Digital Commons Network^™

Healthcare Professionals’ Experiences And Perspectives On Self-Management Education For Breast Cancer Survivors In Australian Primary Care: A Qualitative Study, Meng Yuan Li, Tao Wang, Daniel Terry, Haiying Wang, Isabella Zhao, Jing Yu Tan

Research outputs 2022 to 2026

Purpose: Breast cancer has been recognised as a chronic condition, with survivors experiencing long-term physical and psychosocial effects following treatment. Supporting breast cancer survivors to self-manage their health can optimise health-related quality of life and reduce symptom burden. Self-management education (SME) has been advocated at the policy and programme level in Australian primary care, but its uptake is often limited. This study explores healthcare professionals’ (HCPs) experiences and perceptions of SME in primary care, aiming to identify factors influencing its implementation and to support survivorship care for breast cancer survivors in Australia.

Methods: A qualitative descriptive approach was adopted involving …

The Moderating Effect Of Dietary Fiber And Protein On The Relationship Between Symptoms Of Depression And Anxiety And Cognitive Decline, Samantha L. Gardener, Hilal Salim Said Al Shamsi, Stephanie R. Rainey-Smith, Hamid R. Sohrabi, Kevin Taddei, Colin L. Masters, Ralph N. Martins, W. M.A.D. Binosha Fernando

Research outputs 2022 to 2026

Introduction: Depression and anxiety often co-occur with Alzheimer's disease, exacerbating the associated cognitive impairment. This study examined moderating effects of dietary protein and fiber intake on relationships between depressive and anxiety symptoms, and cognitive decline.

Methods: Cognitively unimpaired (n = 553; 39.4% male, 70.6 ± 9.6 years) provided baseline fiber and protein intake, and had repeated cognitive testing and symptoms of depression/anxiety measured (baseline and up to eight follow-ups over 144 months). Moderation and simple slope analyses were employed in the cohort as a whole and following stratification by sex.

Results: Fiber intake moderated the relationship between change in depressive …

A Scalable Workflow Using Digital Cognitive Assessment And Ptau217 For Mci Detection, Srinivasan Vairavan, Nicholas Griffin, David Wilson, Gallen Triana-Baltzer, Victoria Brugada-Ramentol, Elena Vera-Campuzano, Daniel Alcolea, Silvia Fallone, Lucy Mackintosh, Lindsey Mette, James D. Doecke, Joanne Robertson, Larry Ward, Gonzalo Sánchez Benavides, Carolina Minguillon, Clàudia Porta Mas, Adrià Tort-Merino, Mircea Balasa, Oriol Grau Rivera, Marc Suárez Calvet, Lewis Taylor, Íñigo Rodríguez-Baz, Javier Arranz, Juan Fortea, Ioannis Tarnanas, Marc Jones, Gayle Wittenberg, Emmanuel Streel, Maria Florencia Iulita

Research outputs 2022 to 2026

Introduction: Blood biomarkers like phosphorylated tau (p-tau)217 offer high diagnostic accuracy for Alzheimer's disease (AD) but face implementation challenges in low-prevalence settings. We evaluated the Altoida NeuroMarker Platform as a digital cognitive triage tool before plasma p-tau217 testing.

Methods: XGBoost models were trained to predict mild cognitive impairment (MCI) and p-tau217 status in 688 individuals across Australia, Spain, and the United States using the Altoida NeuroMarker. p-tau217 status was dichotomized using a threshold of 0.04 pg/mL (LucentAD). We modeled a two-step workflow (Altoida, plasma p-tau217) to enrich downstream biomarker testing, assuming 30% prevalence of AD pathology.

Results: The Altoida NeuroMarker …

Legal Infrastructure For Foreign Founders Entering The U.S. Market, Leonardo Lupiano

Student Scholarship

Foreign entrepreneurs contribute substantially to business formation, innovation, investment, and employment in the United States. Although foreign individuals generally may form and own U.S. companies, entering the U.S. market requires more than selecting a state and filing organizational documents. Foreign founders must navigate overlapping rules governing entity formation, cross-border ownership, corporate governance, taxation, information reporting, securities regulation, beneficial ownership, and immigration.

This paper examines the legal infrastructure available to foreign founders seeking to establish, finance, or operate a business connected to the United States. It first explains why founders are attracted to the United States, including access to capital, customers, …

Webinar 2 Systemic Coherence For Content-Based Eld, Slide Deck 7.28.26, Center On English Language Proficiency

Webinars

No abstract provided.

20260701: School Of Medicine Yearbooks, 1982-1984, School Of Medicine

Guides to University Archives

These items include materials from the MUSOM from 1982-1984. Items were received in 2026. This collection includes three years of yearbooks created by the school of medicine that were donated by Dr. Evelyn Rector Banks. Please download the finding aid for a list of contents.

Dc/Dc Converter For A Solar Module, Stella Uribe, Richie Zaragoza, Olivia Grace Tran, Phillip Tyler Rich

Electrical Engineering

This project focuses on the design and validation of a general-purpose DC/DC power converter intended for use with photovoltaic (PV) solar modules operating under variable environmental and loading conditions. Solar panels exhibit significant variation in output voltage, current, and available power due to changes in irradiance, temperature, and operating point, making direct connection to downstream loads impractical. The proposed system addresses this challenge by providing a single, user-adjustable regulated DC output capable of both stepping up and stepping down the solar module voltage. The converter is designed to interface with solar modules rated between 50 W and 400 W, with …

Sunshine Pump: A Trailer-Mounted Solar Powered Water Pump System, Dylan Quan Dinh, Duncan Campbell

Electrical Engineering

The Sunshine Pump is a trailer-mounted, off-grid solar powered water pumping system that delivers approximately 1,000 gallons of water per day from a well of approximately 250 feet total dynamic head to an above-ground storage tank on a rural ranch in Los Osos, California. The system captures solar energy with a 1,500 watt photovoltaic array consisting of four 375 watt panels wired in series, regulates that energy through a maximum power point tracking stage integrated into an all-in-one inverter/charger, stores it in a 4,800 watt-hour LiFePO4 battery, and converts it to 230 volt AC power to drive a 0.75 horsepower …

Scattered Hypothesis Generation For Open-Ended Event Forecasting, He Chang, Zhulin Tao, Lifang Yang, Xianglin Huang, Yunshan Ma

Research Collection School Of Computing and Information Systems

Despite the importance of open-ended event forecasting for risk management, current LLM-based methods predominantly target only the most probable outcomes, neglecting the intrinsic uncertainty of real-world events. To bridge this gap, we advance open-ended event forecasting from pinpoint forecasting to scatter forecasting by introducing the proxy task of hypothesis generation. This paradigm aims to generate an inclusive and diverse set of hypotheses that broadly cover the space of plausible future events. To this end, we propose SCATTER, a reinforcement learning framework that jointly optimizes inclusiveness and diversity of the hypothesis. Specifically, we design a novel hybrid reward that consists of …

Mab-Dqa: Addressing Query Aspect Importance In Document Question Answering With Multi-Armed Bandits, Yixin Xiang, Yunshan Ma, Xiaoyu Du, Yibing Chen, Yanxin Zhang, Jinhui Tang

Research Collection School Of Computing and Information Systems

Document Question Answering (DQA) involves generating answers from a document based on a user’s query, representing a key task in document understanding. This task requires interpreting visual layouts, which has prompted recent studies to adopt multimodal Retrieval-Augmented Generation (RAG) that processes page images for answer generation. However, in multimodal RAG, visual DQA struggles to utilize a large number of images effectively, as the retrieval stage often retains only a few candidate pages (e.g., Top-4), causing informative but less visually salient content to be overlooked in favor of common yet low-information pages. To address this issue, we propose a Multi-Armed Bandit–based …

Avadclip: Audio-Visual Collaboration For Robust Video Anomaly Detection, Peng Wu, Wanshun Su, Guansong Pang, Yujia Sun, Qingsen Yan, Peng Wang, Yanning Zhang

Research Collection School Of Computing and Information Systems

With the increasing adoption of video anomaly detection in intelligent surveillance domains, conventional visual-only detection approaches often struggle with information insufficiency and high false-positive rates in complex environments. To address these limitations, we present a novel weakly supervised framework that leverages audio-visual collaboration for robust video anomaly detection. Capitalizing on the exceptional cross-modal representation learning capabilities of Contrastive Language-Image Pretraining (CLIP) across visual, audio, and textual domains, our framework introduces two major innovations: an efficient audio-visual fusion that enables adaptive cross-modal integration through lightweight parametric adaptation while maintaining the frozen CLIP backbone, and a novel audio-visual prompt that dynamically enhances …

Robust Graph Learning On The Web: Challenges, Methods, And Applications, Ao Xiang, Yang Liu, Guansong Pang, Yuanhao Ding, Hezhe Qiao, Dawei Cheng, Qing He

Research Collection School Of Computing and Information Systems

Graph learning is transforming web intelligence, powering applications from recommender systems to anomaly detection. However, most existing approaches implicitly assume ideal conditions where training and testing data are accurate, complete, and free from manipulation. In reality, web environments rarely exhibit such stability. Dynamic user behavior, incomplete or outdated content, adversarial interference, and sudden distribution shifts can all erode the reliability of even state-of-the-art models, leading to biased or unsafe outcomes. This tutorial provides a comprehensive survey of emerging strategies for robust graph learning on the web. We first present a structured taxonomy of the principal robustness threats specific to web …

Verbalizing Lightgcn: Direct Learning Of Textual Representations From User-Item Interaction Graph Via Llms, Manh-Khanh Ngo Huu, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

In this work, we propose VerbaLightGCN, a novel LLM-based recommendation framework that integrates the semantic understanding of LLMs with user-item interaction modeling. Traditional collaborative filtering (CF) models typically embed user and item IDs into a latent space to capture interaction signals. However, pretrained LLMs cannot natively interpret these learned embeddings. To bridge this gap, VerbaLightGCN adopts a CF-as-text paradigm, in which collaborative signals are encoded in textual form and directly learned from the user–item interaction graph, and are then combined with semantic information to construct user and item profiles that function as latent embeddings. Inspired by LightGCN, our method retains …

Divide-And-Conquer: Generating Ui Code From Screenshots, Yuxuan Wan, Chaozheng Wang, Yi Dong, Wenxuan Wang, Shuqing Li, Yintong Huo, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Websites are critical in today’s digital world, with over 1.11 billion currently active and approximately 252,000 new sites launched daily. Converting website layout design into functional UI code is a time-consuming yet indispensable step of website development. Manual methods of converting visual designs into functional code present significant challenges, especially for non-experts. To explore automatic design-to-code solutions, we first conduct a motivating study on GPT-4o and identify three types of issues in generating UI code: element omission, element distortion, and element misarrangement. We further reveal that a focus on smaller visual segments can help multimodal large language models (MLLMs) mitigate …

Veribrief: A Multi-Agent Retrieval-Augmented Generation System For Policy Decision Support, Imane Bahji

Electrical and Computer Engineering ETDs

VeriBrief is a multi-agent retrieval-augmented generation (RAG) system for evidence-grounded economic policy analysis. The system orchestrates a five-stage LangGraph pipeline, retrieval, research, analysis, synthesis, and critique, to produce cited, structured responses while detecting out-of-scope queries. An empirical evaluation on eight questions drawn from official U.S. macroeconomic releases compared VeriBrief against a single-pass RAG baseline. The multi-agent system achieved 100% refusal precision on unanswerable analytical queries versus 0% for the baseline. Unsupported claims fell substantially on answerable factual questions. A context-propagation defect discovered during evaluation was diagnosed and corrected. Limitations include failure of the evidence gate on policy-counterfactual queries and a …

Other People's Poverty, Emmanuel Hiram Arnaud, Shaun Ossei-Owusu

Faculty Scholarship

Puerto Ricans have a relationship with the United States that is historically unparalleled. They have been citizens of the United States since 1917, served in every major conflict since World War I, and have been influential members of American culture, politics, and society. Yet, Puerto Rico is not fully part of the United States. The island of 3.2 million people— more than the population of eighteen states—is a U.S. territory. This means the federal government wields its complete and largely unrestrained plenary power over the Island, often treating Puerto Ricans differently than the rest of the United States. This differential …

Winning Economically: A Statistical Analysis Of Payroll Allocation Within Major League Baseball, Ryan St.Clair

Senior Theses

This thesis analyzes payroll trends within Major League Baseball (MLB) across the last ten seasons (2015-2024). By examining spending habits across teams, several strategies have been identified, bucketing teams into profiles that allow for easier comparison and insight into optimizing roster construction.

Team success is measured through two statistics: Winning Percentage and Wins Above Replacement (WAR). Winning Percentage determines which teams succeeded each year, while WAR adds color to each team's record. WAR measures a player's value holistically. Essentially, it shows how many more wins he provides compared to a replacement level player. A replacement level player is a minor …

Integrated Optimization Of Farmland Cultivation And Fertilizer Application: Implications For Farm Management And Crop Production, Onur Boyabatli, Lusheng Shao, Yangfang (Helen) Zhou

Research Collection Lee Kong Chian School Of Business

Motivated by the fresh produce industry, this paper studies a farmer’s joint cultivation and fertilizer (a representative farm input) application decisions facing uncertainties in yield, crop price, and harvesting cost where the latter two are yield dependent and yield is stochastically increasing in the fertilizer application rate. We develop a two-stage stochastic model of a farmer growing a commodity crop in a single season to maximize the expected profit. We then use the model to evaluate the optimal expected harvest volume (a measure of crop production). Our analytical analysis is complemented with numerical experiments calibrated to data. We characterize how …

Cross-Cultural Generalizability Is An Empirical Question [Open Peer Commentary], Shawn K. S. Chan, Wilson Cyrus-Lai, Michael Schaerer, Robbie C. M. Van Aert, Marcel Van Assen, Eric Luis Uhlmann

Research Collection Lee Kong Chian School Of Business

Crowd-sourced replication initiatives reveal that cultural differences in findings, while undoubtedly important in some cases, are often smaller and less systematic than assumed. This makes empirical testing, rather than presumption, exigent. The extent to which developmental psychology theories generalize across cultures is an empirical question, best answered via small- and large-scale collaborations between partner laboratories across the world.

Understanding How Fire Impacts Soil Carbon And Nutrient Cycling: Toward Standardized Reporting Of Fire Metrics For The Integrated Plant-Soil System, Julia B. Gaudinski, Kate Wilkin, Jasquelin Peña, Mary E. Miller, Margaret S. Torn

Michigan Tech Publications

Fire events impact soil carbon (C) and nutrient stocks immediately due to combustion of biomass and organic matter and set up additional post-fire changes to ecosystem inputs and losses. The literature on this topic is expanding rapidly as large and intense wildfires are increasingly affecting communities globally. However, many of these studies do not describe initial post-fire soil conditions adequately or consistently, nor do they link the impacts of fire on C and nutrient cycling to key soil properties and soil inputs, stocks and fluxes. Here we conduct a systematic analysis of 56 review- papers published in 2010 or later …

Deconstructing Systemic Sclerosis Heterogeneity: From Patient Subtypes To Pathogenic Fibroblasts, Rezvan Parvizi

Dartmouth College Ph.D Dissertations

This thesis advances heterogeneity as the central barrier both to interpreting therapeutic response and to identifying the molecular regulators that drive fibrosis in systemic sclerosis (SSc). In SSc, heterogeneity is manifest at every level at which the disease can be measured: clinically, in the variable extent of skin and organ involvement; molecularly, in the distinct gene-expression programs that distinguish otherwise comparable patients; and cellularly, in the diverse fibroblast populations from which the fibrotic signal ultimately arises.

Leveraging longitudinal skin transcriptomics from a large cohort treated with mycophenolate mofetil (MMF), the first study demonstrates that intrinsic molecular subtypes are dynamic rather …

State-Mandated Principal Mentoring And Its Relationship To Leadership Efficacy, Working Conditions, And Student Achievement Across Contexts, Ellen Willoughby

Education Theses and Dissertations

Although principal mentoring has been widely studied, far less is known about whether state-level mentoring mandates function as effective policy levers for improving principal or student outcomes. This sequential explanatory mixed-methods study examined the relationship between state mentoring mandates in principal preparation programs and four outcomes: principal leadership efficacy, occupational stress, pay satisfaction, and student achievement. Phase 1 employed multiple linear regression with state-level data from the 2020–2021 National Teacher and Principal Survey (NTPS), 2022 National Assessment of Educational Progress (NAEP), and 2023 Education Commission of the States mentoring mandate classifications. Phase 2 used semi-structured interviews with four practicing principals …

Improving The Implementation Of Response To Intervention Through Structured Professional Learning Communitiies, Amanda Southerland

Education Theses and Dissertations

This Improvement Science Dissertation in Practice examined how the current Response to Intervention (RTI) framework supported math achievement for fifth-and-sixth grade students at a rural intermediate campus in Northeast Texas. Although Tier 1 and Tier 2 supports were in place, many students continued to struggle to demonstrate meaningful growth in mathematics. The purpose of this study was to evaluate the current RTI framework, identify barriers affecting its implementation, and implement an improvement strategy based on the findings. A mixed-methods approach was used to analyze district benchmark and STAAR data, teacher surveys, and focus group interviews. Findings from the evaluation identified …

Saw-Tooth Slot Antenna Sensor For Dielectric Characterization Of Alcohols, Saline Solutions, And Glucose, Hilary Scott Nkimbeng Cho, Jin W. Choi

Michigan Tech Publications

In this study, a low-profile and saw-tooth-shaped slot antenna sensor is proposed for liquid characterization, demonstrating sensitivity to dielectric variations in glucose, saline, and alcohol-based solutions. The antenna consists of a single-layer Rogers 4003C substrate with a rectangular slot integrated with multiple saw-tooth perturbations on the top side and a modified microstrip feedline with a quarter-wavelength transformer on the bottom side. The saw-tooth geometry enhances electric field concentration within the slot region, thereby improving sensitivity to variations in dielectric properties. When liquids with different dielectric constants are deposited on the saw-tooth region of the antenna, measurable resonance frequency shifts occur, …

In Vivo Evidence Of Blood Flow Slippage: Failure Of The No-Slip Boundary Condition Assumption, Alena Jarolímová, Jaroslav Hron, Karel Tůma, Radomír Chabiniok, Josef Málek, Keshava Rajagopal

Division of Cardiology Faculty Papers

The assumption that blood adheres to vessel walls with zero tangential velocity component, the so-called "no-slip" boundary condition, is a foundational premise of cardiovascular fluid dynamics. Whether the no-slip condition holds in vivo, however, remains unknown. Seven healthy adult volunteers underwent cardiovascular magnetic resonance imaging. With four-dimensional flow magnetic resonance imaging of the descending thoracic aorta and modeling blood as a Navier-Stokes fluid, near-wall blood velocities were quantified, and wall shear stress was calculated based on the measured velocity fields. Within the Navier-Stokes data assimilation framework, tangential wall velocities of ∼30-80% of the mean luminal velocity were consistently obtained. These …

Explainable And Hybrid Machine Learning For Predicting Fatal Crash Risk, Hussein Khanjar, Abdolmajid Erfani

Michigan Tech Publications

Road traffic fatalities remain one of the most persistent public safety challenges, demanding predictive models that are not only accurate but also reliable and interpretable. While numerous machine-learning models have been developed for crash severity prediction, most remain limited in three critical dimensions: they simplify the unit of analysis by focusing only on the driver or the most severe occupant per crash, they emphasize predictive performance while neglecting model confidence and probability calibration, and they often function as black boxes lacking interpretability for real-world decision support. To address these gaps, this study proposes a calibrated hybrid machine-learning framework for nationwide, …

The Anatomy Of Earnings Conference Calls: An Integrative Framework For Management Research, Matthew P. Mount, Gokhan Ertug, Wei Shi, Tengjian Zou

Research Collection Lee Kong Chian School Of Business

Over the last decade, there has been an explosion in the use of diverse data sources by management scholars to observe and capture managerial and organizational constructs that have historically been difficult to access. This surge has been driven by the growing availability of rich, multi-modal data—textual, image, and audio (Luo, Jia, Ouyang, & Fang, 2024)—together with advances in analytical techniques to process and analyze data, such as computer-aided text analysis (Harrison, Thurgood, Boivie, & Pfarrer, 2019), machine learning (Choudhury, Wang, Carlson, & Khanna, 2019; Harrison, Josefy, Kalm, & Krause, 2023), and deep learning (Gouvard, Goldberg, & Srivastava, 2023). These …

Modeling And Forecasting Intraday Spot Volatility, Adam Clements, Daniel P. A. Preve

Research Collection School Of Economics

We propose a multiple-equation regression-based method for modeling and forecasting intraday spot volatility. In this approach, intraday intervals are treated as individual time series, deviating from the common practice of treating the data as one continuous sample. Our empirical study, which spans more than two decades and encompasses six US blue-chip stocks, employs the recent OK volatility estimator developed by Li, Wang, and Zhang (2024) to expose the dynamics of latent intraday spot volatility over time. We demonstrate that the proposed method effectively captures the intricate dynamics of intraday spot volatility and find strong evidence that it outperforms a competing …

Navigating Unemployment Without Unemployment Insurance: Evidence From Singapore, Kim, Lanjie Wang

Research Collection School Of Economics

This study investigates the short-term impacts of unemployment among older workers (aged 50–62) in Singapore, a setting with-out public unemployment insurance. Using monthly panel data from the Singapore Life Panel, we analyse dynamic effects onmajor life outcomes such as income, spending, health, and subjective wellbeing over 2 years post-unemployment. Our findingsreveal substantial initial earnings losses with incomplete recovery: income remains 50.7% below pre-unemployment levels after24 months. Despite this persistent income gap, total household expenditure declines by 9.8% on average over 2 years (rangingfrom 7% to 16% across months). The implied two-year marginal propensity to consume is about 0.182, smaller than …

How Do Sectoral Shocks Shape Future Gdp?, Paul Ho, Danial Lashkari, Pierre-Daniel Sarte

Research Collection School Of Economics

A production sector’s size, as measured by its Domar weight, captures the contemporaneous aggregate effect of its productivity shocks. Any future aggregate effects, however, depend on that sector’s participation in the investment network. We derive a dynamic generalization of Hulten’s theorem in an environment with intermediate-input and investment networks. This generalization, implied by production efficiency alone, decomposes each sector’s Domar weight into an impact and a propagation component. The relative size of these components then determines how persistent the aggregate effects of sectoral shocks are, but cannot be known absent information on the economy’s production structure. We show in a …