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Interfacial Chemistry Involved In Selective Separation Of Nmc/Lmo And Lco/Lmo Binary Cathode Materials By Froth Flotation Using Oleic Acid, Richard Kofi Oboh, Kaiwu Huang, Seoung Bum Son, Lei Pan

Michigan Tech Publications

The variability in cathode compositions within recycled lithium-ion battery (LIB) feedstocks poses a significant challenge to efficient downstream refining processes. This study demonstrates the feasibility of using froth flotation with oleic acid as a collector to selectively separate lithium nickel-manganese-cobalt oxide (NMC) and lithium cobalt oxide (LCO) from lithium manganese oxide (LMO) materials. Laboratory-scale flotation tests achieved an 80% separation efficiency in a single stage, producing a froth product with >90% purity of NMC/LCO at approximately 90% yield. Concurrently, the LMO materials were enriched in the sink product with ∼90% purity and ∼90% yield. This approach was further validated using …

Quality Of Life In Patients With P16+ Oropharyngeal Cancer Receiving Accelerated Radiation Therapy With Either Cisplatin Or Cetuximab In The Nrg/Rtog 1016 Randomized Controlled Trial, Jimmy J Caudell, David J Adelstein, Paul M Harari, Erich M Sturgis, Ethan Basch, Shlomo A Koyfman, Greg A Krempl, Dukagjin M Blakaj, James Edward Bates, Thomas J Galloway, Christopher U Jones, Beth M Beadle, Jonathan Harris, Quynh-Thu Le, Sue S Yom, Benjamin Movsas

Faculty, Staff and Students Publications

Purpose: NRG/RTOG 1016 was a phase III randomized noninferiority de-escalation trial comparing cetuximab versus cisplatin, concurrent with accelerated radiation 70 Gy/6 weeks, in p16+ oropharyngeal cancer. Quality of life (QOL) was a secondary endpoint.

Methods and materials: Eligible/consenting patients among the first 400 entered completed the EORTC QLQ-C30/H&N35 at baseline, end of treatment, 3, 6, and 12 months posttreatment, to provide 90% power to detect an effect size of 0.5 in the between-arm change in QOL scores from baseline to 6 months. We report completion, responsiveness, and patterns over time across domains between arms, considering a difference of >10 points …

Combined Dark Matter Search Towards Dwarf Spheroidal Galaxies With Fermi-Lat, Hawc, H.E.S.S., Magic, And Veritas, S. Abdollahi, L. Baldini, R. Bellazzini, B. Berenji, E. Bissaldi, R. Bonino, X. Wang, R. Turner, P. Hüntemeyer, Et Al.

Michigan Tech Publications

Dwarf spheroidal galaxies (dSphs) are excellent targets for indirect dark matter (DM) searches using gamma-ray telescopes because they are thought to have high DM content and a low astrophysical background. The sensitivity of these searches is improved by combining the observations of dSphs made by different gamma-ray telescopes. We present the results of a combined search by the most sensitive currently operating gamma-ray telescopes, namely: the satellite-borne Fermi-LAT telescope; the ground-based imaging atmospheric Cherenkov telescope arrays H.E.S.S., MAGIC, and VERITAS; and the HAWC water Cherenkov detector. Individual datasets were analyzed using a common statistical approach. Results were subsequently combined via …

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Interlibrary Loan: From Basics To Current Issues, Jennifer K. Lloyd

Library Faculty Publications

While interlibrary loan has been a core service for health science libraries for decades, changes in policies, software, and workflow are accelerating. This webinar will explain some basics of ILL and its platforms while also focusing on current issues and changes that are confronting libraries.

Everyone Works On The Sustainability Team: Power Structures And Brand Communication In Sustainable Consumption, Sofia Johansson

USF Tampa Graduate Theses and Dissertations

In response to growing concerns about the way in which consumption practices negatively degrade the environment and contribute to climate change, this thesis explores the role in which brands may counteract this. There are two significant issues pertaining to environmental marketing: (1) current efforts to promote green consumerism, through which consumer brands market products as “eco-friendly” with only marginal reductions in climate impact and misleading labels, are insufficient in mitigating climate change. (2) Additionally, this kind of consumption is unjust, whereby it is marked up in price, limiting access to merely individuals in higher income brackets. Given the insufficiencies of …

A Unified Non-Visual Explainable Ai Framework For Neonatal Pain Assessment, Md Imran Hossain

USF Tampa Graduate Theses and Dissertations

With the power of parallel processing, large datasets, and fast computational resources,deep neural networks (DNNs) have outperformed highly trained and experienced human experts in medical applications. However, the large global community of healthcare professionals, many of whom routinely face potentially life-or-death outcomes with complex medicolegal consequences, have yet to embrace this powerful technology. The major problem is that most current AI solutions function as a metaphorical black-box positioned between input data and output decisions without a rigorous explanation for their internal processes. With the goal of enhancing trust and improving acceptance of artificial intelligence– (AI) based technology in clinical medicine, …

Impact Of Statin Medication Use On Glycemic Control And Complications In Type 1 Diabetes, Ryan Bailey

USF Tampa Graduate Theses and Dissertations

Introduction: Hydroxymethylglutaryl-CoA enzyme inhibitors (statins) are frequently used to prevent cardiovascular events in individuals at high risk for cardiovascular diseases, including individuals with diabetes. Prior research has indicated that statins may increase the risk of developing type 2 diabetes (T2D) and may increase hyperglycemia among those previously diagnosed with T2D. To date, little research has investigated the impact of statins on glycemic control and diabetic complications associated with poor glycemic control in those with type 1 diabetes (T1D). The objective of this dissertation is to investigate the association between statin use and measures of glycemic control including hemoglobin A1c (HbA1c), …

Examining Whether Survivors Of Domestic Violence Perceive Ifps As More Helpful Than Other Available Support Resources, Aleidys Lopez Romero

USF Tampa Graduate Theses and Dissertations

Injunctions for protection (also known as restraining orders or civil protection orders) are often used by survivors as a line of defense against continued instances of physical violence or stalking by abusers (Houseman et al., 2024). This study aims to fill these gaps by examining whether survivors of domestic violence perceive IFPs as more helpful than other available support resources. Understanding this process may offer important insights into IFP accessibility, survivor perspectives, and/or alternative resources that may be equally, if not more, helpful to survivors than IFPs. Grounded in Gondolf & Fisher’s (1988) Survivor Hypothesis and Kimberlé Crenshaw’s (1989) Structural …

Warm-Ups To Works Of Art: How Engaging Choral Students In Fundamentals Of Music Leads To The Creative Outlet Of Songwriting", Clay E. Bradford

SPARK Symposium Presentations

When students typically participate in public school choir, they may learn songs from varying different cultures, genres, and styles spanning from different periods of music and countries. This music is incredibly important for the foundation of student learning; however, students are often consumers rather than generators of music. By then taking the basic music theory students may have, and applying it to songwriting parameters and practices, students are able to compose their own music! This not only teaches students to experiment with songwriting but encourages this creative outlet of composition - something they haven't previously encountered before in choir or …

Rates And Predictors Of Intention To Get Preventive Screenings Among Individuals In Recovery From Substance Use Disorders, Afsha Hossain, Ban A. Majeed, Lia Pierson Bruner

Journal of the Georgia Public Health Association

Background: Individuals with substance use disorders (SUDs) are at greater risk for chronic disease but often face barriers to access and uptake of preventive screenings, so the aim of this study was to identify rates and predictors for intention to get preventive screenings among residents at two recovery centers.

Methods: We used a cross-sectional survey (N=95, response rate 51%) to determine previous screening rates and the intention to get recommended preventive screenings among residents of two long-term recovery programs in Athens, GA, using bivariate analysis with chi-square to look for associations with intention.

Results: Prior use of preventive health services …

Rural Georgia Hospital Covid-19 Virus Patient Outcomes, Susan P. Smith, Neeraj Dayama, Morgan E. House, Debra Flores, Sharon Hunt, April Dukes, Steven Gautney

Journal of the Georgia Public Health Association

Background: The Coronavirus disease 2019 (COVID-19) has led to over 1.2 million deaths in the United States. Given the staggering scale of the pandemic, rural hospitals faced heightened challenges due to limited resource availability and underlying patient characteristics.

Methods: In this context, we examined patient and hospital-related factors associated with inpatient mortality due to COVID-19. This study is a retrospective chart review of patient outcomes of patients who were hospitalized in a Southwest Georgia rural hospital with COVID-19 during the initial onset of the outbreak and over the following 23 months of the pandemic. Patient demographics, other characteristics, …

Norm-Variation Of Triple Ergodic Averages For Commuting Transformations, Polona Durcik, Lenka Slavíková, Christoph Thiele

Mathematics, Physics, and Computer Science Faculty Articles and Research

We prove an r-variation estimate, r>4, in the norm for ergodic averages with respect to three commuting transformations. It is not known whether such estimates hold for all r≥2 as in the analogous cases for one or two commuting transformations, or whether such estimates hold for any r< ∞ for more than three commuting transformations.

2026-03-11 From Despair To Collective Action, Karli Calo

The Spectator Online

No abstract provided.

2026-03-11 Changemaker Ken Butigan Presents ‘The Nonviolent Shift Is Coming (If We Want It)’, Kean Mathis

The Spectator Online

No abstract provided.

Molecular Quantum Particle Algorithm (Mqpa): Hybrid Quantum-Classical Learning For Molecular Property Prediction, Jessica Mcphaul, Bivin Sadler Ph.D.

SMU Data Science Review

Classical machine learning models and quantum kernel methods often struggle to capture quantum-coherent molecular features under the constraints of noisy intermediate-scale quantum (NISQ) hardware, limiting both predictive accuracy and scalability.

This paper introduces the Molecular Quantum Particle Algorithm (MQPA), a hybrid quantum–classical framework designed to achieve chemically accurate property prediction by integrating handcrafted molecular descriptors with parameterized quantum circuits. Molecular inputs, expressed as SMILES strings, are processed via RDKit and encoded through angle-based quantum gates with entangling layers in Qiskit [1]. Quantum parameters are optimized using simultaneous perturbation stochastic approximation (SPSA) [2], while classical regression layers leverage Adam [3] …

Predicting House Prices Using Machine Learning, Pejal Rath, Robert Slater

SMU Data Science Review

This study explores the use of Machine Learning methods to predict housing prices, a problem of significant interest in real estate economics, and data science. Traditional hedonic pricing models have long been used to evaluate the impact of housing attributes on property values, but they often lack the flexibility to capture nonlinear relationships and complex feature interactions. Recent advancements in regression based and Machine Learning approaches provide promising alternatives that may improve prediction of accuracy and market insights. This research will investigate how models such as linear regression, random forest, and gradient boosting can be applied to publicly available housing …

Ai-Powered Reporting For Improved Hospital Efficiency, Joel C. Laskow, Chris Papesh, Srishti Awasthi, Jacquelyn Cheun

SMU Data Science Review

This study explores the feasibility of an AI-powered chatbot for HIPAA-aligned intake of emergency room patients seeking treatment for overdose and violence. The system utilizes AWS Amplify, an encrypted EC2 instance, and a secure S3 Bucket house on Amazon Web Services. Chat functionality is powered by a multi-agentic framework operating on Anthropic’s Claude Sonnet 4. Manual evaluation and exact match testing reveal the system reliably obtains and records relevant information during intake. Future work will focus on expanding accessibility by integrating voice functionality, obtaining HIPAA compliance certifications, and incorporating the chat system into existing healthcare networks.

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

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

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 …

Virtual Ai Lifestyle Assistant, Solomon T. Mathew, Babu T. Mathew

SMU Data Science Review

Patients struggle with adhering to prescribed medication and leading a healthy lifestyle outside of clinical visits. A mechanism needs to be developed and deployed to constantly remind them about the need to take medication and to lead a healthy lifestyle in a non-intrusive way while watching for changes in vitals that can be collected using wearable devices. With these considerations, a Virtual Healthcare Assistant is proposed, built with a multi-agent system that is easily integrated with wearable devices such as Apple Watches, Fitbits, and Oura Rings. a LangGraph-based multi-agent workflow to mimic real-world continuous monitoring. The resulting system enables agent-to-agent …

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

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 …

Availability Model To Evaluate Ai Data Centers’ Role In Grid Stability, Troy Mcsimov, Trevor S. Kunz, Jeffrey Billo

SMU Data Science Review

The United States has made it clear; it is imperative that the US wins the global AI race. This paper focuses on one of the most challenging puzzle pieces surfaced at the POWER Data Center conference (San Antonio, Sept. 30.); for Electric Reliability Council of Texas (ERCOT) the limiting factor is not generation alone but the need to balance generation and load to preserve grid reliability.

The regulatory landscape fundamentally changed with the passage of Texas Senate Bill 6 in June 2025, which mandates new large loads must "contribute to the recovery of the interconnecting electric utility’s costs" (Texas Legislature, …

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

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 …

Echocardiographic Finding In Chronic Kidney Disease Patients On Hemodialysis In Al-Diwaniyah Teaching Hospital, Meld Qasim Kamal, Aqeel Raheem Al-Braqawee

Al-Qadisiyah Medical Journal

 Background: Chronic kidney disease is irreversible deterioration of renal function which results into impairment of excretory, metabolic and endocrine functions leading to development of the clinical syndrome of uremia. Patients with Chronic kidney disease are at significantly increased risk for both morbidity and mortality from cardiovascular disease. Patients on dialysis have a 10- to 30-fold increased risk for cardiovascular mortality compared with the general population. Cardiovascular disease is the single most important cause of death among patients receiving long-term dialysis; accounting for 44% of overall mortality. The magnitude of the problem has become more apparent as patients now survive longer …

The Role Of Hoxa-9 In Prediction Of Positive Pregnancy Outcome Women Undergoing Intracytoplasmic Sperm Injection, Zahraa H. Mohan, Ahmed Harbi Al-Azawi, Nadia M. Al-Hilli, Ali Ibrahim Rahim, Adnan Hamza Albdairi

Al-Qadisiyah Medical Journal

Background: Febrile convulsions are prevalent in children aged between 6 months and 5years, with an incidence of 2-5%. On the other hand, iron deficiency  is the most common hematologic disease of infancy and childhood with a periodof incidence that coincides with the time of developing febrile convulsions. Aim of study :To evaluate  any  association between iron deficiency& febrile seizures. Materials &Methods: Tow groups (n=60 in each) of 6-month to 5-year old febrile children, who were admitted to AL-Zahraa teaching  Hospital in AL-Najaf AL-Ashraf city between  1st of February 2011 to  31th of  December 2011. The first group, or the (FS …

Evaluation Of Serum Levels Interferon Gamma , Interleukin 10 And The Ratio Between Them In Patients With Vitiligo : Association Of Interferon Gamma : Interleukin 10 Cytokine Ratio In Vitiligo Patients, Husam Awad, Israa A. Dheeb

Al-Qadisiyah Medical Journal

AbstractBackground and Objective : In the process of depigmenting vitiligo, cytokines, which control immune response and inflammation, are essential. In this investigation, serum levels of interferon gamma (IFN-?) and interleukin 10 (IL-10) and their the ratio were compared in healthy people and those with vitiligo in Iraqi.Materials and method : In order to conduct the study, samples from 60 patients were collected, while samples from 60 healthy participants (the control group) were pooled and measured using sandwich ELISA. Data on the patient's gender, family history, disease state, stress exposure, and males smoking habits are collected as part of the study.Results …