Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- University of Nebraska - Lincoln (8383)
- Singapore Management University (4506)
- Missouri University of Science and Technology (2969)
- Old Dominion University (2884)
- Utah State University (2662)
-
- TÜBİTAK (2391)
- University of Kentucky (2296)
- Air Force Institute of Technology (1887)
- Portland State University (1642)
- Brigham Young University (1605)
- Louisiana State University (1495)
- City University of New York (CUNY) (1469)
- University of South Florida (1415)
- Purdue University (1351)
- Wright State University (1253)
- Dartmouth College (1190)
- University of Nevada, Las Vegas (1152)
- California Polytechnic State University, San Luis Obispo (1134)
- University of Arkansas, Fayetteville (1124)
- University of Texas Rio Grande Valley (1078)
- Wayne State University (1045)
- University of South Carolina (1004)
- University of Texas at El Paso (979)
- Syracuse University (963)
- University of Central Florida (952)
- Claremont Colleges (936)
- Montana Tech Library (926)
- San Jose State University (918)
- Technological University Dublin (855)
- Embry-Riddle Aeronautical University (854)
- Keyword
-
- Machine learning (1338)
- Machine Learning (695)
- Deep learning (678)
- Artificial intelligence (536)
- Physics (467)
-
- Mathematics (440)
- Chemistry (433)
- Climate change (430)
- Remote sensing (418)
- Computer Science (412)
- Western Australia (387)
- Security (373)
- Classification (371)
- Deep Learning (357)
- Education (316)
- Simulation (315)
- Algorithms (304)
- Statistics (304)
- Artificial Intelligence (290)
- Applied sciences (279)
- Groundwater (274)
- Sustainability (268)
- Computer vision (256)
- Humans (255)
- Cybersecurity (252)
- Neural networks (250)
- Water quality (247)
- Modeling (236)
- Optimization (236)
- Geology (231)
- Publication Year
- Publication
-
- Theses and Dissertations (4667)
- Research Collection School Of Computing and Information Systems (4231)
- Faculty Publications (1870)
- Electronic Theses and Dissertations (1679)
- Nebraska Tractor Tests (1676)
-
- Turkish Journal of Electrical Engineering and Computer Sciences (1233)
- Dissertations (960)
- Masters Theses (945)
- Physics Faculty Publications (918)
- Department of Computer Science Technical Reports (906)
- Physics Faculty Research & Creative Works (864)
- Silver Bow Creek/Butte Area Superfund Site (795)
- USF Tampa Graduate Theses and Dissertations (783)
- Open Access Theses & Dissertations (719)
- School of Natural Resources: Faculty Publications (658)
- All Graduate Theses and Dissertations, Spring 1920 to Summer 2023 (652)
- LSU Doctoral Dissertations (627)
- Dartmouth Scholarship (613)
- Publications (598)
- UNLV Theses, Dissertations, Professional Papers, and Capstones (596)
- LSU Master's Theses (586)
- Master's Projects (569)
- Publications and Research (559)
- Theses (559)
- Dissertations and Theses (552)
- Graduate Theses and Dissertations (552)
- Honors Theses (526)
- Master's Theses (501)
- Journal of Modern Applied Statistical Methods (493)
- Browse all Theses and Dissertations (490)
- Publication Type
Articles 1711 - 1740 of 91558
Full-Text Articles in Entire DC Network
Bias Evaluation Of Healthcare Data With The Use Of Vbqa - A Vaers Inspired Bias Question Answer Dataset, Nolan Dulude, Renu Karthikeyan, Bivin Sadler, Faizan Javed
Bias Evaluation Of Healthcare Data With The Use Of Vbqa - A Vaers Inspired Bias Question Answer Dataset, Nolan Dulude, Renu Karthikeyan, Bivin Sadler, Faizan Javed
SMU Data Science Review
Abstract. Large Language Models (LLMs) are being used increasingly within the healthcare industry to summarize complex clinical information, but their outputs can often reflect biases inherited from their training data. In healthcare, these biases are not just technical flaws, but they can lead to distorted and false information about vaccine safety, compromise patient trust, and lead to potential harmful outcomes. This study investigates bias found in LLM-generated outputs to question-answer pairs inspired by adverse vaccine reactions using COVID-19 data from the Vaccine Adverse Event Reporting System (VAERS) from 2020–2024. We examined whether training the LLMs on a known Bias Benchmark …
Nlp Bias And African American English, Kenya Roy, Faizan Javed
Nlp Bias And African American English, Kenya Roy, Faizan Javed
SMU Data Science Review
African American English (AAE), also referred to as African American Vernacular English (AAVE), is widely used on social media, but most sentiment analysis tools are trained only on Standard American English (SAE). This mismatch can cause models to misclassify dialectal expressions—especially by labeling neutral or positive AAE as negative or toxic. These errors matter, since Natural Language Processing (NLP) systems are now central to content moderation and brand monitoring. This research will evaluate the VADER, RoBERTa, GPT-OSS, and Gemma’s handling of AAE in comparison to SAE using the TwitterAAE corpus, a public dataset of tweets with estimated AAVE usage. The …
Automating Cardiff Model Data Capture In Emergency Departments: Ambient Nlp Integration With Oracle-Cerner Fhir Systems, Simi Augustine, Marco A. Lopez, Jacquelyn Cheun, Chris Papesh
Automating Cardiff Model Data Capture In Emergency Departments: Ambient Nlp Integration With Oracle-Cerner Fhir Systems, Simi Augustine, Marco A. Lopez, Jacquelyn Cheun, Chris Papesh
SMU Data Science Review
Violence and overdose events in Las Vegas occur at rates above the national average, with fewer than half of violent injuries reported to law enforcement [2,7]. The Cardiff Model offers a proven framework for standardized data collection and sharing between hospitals and public safety partners, yet many implementations still rely on manual entry. We propose an ambient triage pipeline integrated with Oracle-Cerner electronic health record systems to listen to nurse–patient dialogue, convert speech to text, extract Cardiff fields, and write standards-based FHIR Bundles for analytics. Using SMART on FHIR standards and Cerner Millennium APIs, the study evaluates whether ambient capture …
Anomaly Detection For Multi-System Bug Triage, Gibran Miguel Zavala Gamero, Hayoung Cheon, Mustafa Iqbal
Anomaly Detection For Multi-System Bug Triage, Gibran Miguel Zavala Gamero, Hayoung Cheon, Mustafa Iqbal
SMU Data Science Review
Large-scale software systems produce vast volumes of logs and telemetry, making manual incident triage slow and error prone. This study presents an unsupervised anomaly detection pipeline that fuses logs, metrics, and traces through late fusion. Using Hybrid Ensemble modeling with Isolation Forest, and Long Short-Term Memory (LSTM) Deep Learning model, the system detects cross-service anomalies producing and assigning a composite triage score reflecting severity and impact. Ranked alerts are categorized into Critical, High, or Medium priorities for review. A retrieval-augmented generation (RAG) layer enriches results with contextual summaries for explainable triage. Evaluated on synthetic multi-service datasets, the pipeline …
A Modular Framework For Cost-Efficient Aspect-Based Sentiment Analysis Using Small Language Models, Senthil Kumar, Nibhrat Lohia
A Modular Framework For Cost-Efficient Aspect-Based Sentiment Analysis Using Small Language Models, Senthil Kumar, Nibhrat Lohia
SMU Data Science Review
Aspect-based sentiment analysis (ABSA) links opinions in text to specific product attributes (for example, battery life, screen quality, or delivery speed) rather than only assigning an overall star rating. This level of detail is important in domains such as e-commerce, where teams need to know which features customers praised and which they criticized. Traditional ABSA pipelines have relied on large language models (LLMs), which achieved high quality but were expensive to run and difficult to scale. This study evaluated whether small language models (SLMs) in the 1–3 billion parameter range could serve as a lower-cost alternative. We implemented a modular …
Application Of Open-Source Small Large Language Models For Finance Report Analysis, Tue Vu, Mark Austin, Marcel Tuijn
Application Of Open-Source Small Large Language Models For Finance Report Analysis, Tue Vu, Mark Austin, Marcel Tuijn
SMU Data Science Review
The rapid integration of generative AI in finance introduces both opportunities and challenges, particularly when analyzing sensitive data such as Securities and Exchange Commission (SEC) filings. This study investigates the use of open-source Small Large Language Models (SLLMs), deployed locally through the Ollama and LangChain frameworks, combined with Retrieval-Augmented Generation (RAG) for extracting financial insights relevant to index performance and reporting quality. Two key objectives guide this work: (1) benchmarking multiple open-source SLLMs for sentiment analysis, multiple-choice reasoning, and financial question answering, and (2) assessing the feasibility of locally deployed SLLMs for domain-specific financial queries. A standardized set of 50 …
Reducing Range Anxiety Through Predictive Modeling Of Ev Battery Degradation, Caleb Thornsbury, Christian Castro, Bivin Sadler
Reducing Range Anxiety Through Predictive Modeling Of Ev Battery Degradation, Caleb Thornsbury, Christian Castro, Bivin Sadler
SMU Data Science Review
Electric Vehicles (EV) range anxiety remains one of the top barriers for broader adoption. Range anxiety can be attributed to battery pack age and degradation over time. This paper plans to explore how to address this issue by creating a machine learning model that can predict degradation based on usage, temperature, battery chemistry, charging habits and exploring whether other factors tie into range degradation. This research will be using real world charging data along with lab tested chemistry data to build a model that can be chemistry specific for degradation. This paper will help perspective used-EV buyers learn about battery …
A General Predictive And Conceptual Model For Repulsive Electronic States In Valence Ionized Molecules, Luka Dockx, Bálint Sztáray, Anthony Dutoi
A General Predictive And Conceptual Model For Repulsive Electronic States In Valence Ionized Molecules, Luka Dockx, Bálint Sztáray, Anthony Dutoi
College of the Pacific Faculty Articles
Valence photoionization generates photoions with excess internal energy, often resulting in statistical dissociation, well described by RRKM theory. Yet, numerous small photoions with electronegative substituents (e.g., F, Cl, Br, OH) have been shown to exhibit nonstatistical behavior, undergoing direct dissociation from repulsive electronic states to yield radicals such as F• or OH•, along with their corresponding fragment ions. Here, we present a general, predictive model that rationalizes this mechanism and extends it to molecules bearing electronegative substituents capable of forming 2P (F•, Cl•, Br•) or 2Π (OH•, SH•, N3•, NCO•) radicals. Nonstatistical dissociation arises from ionization of p- or π-localized …
Predicting Tart Cherry Stem Water Potential Using Uav Multispectral Imagery And Environmental Data Via Symbolic Regression, Anderson L. S. Safre, Alfonso Torres-Rua, Kurt Wedegaertner, Brent Black, Brennan Bean, Burdette Barker, Matt Yost
Predicting Tart Cherry Stem Water Potential Using Uav Multispectral Imagery And Environmental Data Via Symbolic Regression, Anderson L. S. Safre, Alfonso Torres-Rua, Kurt Wedegaertner, Brent Black, Brennan Bean, Burdette Barker, Matt Yost
Civil and Environmental Engineering Faculty Publications
Tart cherry is an important fruit crop in Utah, where irrigation is essential due to arid conditions. Precision irrigation requires reliable indicators of plant water status, and stem water potential (Ψstem), is among the most sensitive though labor-intensive and spatially limited. This study develops Ψstem estimation models using high-resolution multispectral Unmanned Aerial Vehicle (UAV) imagery combined with meteorological and soil moisture data, applying Symbolic Regression (SR). Results show a stronger correlation between optical bands and Ψstem during the pre-harvest period. Among 85 vegetation indices, the Red Chromatic Coordinate (RCC) index performed best (R2 = 0.67). …
Monthly Progress Report Butte Priority Soils Operable Unit Consent Decree Partial Remedial Design/Remedial Action And Operation And Maintenance, Josh Bryson
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Rural–Urban Differences In Cognitive Outcomes Among Older Adults: The Roles Of Falls And Depressive Symptoms, Ayse Malatyali, Tom Cidav, Lisa A.K. Wiese, Jian Zou, Monique J. Brown Ph.D., Mph, Junfeng Ma, Breno S. Diniz, Ladda Thiamwong
Rural–Urban Differences In Cognitive Outcomes Among Older Adults: The Roles Of Falls And Depressive Symptoms, Ayse Malatyali, Tom Cidav, Lisa A.K. Wiese, Jian Zou, Monique J. Brown Ph.D., Mph, Junfeng Ma, Breno S. Diniz, Ladda Thiamwong
Faculty Publications
Background: Older adults with Alzheimer’s Disease and Related Dementias (ADRD) experience a higher risk of falls. However, research lacks evidence on the effect of fall exposure on cognitive impairment and dementia. We investigated the association of falls and depressive symptoms with cognitive impairment and dementia in a nationally representative sample. Methods: We analyzed data from 6221 participants (age ≥ 65) in the Health and Retirement Study (HRS) from the 2018–2020 waves, using Multinomial logistic regression models. Measures included the HRS health status questionnaire, HRS cognition scale, and the Center for Epidemiological Studies Depression scale. Results: Prevalence of fall exposure across …
Human-Ai Collaboration In Marketing Brainstorming: A Meta-Analytic Investigation Of Implementation Approaches And Creative Outcomes, Michael Michaels
Human-Ai Collaboration In Marketing Brainstorming: A Meta-Analytic Investigation Of Implementation Approaches And Creative Outcomes, Michael Michaels
USF Tampa Graduate Theses and Dissertations
Marketing organizations face intensifying pressure to sustain creative output while managing constrained resources and accelerating digital content cycles. The integration of artificial intelligence into marketing brainstorming processes presents a promising response to this challenge; however, prior to this investigation, no comprehensive quantitative synthesis had established the overall effectiveness of human-AI collaboration in marketing creativity contexts or identified optimal implementation strategies.
This dissertation presents a systematic meta-analytic investigation of AI-enhanced brainstorming effectiveness in marketing contexts. Following PRISMA guidelines, 42 independent empirical studies (N = 2,166 participants) published between 2018 and 2025 were identified across four primary academic databases, coded for implementation …
Rural–Urban Differences In Cognitive Outcomes Among Older Adults: The Roles Of Falls And Depressive Symptoms, Ayse Malatyali, Tom Cidav, Lisa A.K. Wiese, Jian Zou, Monique J. Brown Ph.D., Mph, Junfeng Ma, Breno S. Diniz, Ladda Thiamwong
Rural–Urban Differences In Cognitive Outcomes Among Older Adults: The Roles Of Falls And Depressive Symptoms, Ayse Malatyali, Tom Cidav, Lisa A.K. Wiese, Jian Zou, Monique J. Brown Ph.D., Mph, Junfeng Ma, Breno S. Diniz, Ladda Thiamwong
Faculty Publications
Background: Older adults with Alzheimer’s Disease and Related Dementias (ADRD) experience a higher risk of falls. However, research lacks evidence on the effect of fall exposure on cognitive impairment and dementia. We investigated the association of falls and depressive symptoms with cognitive impairment and dementia in a nationally representative sample. Methods: We analyzed data from 6221 participants (age ≥ 65) in the Health and Retirement Study (HRS) from the 2018–2020 waves, using Multinomial logistic regression models. Measures included the HRS health status questionnaire, HRS cognition scale, and the Center for Epidemiological Studies Depression scale. Results: Prevalence of fall exposure across …
Super-Resolution Remote Sensing Datasets For Application To Caral–Supe Archeological Sites Employing Sar And Dems, Jungrack Kim, Ramesh P. Singh
Super-Resolution Remote Sensing Datasets For Application To Caral–Supe Archeological Sites Employing Sar And Dems, Jungrack Kim, Ramesh P. Singh
Mathematics, Physics, and Computer Science Faculty Articles and Research
Publicly accessible spaceborne remote sensing datasets often lack the spatial resolution required to reliably distinguish archeological features from their surrounding geomorphological contexts. In this study, we assess the potential of super-resolution (SR) products derived from multiple public-domain remote sensing datasets for a systematic archeological survey in the Caral–Supe region. We focus on Synthetic Aperture Radar (SAR) and topographic datasets—including Sentinel-1, Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR), and Digital Elevation Models (DEMs)—because of their capacity to detect subtle surface expressions and shallow subsurface structures obscured by vegetation or sediment cover. Using state-of-the-art deep learning algorithms, …
Coordinates, Time, And The Sky, John R. Thorstensen
Coordinates, Time, And The Sky, John R. Thorstensen
Other Faculty Materials
This monograph explains celestial coordinates and their basis in the motion and orientation of the earth. It was written for use in undergraduate classes in basic astronomy and observational techniques.
Fluorescent Biosensor-Guided Engineering Of Enzyme Cascades For Electrochemical Applications, Nathan J. Ricks, Monica Brachi, Fnu Arun, Egor Baiarashov, Shelley D. Minteer, Ming C. Hammond
Fluorescent Biosensor-Guided Engineering Of Enzyme Cascades For Electrochemical Applications, Nathan J. Ricks, Monica Brachi, Fnu Arun, Egor Baiarashov, Shelley D. Minteer, Ming C. Hammond
Chemistry Faculty Research & Creative Works
Substrate channeling is a strategy for enhancing flux and yield in enzymatic cascades and is increasingly relevant for applications in biocatalysis, biotechnology, and bioelectrochemical systems. However, efforts to engineer channeling are limited by the lack of high-throughput methods to evaluate and optimize channeling efficiency. Here, we present a fluorescence-based screening assay to rapidly assess substrate channeling in a model system involving fumarase and malate dehydrogenase, two sequential enzymes from the Krebs cycle. By expressing genetic fusions in Escherichia coli, quantifying intermediate (malate) and product (NADH) formation in lysate using orthogonal fluorescent readouts, and comparing product-to-intermediate ratios, we screened a library …
Main-Chain Ion-Pair Polybenzimidazole Membranes Enabling Reduced-Temperature Ht-Pemfc Operation (Down To 120°C), Huina Lin, Brian C. Benicewicz
Main-Chain Ion-Pair Polybenzimidazole Membranes Enabling Reduced-Temperature Ht-Pemfc Operation (Down To 120°C), Huina Lin, Brian C. Benicewicz
Faculty Publications
Proton exchange membrane (PEM) fuel cells are promising for clean and efficient energy conversion across diverse applications. High-temperature PEM fuel cells (HT-PEMFCs) using phosphoric acid (PA)-doped polybenzimidazole (PBI) can operate up to 200°C, but at lower temperatures, water-induced PA loss often leads to performance degradation and reduced durability. In this work, we present a new class of main-chain ion-pair PBI membranes by integrating the imidazolium-biphosphate ion-pair units directly into the PBI backbone. This design results in membranes with high acid content, stronger acid-polymer interactions and stabilized acid retention. In single-cell tests, the Im+-PBI15-3 wt.% exhibits peak power densities …
Factors For Patient Trust And Acceptance Of Medical Artificial Intelligence, Ana Bracic, Kayte Spector-Bagdady, Sophie Towle, Rina Zhang, Cornelius A. James, Nicholson W. Price Ii
Factors For Patient Trust And Acceptance Of Medical Artificial Intelligence, Ana Bracic, Kayte Spector-Bagdady, Sophie Towle, Rina Zhang, Cornelius A. James, Nicholson W. Price Ii
Articles
Artificial intelligence (AI) is increasingly used in clinical care, but widespread adoption requires patient trust. Trust may be enhanced through systemic governance mechanisms or frontline clinicians providing a human in the loop for AI oversight. However, it is unclear how different approaches specifically influence patient trust in the use of medical AI. The objective is to determine the extent to which patient trust in and choice of medical scenarios involving AI are associated with governance mechanisms, clinician presence, performance, and data quality.
Privacy Preserving Anomaly Detection System For Der Solar Inverters, Tanzim Jim Hassan, Prakash Ranganathan
Privacy Preserving Anomaly Detection System For Der Solar Inverters, Tanzim Jim Hassan, Prakash Ranganathan
Graduate Research Achievement Day Posters
Reliable operation of solar inverters depends on maintaining a stable frequency. Recent cyber attacks on solar DERs are concerning and increase the likelihood of such stealthy attacks leading to anomalies in DER. Therefore, a robust anomaly detection system (ADS) is crucial for solar inverters used in distributed energy resources (DERs), enabling timely detection and correction of frequency anomalies. Additionally, preserving data privacy is essential for the security and reliability of the power grid. This paper proposes a privacy-preserving anomaly detection system (PP-ADS) based on a multi-stage hybrid machine learning (MSHML) model specifically designed for solar inverter data in DER environments. …
Response Of Botovskaya Cave To Local And Regional Environmental Dynamics, Jade Margerum, Oksana Gutareva, Franziska Lechleitner, Maria Box, Stuart Umbo, Anton Vaks, Hanno Meyer, Aleksandr Kononov, Aleksander Osintsev, Dimitri Sokol'nikov, Norbert Marwan, Ola Kwiecien, Sebastian Breitenbach
Response Of Botovskaya Cave To Local And Regional Environmental Dynamics, Jade Margerum, Oksana Gutareva, Franziska Lechleitner, Maria Box, Stuart Umbo, Anton Vaks, Hanno Meyer, Aleksandr Kononov, Aleksander Osintsev, Dimitri Sokol'nikov, Norbert Marwan, Ola Kwiecien, Sebastian Breitenbach
International Journal of Speleology
Speleothems from caves in near-permafrost regions can provide unique insights into the climatic history of temperature-sensitive environments. These regions are often remote and only seasonally accessible, which makes cave monitoring – a requirement for speleothem-based proxy interpretation – challenging. We document ventilation, the infiltration regime, and the isotopic composition of dripwater in Botovskaya Cave in southern Siberia, a host to speleothems previously used to reconstruct Quaternary permafrost dynamics in continental Eurasia. We explore surface and cave temperature records, cave air CO2 concentration data and stable isotopes in precipitation and dripwater and evaluate infiltration conditions and the sensitivity of speleothems …
Sensing Negative-Cone Rotational Diffusion Of Dipole-Like Emitters, Yuanxin Qiu, Kaizhi A. Nie, Matthew D. Lew
Sensing Negative-Cone Rotational Diffusion Of Dipole-Like Emitters, Yuanxin Qiu, Kaizhi A. Nie, Matthew D. Lew
Electrical & Systems Engineering Publications and Presentations
Fluorescence anisotropy and single-molecule orientation-localization microscopy (SMOLM) are powerful techniques that quantify the rotational diffusion of dipole-like emitters, which is important for sensing molecular interactions and chemical environments at the nanoscale. Numerous theoretical and experimental studies have thoroughly characterized single-molecule rotations even when those rotations are much faster than the detector integration time. Here, we extend the theory of measuring rotational diffusion to situations where a single dipole rotates uniformly everywhere outside of an isotropic cone of a certain size, termed a negative cone. This scenario corresponds to negative fluorescence anisotropy 𝑟 and has been observed in emitters exhibiting strong …
Tutoring Prompt For Personalized Self-Study Using Generative Ai, Vasiliy S. Znamenskiy
Tutoring Prompt For Personalized Self-Study Using Generative Ai, Vasiliy S. Znamenskiy
Open Educational Resources
This educational material presents a reusable tutoring prompt for general-purpose generative AI systems (e.g., ChatGPT, Gemini, Claude, Copilot, Perplexity) designed to support personalized self-study. The prompt turns a chatbot into an adaptive self-testing engine: it asks a sequence of multiple-choice questions, waits for the learner’s response, provides brief feedback, and adjusts difficulty based on performance. While the approach can be adapted to many disciplines, the current implementation is tuned to College Physics 2e, Chapter 21 (Circuits and DC Instruments) and uses “formulas only” answer choices to emphasize symbolic reasoning and reduce reliance on verbal cues. Shared in the spirit …
Impediments To Transforming The Healthcare Delivery System: Shifting The Paradigm From Provider Centric To Patient Centric, Elizabeth A. Regan, Manasa Devi Chinta
Impediments To Transforming The Healthcare Delivery System: Shifting The Paradigm From Provider Centric To Patient Centric, Elizabeth A. Regan, Manasa Devi Chinta
Faculty Publications
Introduction:
Stated aims for digital healthcare transformation frequently cite goals for better coordinated patient-centric systems. However, despite advances in medical science, digital technologies, health policies, and billions of dollars invested over the past 25 years, most healthcare providers are far from fully realizing the demonstrated benefits of today's digital technologies for improving patient care. Sharing information across healthcare systems remains challenging. Problems with fragmentation, quality, inequities, and rising costs of care delivery persist. A recent study of 1,026 U.S. hospital systems found that only 15.8 percent achieved a digital maturity level needed to provide digitally enabled healthcare services to better …
Clinical Validation Of Perfusion Imaging With Pulmonary Function Test Data Using Voronoi-Based Discretization, Jorge Cisneros, Caleb J. Herrera, Yi-Kuan Liu, Lisa V. Du, Yevgeniy Vinogradskiy, Richard Castillo, Girish Nair, Edward Castillo
Clinical Validation Of Perfusion Imaging With Pulmonary Function Test Data Using Voronoi-Based Discretization, Jorge Cisneros, Caleb J. Herrera, Yi-Kuan Liu, Lisa V. Du, Yevgeniy Vinogradskiy, Richard Castillo, Girish Nair, Edward Castillo
Department of Medicine Faculty Papers
Objective.Accurate lung function assessment is essential for diagnosing and managing diseases like chronic obstructive pulmonary disorder, pulmonary emboli, and lung cancer. Single-photon emission computed tomography (SPECT) provides valuable 3D functional imaging of ventilation and perfusion, but is limited by low spatial resolution, availability, additional radiation, and cost. Alternative methods, including CT-based perfusion (CT-P) and deep learning models, require large datasets to validate results that are often scarce. Pulmonary function tests (PFTs) offer rapid and noninvasive global lung function measures and are clinically widely used. While ventilation correlates well with PFTs, perfusion imaging presents challenges due to complex blood flow and …
Spectroscopy And Photochemistry Of The Astrochemical Molecules Sicp And Alcp, Vincent J. Esposito, Tarek Trabelsi, Rebecca Firth, Ryan C. Fortenberry, Joseph S. Francisco
Spectroscopy And Photochemistry Of The Astrochemical Molecules Sicp And Alcp, Vincent J. Esposito, Tarek Trabelsi, Rebecca Firth, Ryan C. Fortenberry, Joseph S. Francisco
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Through characterization of the electronic excited-state topology, linear-SiCP is predicted to be photostable in the UV region, whereas linear-AlCP is predicted to undergo photodissociation to form Al+CP products after absorption of light in the 200–250 nm range, representing a catalytic process for freeing aluminum molecules from a solid dust grain. Both SiCP and AlCP are predicted to have electronic transitions with large absorption cross sections (∼10–17 cm2) and to undergo fluorescence from bound excited states. The total electronic absorption spectrum is provided to inform electronic spectroscopy experiments. Silicon (SiC) and aluminum (Al2O3) dust …
Co-Electrospinning Polyacrylonitrile (Pan) / Polymer Of Intrinsic Microporosity-1 (Pim-1) For Electrochemical-Based Sensor For Pyridine Detection And Absorption, Samar A. Salim
Nanotechnology Research Centre
The electrospinning of the polymer of intrinsic microporosity-1 (PIM-1) poses challenges due to its limited solubility and tendency to form bead-like structures at high concentrations. This work details the synthesis and analysis of electrospun composite fibers made from polyacrylonitrile (PAN) and PIM-1 for electrochemical applications. The data analysis confirmed the successful incorporation of PIM-1 into the PAN matrix. The fiber characteristics were significantly influenced by PIM-1 loading (1–10%), resulting in fiber diameters ranging from 0.8 to 1.7 μm. A 10% concentration of PIM-1 results in the formation of macropores with diameters ranging from 0.5 to 1.7 μm. Optical analysis using …
The Modern History Of The Basel Problem, John Campbell, Paul Levrie
The Modern History Of The Basel Problem, John Campbell, Paul Levrie
Euleriana
The \emph{Basel problem} refers to the problem of determining a closed form for the infinite series $\frac{1}{1^2} + \frac{1}{2^2} + \cdots$. If we consider what mathematical results have the most peer-reviewed papers devoted to new ways of proving such results, Euler's formula $\frac{1}{1^2} + \frac{1}{2^2} + \cdots = \frac{\pi^2}{6}$ is certainly among the top of such results. This motivates our historical study of peer-reviewed papers based on proofs of Euler's formula, and we introduce what appears to be the most comprehensive and up-to-date and exhaustive catalogue of peer-reviewed, published papers in the 20th and 21st centuries devoted to or mainly …
Euler And Gauss On The Hypergeometric Function -- A Comparison, Alexander Aycock
Euler And Gauss On The Hypergeometric Function -- A Comparison, Alexander Aycock
Euleriana
We present several results stated by Euler on what is today called the Gaussian hypergeometric function. For this purpose, we compare the results found by Gauss to Euler's results.
The Extent To Which The Earth's Motion Is Perturbed By The Moon, More Accurately Investigated: An English Translation Of E139, Patrick T. Headley
The Extent To Which The Earth's Motion Is Perturbed By The Moon, More Accurately Investigated: An English Translation Of E139, Patrick T. Headley
Euleriana
In Tabulae astronomicae solis et lunae (Solar and lunar astronomical tables) (E87), published in 1746, Euler made a first attempt to correct his astronomical tables for the gravitational attraction of the Earth toward the Moon, simply by accounting for the difference between the position of the Earth and the center of gravity of the Earth-Moon system. In this article Euler revisited the problem, noting that this center of gravity would not itself take an elliptical path around the Sun. To model the motion more accurately, Euler considered the separate gravitational attractions of the Sun and Moon acting on the Earth. …
About Infinite Algebraic Curves Whose Indefinite Lengths Equal An Elliptic Arc: An English Translation Of E780, Derek R. Aoki
About Infinite Algebraic Curves Whose Indefinite Lengths Equal An Elliptic Arc: An English Translation Of E780, Derek R. Aoki
Euleriana
Euler continues his study of algebraic curves with equal arc length, a subject to which he returned several times. After a brief review, he introduces an infinite family of curves with the same indefinite length as a given ellipse. However, this first family is by his own admission poorly motivated, so he derives directly a different but related family of curves with the same indefinite length as a given ellipse.