Digital Commons Network^™

Novel Chiral Interstellar Molecules: Quantum Anharmonic Ir And Vcd Predictions, Meredith Paik

Dissertations, Master's Theses and Master's Reports

The 2016 discovery of the chiral molecule propylene oxide (C₃H₆O) in the interstellar medium (ISM) has opened new avenues into explaining the origin of biomolecular homochirality on Earth. Thus, studies of chiral molecules in the ISM may be able to reveal more about the mechanism behind homochirality. However, while the search for chiral molecules in space has become an active field of study, astrochemical researchers have yet to detect other chiral molecules in the ISM. For this purpose, numerous characteristics for detectability have been outlined that may facilitate the discovery of other interstellar chiral molecules. With …

First-Principles Investigation Of Quasi-One-Dimensional Van Der Waals Magnets For Advancing Low-Dimensional Spintronics, Alyssa Horne

Dissertations, Master's Theses and Master's Reports

Van der Waals (vdW) magnets have been of great interest for advancing low- dimensional spintronics. A notable example is the quasi-one-dimensional (Q1D) vdW CrSbSe₃, as it is composed of individual one-dimensional units that are held together by the vdW forces. Finding other Q1D vdW magnets that exhibit non-metallic behavior together with long range ferromagnetic ordering is critical in developing next generation spintronics. Here in, using first-principles density functional theory (DFT), we investigate the compositional effects on electronic and magnetic behavior of Cr_1–xMn_xSbSe₃ (x = 0, 0.5, 1). When 50% of Cr is replaced …

Using Automotive Lidar To Reduce The Energy Consumption Of An Ego Autonomous Vehicle, Logan P. Schexnaydre

Dissertations, Master's Theses and Master's Reports

There is significant potential to reduce the energy consumption of the transportation sector through autonomous vehicles. Prior work on autonomous vehicle energy efficiency focuses on the whole system or the control subsystem. Yet, the sensing and processing components, which have direct and indirect effects on net energy use, are less explored. This dissertation fills this gap by modeling and evaluating these effects for lidar sensors, which provide high-resolution spatial data at the cost of high power and processing demands. I apply lidar to the energy-saving tasks of automated vehicle following and road surface profiling. For automated vehicle following, I model …

Methodology Development For Evaluating Relative Heat Checking Resistance Of Open-Die Forge Tooling, Jack F. Schaller

Dissertations, Master's Theses and Master's Reports

Heat checking, characterized by biaxial networks of surface cracks induced by thermomechanical cycling, can cause premature failure of open-die forge tooling. To facilitate the evaluation of heat checking resistance of die steels, a simulation‑informed out-of-phase thermomechanical fatigue (OP-TMF) testing methodology was developed using 4330V steel as a baseline material. Temperature‑dependent material properties and flow stress data were collected and compiled into a material data file for use with finite element analysis software. Forging and cooling scenarios were simulated across a range of die preheat temperatures. Temperature and in-plane strain histories extracted from the die surface provided a foundation for laboratory …

Rapid Austenite Restoration Through Non-Partitioning Transformation In Medium-Mn Steel, Rebekah A. Smith

Dissertations, Master's Theses and Master's Reports

Steel microstructures that contain retained austenite exhibit unique mechanical flow behavior which renders them applicable to high-strength forming, and energy absorbing applications. Austenite stability is predominantly controlled through substitutional alloy enrichment, and during deformation, meta-stable austenite transforms to martensite which induces dramatic work hardening that may enhance mechanical properties. After deformation, these steels have greater yield strength but limited remaining ductility. Restoration of austenite through rapid thermal treatments, after it is expended through deformation, can enable retained austenite to be leveraged for additional deformation. In the present work, a rapid austenite restoration heat treatment following deformation-induced martensite transformation is presented …

Enhancing Coastal Vulnerability Assessments And Policy Impacts On Socioeconomic And Environmental Equity In Michigan's Great Lakes Communities, Esther N. Acheampong

Dissertations, Master's Theses and Master's Reports

Accelerating shoreline erosion, fluctuating lake levels, and climate-induced hazards are transforming the Great Lakes’ freshwater coasts, exposing the limitations of static and inequitable management frameworks. This dissertation investigates how Michigan’s coastal governance systems produce and manage vulnerability along the Lake Michigan shoreline by integrating geospatial modeling, institutional policy analysis, and environmental justice theory. It argues that both physical processes and institutional designs co-determine patterns of exposure, protection, and equity. The research begins by developing a refined Coastal Vulnerability Index (CVI) tailored for lacustrine environments, applying it to Muskegon County to assess how shoreline change, armoring, and seasonality influence localized risk. …

Slip Kinematics And Structural Analysis Of The Keweenaw Fault System From Lake Linden To Hancock, Michigan, Katherine M. Langfield

Dissertations, Master's Theses and Master's Reports

The Keweenaw fault is a crustal-scale fault spatially associated with Mesoproterozoic rocks of the Midcontinent Rift System. Along the fault, older Portage Lake Volcanics have been thrust southeastward over younger Jacobsville sandstone. Ideas on the fault’s origin, from oldest to most recent, include that it is: (1) a reverse fault, (2) a normal fault formed during midcontinent rifting that was reactivated and inverted to a reverse fault during the Grenville orogeny, and (3) a detached thrust fault system initiated during the Grenville orogeny.

This thesis is based on a U.S. Geological Survey EdMap grant to remap a portion of the …

A Literature Review Of Adoptive Cell Therapy (Act) In Non-Small Cell Lung Cancer (Nsclc) With Emphasis On Chimeric Antigen Receptor (Car) T Cell And Tumor Infiltrating Lymphocyte (Til) Therapies, Brianna Wickham

Honors Program Theses

Non‑small cell lung cancer (NSCLC) accounts for the majority of lung cancer diagnoses and remains a leading cause of cancer‑related mortality despite advances in surgery, chemotherapy, radiation, and immune checkpoint inhibitors. While immunotherapy has improved outcomes for some patients, many develop treatment resistance or experience significant toxicity, highlighting the need for alternative therapeutic strategies. Adoptive cell therapy (ACT), which involves the infusion of autologous immune cells expanded or engineered ex vivo, has demonstrated substantial success in hematologic malignancies and is now being investigated for use in solid tumors such as NSCLC. This literature review examines the current state of ACT …

Real Time Waste Classification Using Deep Learning: Comparing Mobilenetv2 And Resnet 18 With Transfer Learning And Fine Tuning, Abdul Moaiz

ICT

Waste contamination is a major problem all over the world. The Environmental Protection Agency reports that over two thirds of waste found in general household and commercial bins could have been placed in the recycling or organic waste bins instead in Ireland, with food waste and plastics being the most common misplaced items. This project presents a deep learning solution to classify nine categories of waste from camera images in real time with the goal of helping users sort waste correctly at the source. Following the CRISP DM framework, two convolutional neural network architectures were trained and compared, MobilenetV2 and …

Bitcoin Prediction System Usind Machine Learning Techniques, Carolina Azevedo De Castro

ICT

This project investigated the use of machine learning techniques to predict short-term Bitcoin price direction using historical market data obtained from Yahoo Finance. Following the CRISP-DM methodology, the dataset was analysed, prepared, and transformed through feature engineering techniques including moving averages, volatility indicators, return measures and price position metrics. Multiple classification algorithms were evaluated, including Bayesian Classification, K-Nearest Neighbour, Decision Tree, Random Forest, Logistic Regression, Support Vector Machine and XGBoost. Several optimisation strategies were also tested, including feature selection, hyperparameter tuning, feature scaling and class weight balancing. Results showed that predicting short-term Bitcoin price movements remains challenging, with most models …

Predictive Maintenance For Manufacturing Equipment, Paloma De Andrade Batista

ICT

Unplanned equipment downtime is a significant challenge in manufacturing, resulting in substantial productivity losses and operational costs. Predictive maintenance, enabled by machine learning and big data analytics, offers an opportunity to identify potential equipment failures before they occur and improve maintenance efficiency. This report extends a previous capstone project that applied Random Forest and Logistic Regression to the AI4I 2020 Predictive Maintenance Dataset. The current study expands the analysis by incorporating XGBoost, systematic hyperparameter optimisation, cross-validation, and SHAP-based model interpretability. In addition, SWOT and PESTLE analyses, alongside a legal and ethical assessment, examine the broader strategic and responsible implementation of …

Predicting Loneliness Among Older Adults In Ireland Using Supervised Machine Learning, Ariadne Chaves Miranda

ICT

Over the last two decades, technology has grown exponentially and has facilitated communication that helps individuals remain connected. However, this has also contributed to social isolation and lack of physical interaction. One consequence of this phenomenon is loneliness, which is understood as an unpleasant subjective state of discrepancy between the desired amount of companionship or emotional support and what is available in the person’s environment (Prohaska and Burholt, 2020). In the European context, Ireland has emerged as the loneliest country in Europe with 20% of its population that have reported feeling lonely most or all the time (Schnepf et al., …

The Role Of Parent Involvement In Enhancing Pediatric Speech And Language Therapy, Katie Lynch

Honors Program Theses

As speech-language pathologists, we provide speech and language therapy for children in a variety of settings. It is crucial that we include a client’s family in therapy because family involvement has been shown to promote generalization of skills learned in therapy to a child’s typical environment. Despite this, various barriers exist for families as they aim to support their child’s speech and language goals. This literature review examines how speech-language pathologists can gain an understanding of these barriers and how they can promote family involvement in pediatric speech and language therapy.

Using Simulations And Machine Learning To Improve Routing Algorithms In Wireless Sensor Networks, Luke Abels

Honors Program Theses

Wireless sensor networks (WSNs) are widely used in fields such as environmental monitoring, smart agriculture, disaster response, and other applications where low-power devices must communicate reliably over time. Because these networks operate under limited energy and communication constraints, routing and broadcast strategies strongly influence performance, scalability, and network lifetime. This thesis examines how simulation and machine learning can be used to study interference-aware broadcasting in WSNs. The project first evaluates the usefulness of existing network simulation tools, including ns-3, and then describes the development of a custom Python simulator designed for rapid experimentation with broadcast behavior, mobility, and signal-to-interference-plus-noise ratio …

Approximation Algorithms For Center-Based K-Clustering, Ankita Sarkar

Dartmouth College Ph.D Dissertations

Center-based metric k-clustering is a rich class of well-studied optimization problems. These include the classical k-center, k-median, and k-means problems. In all these problems, a client set C and a set F of candidate facilities live in a metric space. We are required to pick or "open" k facilities S ⊆ F to minimize some objective function, potentially subject to further constraints on S. Such problems are NP-hard, which has encouraged a long line of research in approximation algorithms for them.

In this thesis, I present research on center-based k-clustering in scenarios where either …

Designing Narrative-Based Ai Assistance For Sensemaking In Collaborative Environments: Case Studies In Education And Dementia Care, Dylan Edward Moore

Dartmouth College Ph.D Dissertations

This thesis addresses a gap in the human-computer interaction literature regarding the design, development, and evaluation of narrative-based AI assistance for collaborative, complex problem solving. I explore this design space through three case studies across the domains of education and dementia care. This work encompasses multi-year industry partnerships and longitudinal fieldwork, user-centered design, dataset curation, model training, and system evaluation.

Specifically, the first case study considers a story-based web platform for teaching AI literacy through peer-generated, personalized narrative scaffolding. Learners on the platform showed significant knowledge gains and other learning-related outcomes. To describe the novel design of this system, I …

Characterizing Glacial Sediments From The Cincinnati, Ohio Area By Analyzing Grain Size Distribution And Elemental Composition, Laura Comstock

Honors Program Theses

Reconstructing the history of ice sheet dynamics is essential for understanding how past climate change has shaped modern landscapes. The Laurentide Ice Sheet advanced and retreated multiple times over North America during the Pleistocene Epoch. Although there is widespread sedimentary evidence for the most recent glacial episode, much of the evidence of older glaciations has been overwritten by more recent glacial advances. This study focuses on Paddison Run, an exposed Pleistocene sequence near Cincinnati, Ohio, that has previously been interpreted as Illinoian in age. Five distinct units were identified within the exposure, based on centimeter logging of this section, high-resolution …

Consensus Decision-Making: Decision-Making Model Of Chinese Constitutional Review, Songfeng Li

Emory International Law Review

The judgment model of constitutional review in China adopts a consensus-based judgment model involving multiple stakeholders, including review authorities, drafting authorities, relevant interest parties, and the general public. Through multi-level, multi-stage, and multi-round interactive communication and negotiation, consensus is reached on constitutional judgments. This judgment model aligns with the power division political system under the NPC system, reflecting the institutional concept of people’s sovereignty and the cultural foundation of valuing harmony. It is also a result of the decentralization of constitutional review authority leading to insufficient power for actual reviewers, the parallel nature of factual and normative judgments in constitutional …

Treating Social Media Corporations As Quasi-State Actors To Address The Use Of Artificial Intelligence In Content Moderation, Michael T. Tiu Jr.

Emory International Law Review

Corporations have become powerful actors in the international system. They have the potential to disrupt the protection of values that states have been performing for decades. One of these values–freedom of expression–has been the recipient of impact of emerging technologies owned by corporations. Social media platforms have become new governors of expression. Content moderation rules cause adverse impacts on freedom of expression. The vagueness of certain criteria and the inconsistency of their application have led to censorship of speech which would have been protected offline. This situation is exacerbated by the use of artificial intelligence in content moderation, owing to …

A Practitioner’S Guide To Panel Data Quantile Regression, Antonio F. Galvao, Carlos Lamarche

Economics Faculty Publications

Quantile regression for panel data has become a common model of interest for econometricians and statisticians. The theoretical literature has addressed important questions, including identification, estimation, and statistical inference. Although recent advances have enabled practitioners to estimate flexible models under a wide range of assumptions, practical issues have not been fully addressed. In this paper, we offer a guide to empirical practice intended to help applied researchers navigate the challenges of estimation and inference for panel quantile models. We also present a series of practical recommendations and illustrations, emphasizing both “why” and the “how” to help researchers with the implementation …

A Simple Statistical Tool To Correct The Daily Temperature Effect On Dielectric Soil Matric Potential Sensor Readings, Sebastián Bravo Peña, Meindert Commelin, Ole O. Wendroth

Plant and Soil Sciences Faculty Publications

High-resolution time series recorded by soil water dielectric sensors are often affected by other processes. Dielectric soil matric potential sensors, such as the TEROS 21, exhibit temperature sensitivity, resulting in deviations of readings from the true value due to soil temperature fluctuations. However, methods for correcting this effect remain limited. The objective of this study was to create a straightforward, scale-based statistical approach to mitigate the influence of daily temperature oscillations on matric potential dielectric readings. The temperature sensitivity correction function (TSCF) identifies, quantifies, and smooths diurnal fluctuations caused by soil temperature dynamics. We provide a detailed description of the …

Applying Photovoice To Uncover Fundamental Causes Of Health Inequality In Local Health Contexts, Marisa Booty, Madelyne G. Culbertson, Mason Taylor, Dakota Heise, Heather Stone, Katherine Leanne Kommer, Jennifer Gulley, Jeanette Hart, Christina Nentwick, Margaret Mcgladrey

Sociology Faculty Publications

Introduction: Participatory action research methods like Photovoice are uniquely equipped to identify structural determinants of health based on lived experiences of how they influence proximal and distal population health outcomes. This study uses Photovoice data to examine how structural determinants impact community health needs.

Methods: Qualitative thematic analysis used focus group discussion data (25 transcripts) from four Kentucky counties that embedded Photovoice into their local health department community health assessment processes. Coded excerpts were examined for ways in which participants' community health concerns reflected structural issues rather than individual health behaviors.

Results: Participants perceived issues such as houselessness, food insecurity, …

Adversarial Robustness In Biomedical Time-Series Models, Rohan Tiwari

Bioengineering Theses

This study investigates adversarial vulnerabilities in deep learning models for biomedical time-series classification across two clinically important modalities: electrocardiography (ECG) and electroencephalography (EEG). Using the MIT-BIH Arrhythmia and CHB-MIT seizure datasets, I evaluate time-domain attacks (FGSM, PGD), Fourier-domain constrained attacks, and learned spectral perturbations designed to reveal modality-specific sensitivity patterns. Across both tasks, a consistent trend emerges low-frequency components (0–5 Hz) constitute a dominant axis of adversarial vulnerability, with perturbations in this range producing the steepest degradation in classification performance. In ECG models, protecting the physiologically relevant QRS band (5–20 Hz) significantly improves robustness, whereas EEG models remain highly sensitive …

Results Of The Second Ice Shelf-Ocean Model Intercomparison Project (Isomip+), Claire K. Yung, Xylar S. Asay-Davis, Alistair Adcroft, Christopher Y. S. Bull, Jan De Rydt, Michael S. Dinniman, Benjamin K. Galton-Fenzi, Daniel Goldberg, David E. Gwyther, Robert Hallberg, Matthew Harrison, Tore Hattermann, David M. Holland, Denise Holland, Paul R. Holland, James R. Jordan, Nicolas C. Jourdain, Kazuya Kusahara, Gustavo Marques, Pierre Mathiot, Adele K. Morrison, Yoshihiro Nakayama, Olga Sergienko, Robin S. Smith, Alon Stern, Ralph Timmermann, Qin Zhou

CCPO Publications

Ocean-driven basal melting of Antarctic ice shelves plays an important role in the mass loss of the Antarctic Ice Sheet. Ice shelf cavity-resolving ocean models are a valuable tool for understanding ice shelf-ocean interactions and for simulating projections of ice shelf and ocean states under future climate. Designed to assess the current state of ice shelf–ocean modelling, the second Ice Shelf–Ocean Model Intercomparison Project, ISOMIP+, consists of 12 ocean model configurations submitted with a common, idealised experimental setup. Here, we focus on the experiments Ocean0–2 (Asay-Davis et al., 2016), which are ocean models with idealised, static ice …

Intermittent Versus Continuous Reinforcement: Which Is More Effective For Skill Acquisition In Children With Adhd Using Precision Teaching?, Samantha Pulling

Masters Theses

Children with Attention Deficit Hyperactivity Disorder (ADHD) can experience challenges learning academic skills, possibly because of altered reinforcement and learning processes. Reinforcement is commonly used to support learning and adaptive behavior; however, research examining continuous and intermittent reinforcement schedules for children with ADHD has produced inconsistent findings. Precision Teaching (PT) is a fluency-based, data-driven instructional approach that emphasizes rate and celeration of behavior and has been shown to effectively support academic learning for individuals with ADHD. This study compared the effects of a continuous reinforcement schedule with a small reinforcer and an intermittent reinforcement schedule with a larger reinforcer on …

Wedges: A Microeconomic Perspective On Misallocation, Lauren Falcao Bergquist, Danial Lashkari, Eric Verhoogen

Discussion Papers

This chapter takes stock of what has been learned from the recent micro-development literature about wedges—mechanisms generating dispersion in marginal revenue products of factors across firms, which are commonly interpreted as indicators of misallocation. We present a general theoretical framework that allows us to consider several different types of wedges simultaneously. We argue that it is important to distinguish between between technological wedges, which are present even in the efficient allocation that would be chosen by the social planner, and distortionary wedges, which are present in market equilibrium but not the social planner's allocation. Not all wedges, as we have …

Rethinking Transnational Adjudication: The Normative Foundations Of Institutional Design, Sanctions-Related Arbitration Frameworks, And Digital Recognition Systems, Avaskhan Asanaliyev

SJD Dissertations

This dissertation examines how emerging judicial and dispute resolution architectures can sustain cross-border commerce, investment, and enforcement in the post-Soviet space and beyond, at a time of institutional fragility, geopolitical tension, and rapid digitalization. Drawing on the experience of Kazakhstan, Russia, Ukraine, and key global hubs, it argues that institutional innovation in courts, arbitration, and enforcement mechanisms is central to rebuilding credible governance frameworks for international business. It does so through three interconnected studies that together explore the evolution of modern adjudication: first, through the transplantation of a common law judiciary model within a civil law state; second, through the …

Blurred Lines: Did Booker Change Federal Sentencing Outcomes?, Hugh Mundy

UIC Law Open Access Faculty Scholarship

No abstract provided.

Fear, Delay, And Preventable Death: Rethinking Wyoming's Legislative Framework To Reduce Barriers In Overdose Emergency Reporting, Shoshana Sangros

Wyoming Law Review

This Comment asks whether Wyoming’s current immunity framework for reporting overdoses truly reduces delays in emergency treatment when distance, weather, and limited emergency medical service (EMS) capacity already regularly extend response times. It proposes that by amending two Wyoming statutes and funding statewide education, the goal of reducing barriers to calling 9-1-1 to report overdoses can be better achieved, and residents better protected. To support these proposed changes, Part II provides a concise account of relevant Wyoming statutory protections. Part III proposes specific amendments that would address the on-the-ground challenges of the Wyoming emergency response system. These adjustments will utilize …

Medications For Opioid Use Disorder In Correctional Facilities: A 2022 Cross-Sectional Survey Of Health Care Staff, Claire Wolfe, Sabrina Gaiazov, Dr. Pamela Valera, Will Mullen, Ross Macdonald, Christian Heidbreder

School of Social Work Faculty Publications

A national, anonymous, online survey was administered inviting 3,161 correctional health professionals to examine the associations between facility characteristics and the availability of medications for opioid use disorder (MOUD) in jails and prisons. Responses from 268 participants representing 212 correctional facilities were analyzed. We used multivariate logistic regression to identify associated facility characteristics, and open-ended responses were analyzed using content analysis. Facilities in the Western United States had higher odds of providing MOUD compared with those in the Midwest (adjusted odds ratio [AOR] = 3.67, 95% confidence interval [CI]: 1.28–10.99). Jails had higher odds of offering MOUD than prisons (AOR …