data directed pipeline, Weave, and two Viterbi pipelines (single- and dual-harmonic)—and PyStoch, a cross-correlation-based pipeline. These searches cover wide frequency bands and do not assume prior knowledge of the targets’ ephemerides. No evidence of a signal is found from any of the 15 sources. We set 95% confidence-level upper limits on …

Investigations On The Effect Of Nano Titanium Oxide On The Properties Of Nickel Alloy Using Powder Metallurgy Technique, Sawsan F. Ahmed, Muaamar A .Kamil

Al-Bahir

Powder metallurgy method was used to prepare nickel-based samples enriched with nano-chromium at a fixed ratio of 5 %wt. Different percentages of nano-titanium oxide were added at (0, 5, 10, 15, 20) %wt. . A 10 mm diameter die was used and the pressing process was carried out with a hydraulic press in one direction at a pressure of 10 tons. The resulting alloys were sintered at 1000°C for two hours. Several tests were performed, including X-ray diffraction of the primary and post-mixed powders, which showed that the nickel was in the FCC (Cubic) system and completely pure, the nano-chromium …

Engineering And Geochemical Assessment Of Grey Clay From Iko Town, South-South Nigeria, For Building Construction Applications, Ubong Williams Robert, Sunday Edet Etuk, Okechukwu Ebuka Agbasi, Grace Peter Umoren

Al-Bahir

Grey clay is abundantly available in Iko Town in South-South Nigeria. However, there is no scientific information on its potentialities. Hence, this research has been designed to determine its suitability for building purpose, considering how necessary shelter is for the survival of man. The flowability, gradation, and geochemistry of the clay were assessed. Also, samples were prepared from the clay under same conditions, dried sufficiently, and then subjected to various tests to examine their heat transfer and strength behaviors. For each test category, ten samples were prepared and used and the data obtained were averaged per test. It was found …

Analysis On Thermo-Viscous Steady Fluid Motion Over An Impermeable Infinitely Stretched Horizontal Moving Rectangular Surface, P. Krishna, N. Pothanna, K. Spandana

Mansoura Engineering Journal

This study presents analysis on thermo-viscous steady fluid motion over an impermeable infinitely stretched horizontal moving rectangular surface. The numerical results have been found employing R-K method of order 6 shooting techniques developed in Mathematica software ND solve for the flow adaptable equations comprising temperature and velocity. The flow behavior and the impacts of material constraints on the flow region have been analyzed and deliberated taking the help from the generated graphs. The variations of these flow fields have been studied for wide spectrum of physical characteristics which influences the nature of thermo-viscous fluid. The impact of viscosity, constant pressure …

Factors Influencing Tourist Interest In Walking Tours In The Kota Tua Area, Novi Handayani, Adrian Hartanto

Journal of Indonesian Tourism and Policy Studies

This study aims to analyze the extent to which the variables of Attraction, Accessibility, Cost and Tarif, Facilities, and Information contribute to Walking tour Interest, both individually (partially) and collectively (simultaneously).  As previous research states that Indonesia has one of the lowest levels of mobility. The average Indonesian walks only 3513 steps per day, while the recommended daily step count for maintaining good health is 5000. This study uses Multiple Linear Regression Analysis as its analysis method using partial hypothesis testing (t-test) and simultaneous hypothesis testing (f-test).. Data were collected through an online questionnaire distributed via Google Form to …

A Conceptual Model Of The External Costs Of Truck Overloading On Road Damage, Emissions, And Traffic Congestion: A Systematic Literature Review, Aleksius Sitepu, Sutanto Soehodho, Andyka Kusuma

Smart City

Freight transport services cannot be separated from the infrastructure and facilities involved, each of which faces its own challenges in delivering optimal performance in the logistics sector. A common challenge in Indonesia’s road sector is the presence of overloaded freight vehicles, which has become a national issue. This phenomenon has a negative impact not only on road infrastructure but also on the environment and traffic. This study aims to develop a conceptual model of the external costs caused by truck overloading practices in terms of road infrastructure damage, increased exhaust emissions, and traffic congestion through a systematic literature review. This …

Leveraging A Centralized Fleet Assignment Management For An Aviation Resilience, Inof Seno Acton Mr., Sutanto Soehodho, Nahry Yusuf

Smart City

Since deregulation in the aviation industry, competition among airlines has intensified. This competition is shown by the increasing number of routes, service times, aircraft, and airports served. This competition causes not all flight services to meet their targets, resulting in aircraft operating less efficiently. Passenger seats are not filled, and flight delays are becoming more frequent. Obviously, this will negatively impact consumers and the airline's finances. The study focused on assigning the fleet used to serve flights to maintain existing aviation services and improve aircraft operational efficiency. This study aims to maximize profits by optimizing fleet assignments through the Centralized …